Ongoing projects

Situational aware navigation and mapping (SITANAV). 01/04/2024 - 31/03/2028

Abstract

SITANAV aims at increasing the reliability and robustness of Autonomous Vehicles (AV) operating in logistic, industrial and agricultural facilities by focusing on the following problems raised by companies in the consortium: 1) the limited flexibility of AVs in complex environments, 2) the high costs when localization requires additional infrastructure, 3) the high deployment and layout reconfiguration costs, and 4) the high memory footprint of discrete metric maps that hinders applications in large environments. SITANAV's key idea to overcome these problems is to increase the situational-awareness in navigation and mapping capabilities of autonomous vehicles. This will provide AVs with higher levels of self-adaptation based on the current situation through explainable decision-making via semantic maps and reasoning. There are three main technological barriers that SITANAV has to overcome: 1) lack of models fordescribing situations, 2) lack of capabilities to reason about objects and maps, and 3) lack of situational awareness in AVs' decision-making for navigation. The approach to remove these barriers is a framework that combines a metric-semantic map with situational models, which describe a set of relations that connect an AV's motion and perception capabilities to a particular situation. For example, when the AV can find the appropriate pieces of information to infer the current situation from the perceived environment, it can select and configure its perception and control behaviors (situational aware decision-making) to achieve the desired robustness and performance for the application at hand (e.g., detecting the situation of a partly blocked pathway and switching to a narrow-space navigation). The proposed method will extend existing graph-based models and tools with new features, reasoning, and query answering mechanisms, to gradually increase AVs' situational assessment capabilities. The improvements will be in small-scale iterations, following a continuous integration approach. This will be accomplished by two running demos (indoor and outdoor) with increasing complexity throughout the project. The SITANAV models and software are designed with forward compatibility in mind, because we can now already foresee many future extensions, such as new types of semantic features, memory and learning capabilities, and the integration of task planning.

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  • Research Project

Conditioned harsh outdoor environment for perception systems of autonomous applications (CAVE). 01/02/2024 - 31/01/2026

Abstract

Autonomous mobile systems might fail for many reasons, but one of them is when the harshness of the environment increases. It is difficult for OEMs, integrators, sensor and hardware components providers to design a robust autonomous mobile system based on traditional testing methods. Especially perception systems are challenged in realistic and relevant harsh conditions (e.g. rain, fog, direct sunlight). Currently, testing of perception systems is done by waiting for these conditions to happen in real-life – which can easily cost weeks of waiting. When an update is done on the hardware of the perception system (e.g. a coating on the lens is added) the exact same test is needed to verify an improvement. However, in real-life this exact same harsh condition cannot be reproduced. So, there is a need for a modular, validated testing facility that allows controllable and measurable conditions, to enable repeatable and controlled harsh conditions. CAVE_INFRA aims to develop a fixed perception test facility which can control and measure rain, snow, fog, illumination, dust and debris conditions, including its digital twin and a real-life validation. We aim to provide the following services: i) Sensing hardware (incl coatings/cleaning systems) and software performance evaluation in harsh conditions, including benchmarking to support sensor selection ii) Harsh condition model and/or sensor model derivation iii) Training or validation of AI models for objects / human detection and pose estimation iv) Degradation tests in harsh conditions v) Generate test data and scenarios that can be used for driving out own research but also for certification purposes and discussions with certification bodies such as TuV. To produce the harsh conditions in realistic scenarios, there are different actuation systems foreseen to respectively actuate the perception system under test, the target objects to be detected, and some of the generated conditions such as diverse illumination systems to create dynamic contrast.

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  • Research Project

The role of the hip capsule in patient outcome after hip arthroplasty. 01/01/2024 - 31/12/2027

Abstract

Passive energy storage and return has long been recognized as one of the central mechanisms for minimizing the energy cost needed for terrestrial locomotion. Although the hip capsule resides the strongest ligaments in the body, its potential role in energy-efficient walking remains unexplored. Increasing our understanding of soft-tissue balancing following THA could help prevent instability and improve early and long-term hip function. Clearly, our understanding of the hip capsule and its role in human mechanics remains largely incomplete. This research proposal aims to address this important gap by investigating the active and passive role of the hip capsule in hip functioning by examining the impact of implant design, anatomical variance and surgical handling on the properties of the hip capsule. This research will inform the development of improved surgical techniques and implant designs that can optimize patient outcomes and enhance long-term performance following hip arthroplasty.

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  • Research Project

Lower limb instability: the missing link between knee and ankle. 01/01/2024 - 31/12/2027

Abstract

Sport injuries account for 10-20% of all acute injuries treated in the emergency room. From this, the most common injuries are knee and ankle injuries. Injury-prevention techniques rely on understanding the injury mechanisms. The focus in this project will be on anterior-cruciate ligament (ACL) rupture in the knee joint and high ankle sprains (syndesmosis injury) as they are difficult to diagnose and often are misdiagnosed potentially leading to chronic instability. To improve diagnosis, a novel imaging technique, standing CT, is used as knee and ankle joints can be imaged under standing conditions rather than the currently used supine position. A novel medical device is developed to extend the standing CT from static testing to dynamic testing. The prototype allows for internal/external rotation and varus/valgus rotation in the ankle joint to simulate different positions of the foot. Kinematic measurements allow for measurement of the joint laxity in the knee and ankle, which has been focus of the PI's previous research. ACL deficient knees will be tested in-vitro to define when ACL rupture occurs. Ankle syndesmosis conditions will be simulated in an in-vitro test validating the new prototype. The final step in this research is a first-in-human test in the standing CT to evaluate if the position of the foot is inducing ACL rupture or high ankle sprains. As follow up of this project, an IOF project will be taken on to bring the device on the market.

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Robotic Safe Adaptation In unprecedented Situations (RoboSAPIENS). 01/01/2024 - 31/12/2026

Abstract

The robots of tomorrow will be endowed with the ability to adapt to drastic and unpredicted changes in their environment including humans. Such adaptations can however not be boundless: the robot must stay trustworthy, i.e. the adaptations should not be just a recovery into a degraded functionality. Instead, it must be a true adaptation, meaning that the robot will change its behavior while maintaining or even increasing its expected performance, and stays at least as safe and robust as before. RoboSAPIENS will focus on autonomous robotic software adaptations and will lay the foundations for ensuring that such software adaptations are carried out in an intrinsically safe, trustworthy and efficient manner, thereby reconciling open-ended self-adaptation with safety by design. RoboSAPIENS will also transform these foundations into 'first time right'-design tools and robotic platforms, and will validate and demonstrate them up to TRL4. To achieve this over-all goal, RoboSAPIENS will extend the state of the art in four main objectives. 1. It will enable robotic open-ended self-adaptation in response to unprecedented system structural and environmental changes. 2. It will advance safety engineering techniques to assure robotic safety not only before, during and after adaptation. 3. It will advance deep learning techniques to actively reduce uncertainty in robotic self-adaptation. 4. It will assure trustworthiness of systems that use both deep-learning and computational architecturesfor robotic self-adaptation. To realise these objectives, RoboSAPIENS will extend techniquessuch as MAPE K (Monitor, Analyze, Plan, Execute, Knowledge) and Deep Learning to set up generic adaptation procedures and also use an SSH dimension. RoboSAPIENS will demonstrate this trustworthy robotic self-adaptation on four industry-scale use cases centered around an industrial disassembly robot, a warehouse robotic swarm, a prolonged hull of an autonomous vessel, and human-robotic interaction.

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ABN HaFreeS MVP Prototype. 01/01/2024 - 31/12/2024

Abstract

In this project we investigated during the first phase (IOF-POC ABN HaFrees Feasibility) whether it was possible to develop a hands-free kit for bicycles. The main goals here were ease of use and call quality at speeds above 10 to 15 km/h. To this end, we mapped the market, from which it became clear that the first focus should be on the functional user (i.e. the professional who wants to use his work-related commute by bike to call colleagues, customers, etc.). The first tests showed that a significant suppression of wind noise is possible using several techniques (selection of good microphones, the choice of an optimal arrangement of each individual microphone combined in an optimal configuration, appropriate shielding i.c.w. the right signal processing algorithms). The techniques on their own do not provide sufficient improvement, but the delta is sufficient so that the combination should allow for a quality conversation at 25km/h. In this second phase of the project, we want to develop a minium viable product (MVP) prototype, which should allow to (1) characterize the product on its main qualities, (2) benchmark the product against competing products, (3) set up tests in view of user feedback and (4) define the further direction of the valorization. An essential hurdle here is the intellectual protection of the technology.

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Multi-Port Wireless Power Transfer Systems via Electric Coupling. 01/11/2023 - 31/10/2025

Abstract

This research proposal focuses on a multi-port wireless power transfer system that applies electric coupling to transfer energy from one or more transmitters to one or more receivers. The fundamental research question is how novel optimization algorithms can keep the operating conditions of this capacitive system with an unpredictable electric coupling optimized, depending on the chosen optimization goal. This includes determining the suitable models and fundamental relationships between the system characteristics (including its unpredictable coupling) and the different optimization gains. An important aspect is the experimental validation of the models via a low power setup, containing a versatile driver in order to allow easy frequency adaptation. More specifically, the contributions of this project will be the following: (i) Development of a model describing quantitatively the fundamental relationships between varying couplings and the (relative) variation of the impedance compensation networks. (ii) Modelling the so called "frequency bifurcation phenomenon" for multi-port systems. (iii) Determining and applying optimization algorithms for different scenarios, i.e. applying impedance and frequency adaptations based on a feedback procedure in order to keep the multi-port system in its (near-to) optimal operating condition, and finally (iv) validation of the aforementioned models and algorithms by simulation and experiment.

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Creating Harmony Between Prosthesis, User and Control Theory. 01/11/2023 - 31/10/2025

Abstract

Lower limb amputations often severely restrict patients when trying to perform activities of daily living, even when using prostheses. Active lower limb prostheses are a promising alternative to the more common passive prostheses but even those still have significant limitations and shortcomings. This project aims to overcome a number of those limitations and shortcomings through the development of a novel control strategy for active lower limb prostheses. The novel control strategy will be widely applicable and will consist of a novel classifier, a novel variable impedance control and novel 'amputee in the loop' learning algorithms. The strategy will be tested on two different hardware platforms and for varying activity patterns and contexts. Performance in each setting will be measured via well-designed evaluation processes with a focus on patient reported outcome measures (PROMs). The hypothesised outcomes with respect to the state-of-the-art are: a higher number of supported activity scenarios, high classification accuracy, a more natural switching of modes, high anti-interference capability, a reduced need for parameter tuning, increased system simplicity and reliability. This will bring significant improvements of the quality of life for active prosthesis users as well as socio-economic benefits in the prosthetics sector.

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Drive Line Concept Optimization. 01/10/2023 - 30/09/2025

Abstract

he AnCoOpt project aims to develop tools and methodologies for the conversion of customer inquiries into optimal machine concepts for electric positioning applications. This is achieved by minimizing component costs, energy consumption, and material usage, while maximizing performance through the utilization of commonly used CAD tools. The project specifically targets Flemish machine manufacturers, engineering consultants, and providers of drive components and CAD software.

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Natural objects rendering for economic AI models (NORM.AI). 01/09/2023 - 31/08/2027

Abstract

Natural objects (vegetables, fruits, food, etc.) are omnipresent in different industrial applications: food sorting, vegetable spray treatments, precision & automated farming, etc. Automating these applications to deal with large variabilities of natural objects (object's detection, recognition, pose estimation, etc.), requires innovative technologies that are enabled by Artificial Intelligence (AI) that has the ability to generalize to variabilities. However, training these AI models would require thousands of images / videos with detailed annotations of different items. In the state of the art, one needs >10k images to (re-)train an AI model with an accuracy of >90%, when, in average one minute is needed to annotate one 'real' image, however these can increase drastically depending on the use case at hand and the variability around it. The more variability one wants to cover, the more training images are needed. These findings clearly indicate that in order to be able to deploy AI models in the industrial applications, innovative techniques are highly needed to remove the burdens of data annotations2. These techniques need also to be easily usable by end users to avoid large amount of manual work to update the proposed methodology to new applications. NORM.AI builds further on the successful results from PILS SBO3,4, where rendering techniques were applied to industrial products with CAD (Computer Aided Design) information, to retrieve AI (synthetic) training data from updated CAD with radiance models. While CAD facilitates synthetic data generation in PILS SBO by providing a reference model to start rendering from, the goal of NORM.AI project is to extend this research to Natural objects where no CAD is available. Therefore, defining a reference model to start rendering from, is part of the research in the project. Creating variations from the reference model that takes both spatial & time changes of the natural objects and the natural scenes, as well as finding a sweet spot between real data augmentation techniques & synthetic data generation techniques constitute another research challenge in the project. This research will allow to identify economic scenarios of training data generation, taking into account their effect into AI model's accuracy and robustness. The project focuses into three research applications: 1- Food sorting applications, where 2D images are used to detect & sort fruits & vegetables, as they are coming, for example, in a conveyor system. 2- Crop monitoring applications, where images from 2D cameras, for example, installed in a harvester, are used to detect vine's rows, crop distribution, etc. 3- Weed monitoring applications, where 2D images guide a spraying system to locally sprayweeds in a high precision.

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eMotioniser: Development of an online tool for optimal designing of electrically driven positioning applications. 01/09/2023 - 31/08/2024

Abstract

Designing an electrically driven positioning driveline involves lots of dimensioning and selection. Selecting the correct components and designing the motion profiles, machine geometries, and controllers, … all have a major impact on the initial component cost, required electrical energy to drive the application, and machine performance …. In other words, each selection and design choice can be considered a design parameter in an optimisation that maximises performance, such as machine throughput and simultaneously allows the minimisation of cost and required electrical energy. In 2017, our research group started developing algorithms to optimise the design of electrically driven machines. In cases where we applied our algorithms, it is not uncommon to see a reduction in required electrical energy of 67%, while at the same time, the component cost could be reduced by 30%. In other cases, we could improve the accuracy by 93% or improve the speed of the machines by 43%. All cases handled by our research group clearly show the potential benefits for industrial machine builders in terms of cost minimisation and performance maximisation. However, the algorithms we developed can only create value if we expand the scope of possible industrial usersinterested in applying our techniques beyond our local contacts with whom we regularly collaborate. Each machine builder in Europe and worldwide can benefit by applying our algorithms! To enable this European and worldwide outreach, an online tool which can be conveniently used by small up to international machine builders is envisaged. Such a tool should run our algorithms in the back with a graphical user interface that only requires machine parameters known or identifiable by the envisaged machine designers. This project contains two important parts. First of all, the concerned web tool should be developed. Secondly, the best path to a self-sustaining tool will be initiated.

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Hunting in the understory: Efficient foraging strategies of bats in acoustically complex environments. 01/04/2023 - 31/03/2024

Abstract

For the detection of their prey, echolocating bats produce ultrasonic calls and listen for echoes reflected off the insects. Gleaning bats hunt by taking resting prey from the vegetation. They hunt in an acoustically highly challenging and complex environment, such as the forest understory. As active flight is energetically very costly and the great majority of understory leaves do not hold resting prey, bats must have developed behavioural and acoustical strategies to efficiently check a vast amount of vegetation surfaces for the presence of prey. Here, I investigate which underlying foraging strategy echolocating bats use to efficiently search for resting prey in the forest understory. State-of-the art stereo high-speed video recordings synchronised with multi-microphone array recordings will be used to observe bats in a behavioural experiment searching for prey randomly placed on leaves of an artificial vegetation. To analyse the bats' 3D flight-paths and the corresponding echolocation behaviour I will train neural networks to perform automated pose tracking of the bats' foraging behaviour. The combination of detailed, three-dimensional behavioural and acoustic analysis will lead to a better understanding of the underlying mechanisms of efficient prey detection and foraging behaviour of bats in structurally and acoustically complex environments. Furthermore, the project will also offer the opportunity to inform and inspire biomimetic methods and applications for efficient acoustic object detection.

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Sparse interpolation for high-dimensional mechatronic co-design. 01/01/2023 - 31/12/2026

Abstract

The design and engineering of electrically driven machine mechanisms increasingly rely on optimisation. This allows the minimisation of objectives such as the initial component cost or electrical energy required to drive these machines, all without compromising the performance. Heuristic optimisers, popular in mechatronics, often result in local optima and so leave a significant untapped optimisation potential. Different domains such as trajectory, geometry, and controller should be optimised simultaneously in a co-design approach to find the global minimum. Therefore, an explicit model of the design variable's impact on the objective is required. However, the data collection necessary for such a high-dimensional model, simultaneously considering all the design parameters, results in an explosion of the needed number of motion simulations. So, the co-design objective is only attainable if the model can be built from a minimal number of simulations. Through recent developments in multi-dimensional data fitting techniques, a practically feasible method for co-design in a high-dimensional setting may now become available for the first time.

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Capacitive Wireless Power Transfer for MIMO Configurations. 01/10/2022 - 30/09/2026

Abstract

Capacitive wireless power transfer (CPT) applies the electric field to transfer energy from a transmitter to a receiver without the need of physical connections. However, depending on the distance between transmitter and receiver, and their relative alignment, the system performance varies. A CPT system that automatically positions itself in the optimal working point, regardless the value of the unpredictable coupling, is therefore necessary. This is in particular challenging for a setup with multiple transmitters and multiple receivers, i.e., a Multiple Input – Multiple Output (MIMO) configuration. The objective of this project is to determine the necessary fundamental relationships to enable and implement algorithms to keep the operating conditions of a MIMO CPT system optimized.

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Echo-acoustic signalling of aposematic and cryptic insects – A bat inspired modelling approach (EchoBug). 01/09/2022 - 31/08/2024

Abstract

In the arms race between prey and predators, diverse anti-predator defence mechanisms evolved. To avoid predation, many insects developed camouflage (crypsis) or chemicals that render them distasteful or toxic. To warn of their unpalatability, many insects evolved striking warning colours or patterns (aposematism). Insects comprise most of the diet of bats. Some of these nocturnal predators glean resting, silent, motionless diurnal insects from the vegetation. Instead of using vision during foraging, they produce ultrasonic calls and detect their prey through echolocation. Here, I want to research whether visually cryptic or aposematic insects also have cryptic or aposematic acoustic reflection properties, to hide from or signal their unpalatability to echolocating bats. I will use bio-inspired sensor systems to acquire echo-acoustic sonar recordings of selected insect species and conduct behavioural prey-detection and -capture experiments using live bats to explore the prevailing acoustic predator-prey interactions. Based on these experiments, I will apply neural network algorithms for classifying and analysing the distinguishing features in different insect echoes. This approach will allow an in-depth investigation of the underlying acoustic mechanisms of the interaction between prey and predators and will inform and inspire biomimetic applications for detecting and identifying objects by sonar. Further, the project will lead to synergism between the research fields of biology and engineering in the study of animal interactions and bio-inspired robotics.

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On-line optimization of ISOL@MYRRHA performance through an intelligent and automated control system. 01/01/2022 - 31/12/2025

Abstract

ISOL@MYRRHA is the Isotope Separation On Line facility to be constructed in the first phase of the MYRRHA project. It will be capable to produce a large variety of radioactive isotopes for applications in the field of nuclear physics, condensed-matter physics, biology, nuclear medicine and others. The quality (purity) and quantity (intensity) of the supplied RIB depends heavily on the proper tuning of the underlying process steps and their mutual interaction. From feedback of running ISOL facilities (ISOLDE/TRIUMF) it is known that the operation of an ISOL system needs constant intervention of an experienced operator/user. His job is to adjust the operational parameters of the system at a regular basis to compensate for effects likes ageing of the target and ion source, foiling of the extraction electrode, aligment issues due to temperature effects, etc ... . ISOL@MYRRHA aims at providing long uninterrupted beam times whichout compromising the quality and quantity of the beams to the users. An online optimization (retuning target, ion source and RIB transport parameters, ...) would unsure the continous delivery of the RIB to the users at optimal parameters and without interuptions. In this project, a control strategy will be developed to provide initial optimal selection of the control parameters as well as provide online tuning to keep the system continuously in the optimal operational regime.

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Flexible multi-domain design for mechatronic systems (Flexmosys_SBO). 01/01/2022 - 31/12/2025

Abstract

The Flexmosys project focusses on the co-design between multiple domains (such as structural component design, control design, software design, embedded design, …) for the development of mechatronic products. In order to develop improved mechatronic products (machines, vehicles, ...) in a shorter development time (by fewer iterations), this project aims at a cross-domain system model as the enabler for a more efficient collaboration environment between the different development teams. The project will therefore develop designer-centric methods and tools supporting the multi-domain development for these mechatronic systems. Starting from model-based design techniques available in the project team (such as ontological reasoning, co-simulation, parameter identification, sensitivity analysis and design space exploration), we will build methods and tools that will detect sensitivities of design choices from one domain to another, assure a consistent design across the involved development teams, and that allow for computationally efficient product optimization across the different engineering domains. The developed methods and tools will be validated on two industry-relevant demonstrators: an automotive electrical drivetrain and a high-performance drone. Eight companies have committed to participate in the Flexmosys user group. From the project results, they will ultimately benefit from fewer integration faults, a better overall design, visual information about the system's sensitivity on design choices, and more trustworthy system models and component models.

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Goldilocks' Fusion: Adaptive and Robust Sensor Fusion in Resource-Constrained Robotic Systems. 01/11/2021 - 31/10/2025

Abstract

In recent years, autonomous robotic systems have gained lots of attention from the academic world and industry. The many applications in industrial fields going from manufacturing, mining and surveillance makes the study on autonomous systems interesting with lots of valorization potential. The cost of these autonomous systems is currently extremely high as expensive computational platforms and sensors suites are used to provide necessary levels of safety and autonomy. Using the measurements from different sensors, an environment representation is created to make navigational decisions. While the environment representation determines the complexity of the behavior that can be achieved, the detail stored in this representation is dependent on the available computational resources and sensor data. The goal of this research project is to enable an autonomous agent to select the optimal heterogenous set of sensors to create an environment representation of the appropriate complexity for the current situation. Resource awareness plays an important role in our research as we aim to reduce computational workloads on the autonomous vehicles, which means less expensive computational platforms can be used. Additionally, increased reliably and accuracy in environment perception will benefit the autonomy of these systems. Less expensive autonomous systems while being efficient in the use of resources will benefit and increase the adoption of autonomous vehicles.

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Portable Innovation Open Network for Efficiency and Emissions Reduction Solutions (PIONEERS). 01/10/2021 - 30/09/2026

Abstract

PIONEERS brings together four ports with different characteristics, but shared commitments towards meeting the Green Deal goals and Blue Growth socio-economic aims, in order to address the challenge for European ports of reducing GHG emissions while remaining competitive. In order to achieve these ambitions, the Ports of Antwerp, Barcelona, Venlo and Constanta will implement green port innovation demonstrations across four main pillars: clean energy production and supply, sustainable port design, modal shift and flows optimization, and digital transformation. Actions include: renewable energy generation and deployment of electric, hydrogen and methanol vehicles; building and heating networks retrofit for energy efficiency and implementation of circular economy approaches in infrastructure works; together with deployment of digital platforms (utilising AI and 5G technologies) to promote modal shift of passengers and freight, ensure optimised vehicle, vessel and container movements and allocations, and facilitate vehicle automation. These demonstrations form integrated packages aligned with other linked activities of the ports and their neighbouring city communities. Forming an Open Innovation Network for exchange, the ports, technology and support partners will progress through project phases of innovation demonstration, scale-up and cotransferability. Rigorous innovation and transfer processes will address technology evaluation and business case development for exploitation, as well as creating the institutional, regulatory and financial frameworks for green ports to flourish from technical innovation pilots to widespread solutions. These processes will inform and be undertaken in parallel with masterplan development and refinement, providing a Master Plan and roadmap for energy transition at the PIONEERS ports, and handbook to guide green port planning and implementation for different typologies of ports across Europe.

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Embedded and distributed systems. 01/12/2020 - 30/11/2025

Abstract

Distributed embedded systems play a very important role in everyday life, now and even more so in the near future. Many of these embedded systems have one or more sensors for measuring physical quantities like the room's temperature or the position of a person in the building. Due to the increasing functional complexity of the desired applications in combination with the intricate interplay between the components of the system, it can become difficult to optimize the overall performance manually. Furthermore, the current desire for quick time-to-market demands quick design processes focused on adaptability of the design. One way to achieve this quick time-to-market is the (partial) automation of the design process. Distributed embedded systems play a very important role in everyday life, now and even more so in the near future. Many of these embedded systems have one or more sensors for measuring physical quantities like the room's temperature or the position of a person in the building. Due to the increasing functional complexity of the desired applications in combination with the intricate interplay between the components of the system, it can become difficult to optimize the overall performance manually. Furthermore, the current desire for quick time-to-market demands quick design processes focused on adaptability of the design. One way to achieve this quick time-to-market is the (partial) automation of the design process. As the system has to operate in real environments using real sensors, the environment where the system operates in has to be included in the model as well. Simulating physical quantities and realistic environments can become very complex very quickly. The time that has to be invested for achieving accurate simulation results can become too much. Experimental setups can provide the data which is needed to avoid the need for complex simulations. Therefore, a Hardware-in-the-loop and Sensor-in-the-loop approach will be adopted to provide the relevant data at the right time of the modeling process. Strategies for the right spatio-temporal sampling and the right moment to apply HIL/SIL methods are important questions to answer. Once the complete system has been modeled using the realistic models and the platform-specific constraints, hardware generation (VHDL, analog schematics, etc.) and code generation (C-code for embedded processors) from the high-level model can be used to accelerate the design cycle. Large functional changes often translate to small changes in the high-level model, and results often in large changes in the low-level representation. Using the right type of code- and hardware-generation can accelerate the design cycle significantly. Code generation can also be used in the form of prototyping platforms such as large FPGA's to accelerate certain sub-models of the MBD-design. HIL/SIL systems also allow for real-time performance to give rise to sensor flow, which is very important in a wide range of applications.

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Digital Twins for Continuous Deployment in Model-Based Systems Engineering of Cyber-Physical Systems. 01/11/2020 - 31/10/2024

Abstract

Cyber-Physical Systems (CPS) are required to operate over a longer lifetime. As such, the initial requirements can be changed, requiring the system to be updated continuously. These updates to the system must be rolled out continuously (Continuous Deployment) throughout the system's lifetime. The DevOps methodology provides a structured, quality assuring way to do so, as it integrates Development and Operations of a system in a continuous cycle. DevOps is generally applied in software development, however in the design of CPS, which follows a Model-Based Systems Engineering (MBSE) approach, it is not. This is because many challenges remain in the application of DevOps in MBSE. My focus is to create the foundations for continuous deployment of safety-critical CPS using digital twins of the CPS.

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Sparse interpolation potential in multidimensional optimisations. 01/10/2020 - 30/09/2024

Abstract

In engineering, simulations access the impact of design changes applied by engineers. Based on the simulation output, the engineer improves the design. Recently the engineer is replaced by an optimisation algorithm which adapts the design parameters to ensure optimal performance. Literature mentions case where applying these optimisation techniques leads to performance improvements up to 33%. However, current state-of-the-art very often relies on heuristic optimisation techniques. While they are easily applicable and suited for many applications, they cannot at all guarantee to find the global optimum. In contrast to local optima, the global optimum is the unique design which guarantees the best performance. Using optimisers which cannot guarantee the global optimum very often result in an untapped potential of up to 18%. Nevertheless, heuristic optimisers are still preferred in engineering as they do not require an exact mathematical model of the objective function. We propose to identify the mathematical model based on simulations standard in engineering practice. These simulations can deliver samples of the objective function based on specific settings for the design parameters. However, if the number of design parameters increases, providing an accurate grid of objective function samples becomes inconceivable as the number of necessary simulations explodes. Recent advances, obtained by the co-promotor, in multidimensional sparse interpolation will be a game-changer as it would reduce the number of necessary samples to an absolute minimum. By doing so, the underlying mathematical model we identify the objective function. This enables exact global optimisation. The research in this proposal will result in a generic workflow starting from commonly used simulations leading to a model via multidimensional sparse interpolation. The fact that such a model will enable global optimisation of engineering problems with multiple design parameters will be a genuinely fundamental novelty for the mechatronic state of the art.

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Intelligent Software Agents and Multi-agent Systems for the Lifecycle of Smart Cyber-physical System-of-Systems. 01/10/2020 - 30/09/2024

Abstract

AnSyMo (Antwerp Systems and Software Modeling) is a Computer Science research group investigating foundations, techniques, methods and tools for the design, analysis and maintenance of software-intensive systems. MICSS (Modeling Intelligente Complex Software and Systems) is a lab in AnSyMo group dedicated to the modeling of intelligent systems such as smart cyber-physical system of systems using intelligent agents and model driven engineering techniques. Cyber-Physical Systems (CPS) consist of tightly integrated and coordinated computational and physical elements. They are the evolution of embedded systems to a higher level of complexity, focusing on the interaction with highly uncertain physical environments (such as human interaction or wear & tear of devices). In these systems, embedded computers and networks monitor (through sensors) and control (through actuators) the physical processes, usually with feedback loops where physical processes and computations affect each other. The computational part of these systems plays a key role and needs to be developed in a way that can handle uncertain situations with the limited resources (including computational resource, memory resource, communication resource, and so on), mostly in real-time. With IoT and Industry 4.0 maturing, these systems are getting interconnected and making a complex larger system called the Cyber-physical System of Systems (CPSoS) to serve in more sophisticated tasks. In these systems, CPSs are working as part of a large system that is spatially distributed, has no central control, has autonomous subsystems, is dynamically configured, has emergent behaviour, and is continually evolving, even at runtime. A key point in CPSoS is to obtain knowledge out of the information that is collected by distributed monitoring of the environment, using artificial intelligence techniques. This knowledge can improve the control and feedback mechanism. Further, these capabilities lead to the smart systems of the future with timely and more accurate decisions and actions, called Smart CPSoS (sCPSoS), which can help to address a number of social, industrial, and environmental issues. This project aims to address the challenges of sCPSoS using intelligent agents and model-driven engineering techniques.

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  • Research Project

Deterministic and inexpensive realizations of advanced control (DIRAC-SBO). 01/09/2020 - 28/02/2025

Abstract

The mechatronic machine building and manufacturing industry is currently facing various control challenges that simple PID controllers and alike fail to address: systems are increasingly complex, need to comply to constraints, need to account for economic objectives and effectively cope with valuable preview information. Model Predictive Control (MPC) is the only advanced control approach able to address all these challenges, and this thanks to its model-based and optimization-based nature. Yet MPC's optimization-based nature currently impedes wide adoption in industrial mechatronic systems: current MPC implementations are expensive in terms of computational and memory resources, computation time is non-deterministic and hence MPC algorithms cannot be certified to operate at a given sampling rate, MPC development and deployment is not straightforward and comes with a high engineering cost because proper tools are missing. The project "Deterministic and Inexpensive Realizations of Advanced Control" (DIRAC) aims for a breakthrough of MPC in the mechatronic/machine building/manufacturing industry by resolving all impeding elements through accomplishments that revolve around the three keywords in its title:  - Deterministic: Novel MPC algorithms and approaches will be developed that can run reliably at a given sampling rate as well as methods to verify their worst-case computation times and control performance.  - Inexpensive: Implementations will be created that approximate "full-blown" (=online nonlinear optimization with high fidelity models) MPC and hence can run on inexpensive computational hardware with a quantifiable impact on control performance that is computed upfront.  A modular MPC toolbox will be developed facilitating the development, tuning and validation of advanced control at manageable engineering cost. - Realizations: We will demonstrate the MPC toolbox and potential of MPC on industrially relevant demonstrators and validation cases in order to break the status-quo in control practices, foster take-up and inspire Flemish industry.  The overarching tangible reusable generic result of this project is a toolbox that simplifies design of nonlinear MPC controllers and brings methodological advances in solvers, approximations and validation techniques to the fingertips of control practitioners.

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Modelling and Simulation of Cyber-Physical Systems 01/08/2020 - 31/07/2025

Abstract

Cyber-Physical Systems (CPS) consist of tightly integrated and coordinated computational and physical elements. They focus on interaction with highly uncertain environment with the limited resources. By introducing IoT and Industry 4.0, the CPSs are connected to each other to meet the emerging more complex requirements. These interconnected CPSs constitute complex systems called Cyber-physical System of Systems (CPSoS) in which there may be emergent behaviour, lack of central control, dynamic structure, and need for autonomy. Therefore, CPSoS cannot be designed and managed using theories and tools from only one single domain. A key point in a CPSoS is to obtain knowledge out of the information, collected by monitoring the environment. This knowledge can improve the control and feedback mechanism. This capability leads to the next generation of CPSoS with timely and more accurate decisions and actions called Smart CPSoS (sCPSoS). These smart systems can analyze a situation and make decisions based on the available data in an adaptive manner, to perform smart actions. However, such intelligent techniques put yet additional complexity to the systems, specifically to the computational part. Thus, these systems of the future have a high complexity (both from structural and behavioural points of view) throughout their lifecycle, including modeling & simulation, design & implementation, validation & verification, deployment, execution & monitoring, and maintenance & evolution. There is a need for new methodologies, architectures, process models, and frameworks to tackle this complexity. To overcome the challenges in the development and operation of sCPSoS, modeling techniques can be used for different aspect and various levels of abstraction in the system. To this end, appropriate modeling paradigms should be chosen for each aspect/level. These models and modeling paradigms will be integrated, hence called multi-paradigm modeling (MPM), to represent the whole system. Specifically, the idea is to integrate agent paradigm with the model-based system engineering (MBSE) for both modelling & simulation phase as well as execution and monitoring phase in the lifecycle of sCPSoS. Agent based system engineering (ABSE) uses software intelligent agents to successfully cross-fertilize the fields of systems engineering and artificial intelligence. In this way, the autonomy, dynamic behaviour and smart-ness of sCPSoS can be handled by intelligent agents, integrated with MBSE models.

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Foundations for Self-Adaptive Abstraction and Approximation in Real-time Cyber-Physical Systems (of Systems). 01/05/2020 - 30/04/2024

Abstract

Cyber-physical systems (CPS) are engineered systems that have a tight integration between the cyber part (computation and networking) and its physical components. Examples include but are not limited to industry 4.0, automotive and aerospace. To allow decisions to be made in a CPS (strategic control, tactical control and, low-level control), decision models are used. These models use input from sensors, but also from other supporting processes, e.g. predictions over the state of its contexts, to come to a control decision. The decision processes are implemented in software that runs on embedded hardware and is commonly real-time constrained, meaning that the time at which the decision is taken, is as import as the decision itself. In literature several techniques are available to reduce the computational cost of executing models by using abstraction and approximation (e.g. surrogate modelling). This reduced cost would make the process to come to a decision easier (scheduling) and would require less computational resources. However, we still need to be sure that the decision process is robust against approximations and uncertainties in these models. Furthermore, an approximated and/or abstracted model is most probable not valid in all the different contexts the system will be in. To enable this, the system should be able to switch at run-time between different abstractions and approximations. Therefore, this project will create the foundations to reason about dynamically adapting the decision models and prediction models with different abstractions and approximations depending on the context of the system. The project will result in a framework with supporting modelling languages, methods and proof-of-concept tools to reason on the trade-off between uncertainty (from the approximation) and the real-time behavior of the system.

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A Hybrid SLAM approach for autonomous mobile systems (HySLAM_SBO) 01/07/2019 - 31/03/2024

Abstract

In HySLAM,we will investigate the introduction of semantics in SLAM. We will introduce new probabilistic models which are based on scene understanding to increase the conditioning of the SLAM problem. Taking into account the underlying dynamics of the objects, and their effect on the perceptual scene, can help to increase the robustness of the SLAM algorithms. We will demonstrate the efficacy of the algorithm in a 2D and 3D test case.

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Past projects

ABN HaFreeS Feasibility. 01/09/2022 - 31/12/2023

Abstract

In this project, we take the first steps in the development a novel hands-free communication set for use on bicycles. The main advantages of our solution in comparison to current solutions are call quality and convenience. Call quality is our main selling point: wind noise, traffic noise and contact noise impede comfortable calling at a speed above 10-15 km/h with the current available technology; we aim to overcome these shortcomings using technology building blocks available in Cosys-lab that have matured in other application domains. We mainly focus on showing technology feasibility, initiating a market study and perform initial user outreach activities. We will also start preparing the design of an MVP prototype. These activities are an essential first step to determine if it is worthwhile to pursue the end goal of commercializing the solution in a spin-off. If the technology is shown to work and the valorisation potential lives up to our expectations, we will undertake further steps in later projects to develop a deep market insight, a convincing MVP prototype and a solid value chain. These elements are necessary to reach the end goal of starting a VC-funding-free spin-off, bootstrapping with funding gathered in a crowdfunding campaign.

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Wireless Power Transfer for building-integrated photovoltaics 01/05/2022 - 30/04/2023

Abstract

This research project aims at developing a module to wirelessly transport energy from photovoltaic solar cells in buildings. A crucial problem with building integrated photovoltaics (e.g. as a facade, or embedded in a window) is that with current technology, electrical cables still have to be pulled from the outside to the inside of the building, which has negative consequences for the insulation and water tightness of the building. Through prototypes, we test the efficiency and reliability of wireless energy transfer applied to the context of a building.

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Optimisation of the flexibility in a driveline through virtual engineering (OptiFlex). 01/10/2021 - 30/09/2023

Abstract

The OptiFlex project, executed by Ghent University, University of Antwerp, and KU Leuven, has developed rapid deployment methodologies and tools to quantify and simulate flexibility in drivetrains. As a result, flexibilities can be compensated by optimizing motion profiles and controller settings. This has led to notable successes, such as a speed enhancement of 52% in the cyclical motion of a loom machine and determining the impact of flexibility on the cutting accuracy of a plasma cutting table. These findings emphasize the significance of gaining knowledge about your drivetrain system and employing optimized motion controllers and motion profiles.

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Mixed absolute and relative localization (MARLOC). 01/04/2021 - 31/03/2023

Abstract

In this project, we will combine fixed infrastructure localization (markers, UWB) with relative localization perception (SLAM, odometry) to arrive at a highly accurate and robust location estimate for mobile robots. We will work on simulation models and performance prediction based on deep learning techniques to optimize the localization setup.

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Hydrophone Array Sensing as a Means for Subaqueous Monitoring. 01/04/2021 - 31/03/2022

Abstract

Over the last years CoSys Lab developed state of the art sonar sensors, sensor arrays, acoustic monitoring techniques and bioinspired sensing approaches, published them in high impact journals and successfully initiated industry collaborations. So far all the sensor systems were designed for airborne (ultra)sound, however, these systems can also be adapted to underwater acoustics and therefore broaden the field for applications both within research as in industrial collaborations. Therefore, we want to develop an underwater acoustics/sonar measuring device and need additional equipment (e.g. hydrophones, underwater speakers and data acquisition cards) that can provide us with ground truth benchmarking data in order to quantify the efficacy of our initial prototypes. We want to focus mainly on hydrophone arrays for bioacoustics research as we see here most potential for now, but in future our knowledge acquired in this project will help us to design 3D underwater sonar sensors.

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ModAU - Modernized Auscultations for Remote Monitoring. 01/01/2021 - 31/12/2022

Abstract

In hospitals where there is a significant workload, performing auscultations can be a timeconsuming process, which also exposes the medical personnel to potentially contagious diseases. Current systems that allow remote auscultations are often not fit for use with large amounts of patients, long-term use, or are limited in terms of functionality. The major drawback in current remote auscultation systems is the relatively bulky acoustic coupler which makes part of the stethoscope assembly. This physical dimension reduces the applicability for long-term monitoring, because of the discomfort for the patient and the inherent risk of decubitus wounds. In this project, we will investigate the construction of thinner stethoscopes, increasing patient comfort

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Echo-acoustic signalling of aposematic and cryptic insects – A bat inspired modelling approach (EchoBug). 01/05/2020 - 30/04/2021

Abstract

In this project we investigate acoustic aposematic signalling in insects. We combine acoustic measurements with computational bat behaviour modelling to gain insights into the effects of aposematic signalling on the bat's perception mechanisms.

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AutoRIO. 01/04/2020 - 30/06/2022

Abstract

In this project we develop robust navigation strategies for AGVs which need to operate in both indoor and outdoor conditions. We evaluate various sensor subsystems which can support the navigation applications

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SmartFlush. 01/02/2020 - 31/07/2021

Abstract

In this project we develop smart flushing solutions together with our industrial partner, IPEE nv. We use advanced techniques to improve the processing of their proprietary sensor data. We also operationalize a deployement setup.

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EPSim - Embedded Platform Simulator. 01/02/2020 - 31/01/2021

Abstract

When designing a complex cyber-physical system, components of the system are often designed by different engineers, each with their own expertise in a particular domain, e.g. software, control, and mechanical engineering. In later design stages, the integration of the designed components into one system needs to be performed. This integration phase however often leads to unexpected problems such that the system does not function as it was intended. The goal of this project is to develop EPSim, an engineering tool which tackles an important integration problem between embedded engineering and control engineering. EPSim will focus on the particular problem that embedded platforms introduce time delays on the signal path that is used by the control engineers. Hereto, EPSim will allow for the virtual integration of embedded components into control loops already in early stages of the design process. This will ultimately lead to optimised design processes by reducing, or even avoiding, costly design iterations. The foundations of this idea have already been developed in our lab; the related method and tool is now situated at TRL 3. The current status is attracting attention from some mechatronic companies in the framework of an ICON-project, which is an appealing starting point for further valorisation. By means of this project, we intend to further develop the method and tool towards TRL 5.

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3D sonar sensing for inland shipping applications.. 01/02/2020 - 31/01/2021

Abstract

In this project, we will evaluate the applicability of the eRTIS 3D sonar sensor in autonomous indoor shipping applications. We will collaborate with a supplier of indoor autonomous shipping solutions to provide an experimental platform which can be used to evaluate the sensing capabilities of the sensor setup. Furthermore, we will work on water-proofing of our technology, which is an important asset for the overall sensor performance.

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Integration, deployment and operationalization of an experimental fluttering insect measurement sonar. 01/01/2020 - 31/12/2021

Abstract

In this project we operationalize an ensonification setup for fluttering insects. Through the implementation of a 32 channel phased microphone array in combination with a high-speed video camera we develop a multimodal setup which can record and localize echoes originating from fluttering insects. These echoes can be overlayed with high-speed video data.

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Modelling and testing for total life cycle management in mechatronics. 01/12/2019 - 30/06/2022

Abstract

The complexity and intelligence of cyber-physical systems (CPS) are continually increasing. Developers and manufacturers of large systems such as industrial printing machines, many-sided agriculture machines, high-speed weaving looms, autonomous driving cars, up to highly safe commercial airplanes are confronted with common technical challenges that span the total product's life cycle from requirements capturing over design and validation up to product family management. In the current project, we will contribute to two main aspects of the mechatronics product life cycle: managing the complexity of evolvable CPS, and system level validation. We will therefore use state of the art model-based design techniques and mutation testing techniques. The objectives of the current project can be summarised as follows: - Becoming a partner in at least one European proposal related to the above topics. To this purpose, we will focus on dedicated networking activities with industry and academia in the European networks in close collaboration with the Nexor IOF valorisation manager. We will target projects in the Digital and Industry Cluster in Pillar 2 (Global Challenges and Industrial Competitiveness), mainly in the areas Key Digital Technologies, Artificial Intelligence and Robotics, Manufacturing Technologies, and Space, as well as in the Pathfinder grants of the European Innovation Council in Pillar 3 (Open Innovation). - Refining the AnSyMo and CoSys-Lab roadmap against the use cases defined by the problem owners within the European consortia we negotiate with. To this purpose, discussions with possible partners (see item above) must lead to better insights in the industrial needs for the upcoming CPS and to better insights in the objectives of the European project types. - At least one demonstrator showing the capabilities of the Ansymo and CoSys-Lab research groups on the related topics, i.e. on consistency management, orchestration, mutation testing, fault injection.

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Towards optimal design, trajectories and control for repetitive movements. 01/11/2019 - 31/10/2023

Abstract

There is a strong desire to maximize the efficiency or speed of industrial machinery. Designers of machines, performing repetitive motions, often only define the position start- and endpoint of a movement and not the exact position function. This flexibility opens the opportunity to optimize the trajectory of the mechanism. Moreover, for the machine design itself, machine builders often rely on standard components and dimensions. The effect of the geometric design on the optimal trajectory and energy need of the system is very often neglected. The literature mentions cases where ad-hoc optimizations reduce energy usage up to 39% thanks to trajectory and geometric optimization. This project will use available CAD models and sparse interpolation to extract a closed mathematical system property description. This will enable using an interval optimization technique which can guarantee to find the one true global optimal geometric design and trajectory. The knowledge of the system properties will be used to design a robust controller to ensure the machine follows the desired trajectory. Finally, any mismatch between the virtual and real model will be detected with online tracking techniques to assure the machine operation remains optimal. The potential impact for machine builders is high as this project enables them to construct machines with a reduced total cost of ownership or allow them to perform a task as fast as possible purely based on their readily available CAD models.

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Scientific chair 'Industrial Acoustic Condition Monitoring'. 01/10/2019 - 30/09/2022

Abstract

In this research chair we will investigate the efficacy of array signal processing for industrial condition monitoring. Through the combination of novel embedded systems technologies as well as advanced signal processing paradigms we will create an experimental setup with which advanced condition monitoring and predictive maintenance scenarios can be investigatedN

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Optimal machine design by means of virtual engineering (OPTIMOTION) 01/10/2019 - 30/09/2021

Abstract

The overarching objective of this project is to develop tools and train the members of the target group in their usage. These tools should allow the straightforward optimisation of the mechanical design of machines and their drive system. Optimizing the placement of essential machine parts and optimising the selection of drive components can minimize the drive torque required for a machine. This optimisation potential can be fully exploited if the motion controller that drives the whole is properly tuned. All Flemish companies involved in mechanical engineering operate in a competitive market and are under pressure to optimise their machine design. More specifically, this project is aimed at machine builders, engineering consultants and suppliers of drive components and CAD software.

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HR-RTIS: High-Resolution Real Time Imaging Sonar Sensor. 01/07/2019 - 31/12/2020

Abstract

For autonomous vehicles, sonar sensors can pose a real alternative to optical sensing techniques such as laser scanners and 3D cameras in situations where these optical techniques fail. The failure of these optical systems can be caused by medium distortions such as dust or fog, or sensor contaminations such as mud splashes. In the CoSys research group we develop advanced 3D sonar sensors for industrial applications, which are currently being validated in various industrial application niches. During this proposed STIMPRO project we propose to expose the uncover the dynamic range in the strengths of echoes created in relevant industrial environments and their spatial distribution in that environment. To this extend, we propose a high-resolution microphone array consisting of 1000 microphones, which will allow the creation of high-resolution and high dynamic range 3D sonar images. The sensor will provide us with essential insights into the reflective properties of relevant environments and will allow us to improve the low-cost sensors which we are famous for worldwide.

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Development of a priori and online trajectory optimisation for repetitive motions. 01/10/2018 - 30/09/2022

Abstract

As global energy demand will continue to rise and man's negative impact on global warming is known to be a fact, there is a strong desire to minimise the energy usage of industrial machinery. A significant opportunity lies in optimisations which do not require any adaptations or investments in installed hardware such as trajectory optimisation. Machine builders and users often only define the time to move from one point to another and the position of start- and endpoint. The exact position as a function of the time, or position function, in between these two points is very often not an issue for machine users. This flexibility opens the opportunity to optimise the position function. The literature mentions cases where ad-hoc optimisations reduce the energy usage of machinery used for repetitive tasks up to 50% by choosing optimised trajectories over the usual standard movement profiles. However, there is no scientific consensus on a computationally efficient technique which can guarantee to find the global optimum for systems with position varying mechanical load properties. Therefore, this project will assess the use and implementation of direct calculus optimisation. Applying this pure mathematical technique based on symbolic methods of trajectory optimisation would be a genuinely fundamental novelty, especially for machines with position varying dynamics. For one thing, this would eliminate the necessity of time-consuming iterative optimisations. On the contrary, direct calculus methods would lead to closed mathematical functions for the position function. To enable the use of this direct calculus methods, closed mathematical equations, describing the position-varying mechanical load properties, will be necessary. Obtaining such functions can be done theoretically based on Lagrange formulations. However, such an approach is not feasible in practice where the complexity of the machinery hampers analytical analysis. On the other hand, machine builders increasingly rely on CAD multibody software to design their machines. The promotor has expertise in extracting data by applying specific simulations on these virtual CAD models. The sampled data, obtained in this way, can be translated to explicit formulas, based on the expertise of the co-promotor. Developing such a technique to transform the sampled data to closed mathematical equations will be a core challenge of the project and the major enabler to apply direct calculus optimisation. Furthermore, to guarantee the machine still operates at its optimum if machine behaviour changes during operation, an online tracking method is necessary. For this purpose, the knowledge of the promotor on tracking the position dependency of machine parameters online in the frequency domain is essential. The data samples obtained in this way will again be translated to a mathematical description to allow a re-optimisation of the trajectory. For this purpose, the direct calculus optimisation method will be advantageous as it defines the optimised path as a function of position varying parameters. This definition enables direct re-optimisation. Moreover, where the current state of the art focusses on offline a priori or online optimisation, facilitating online re-optimisation based on a priori offline determined information will be another fundamental novelty of this project.

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  • Research Project

Product-Assemby Co-Design (PACo). 01/09/2018 - 31/08/2023

Abstract

The Product-Assembly Co-Design (PACo) project is a project within the scope of the cluster Design & Optimisation of Flanders Make. The project aims at bridging the gap between product design and assembly system design by incorporating assembly knowledge into the early stages of the product development. Today, most companies consider assembly aspects later in the design process, often in a manual way, solely relying on the experience of assembly engineers. This leads to numerous design changes later on, causing significant extra costs. The current industrial context requires companies to aim at a first-time-right, down to lot size 1 at the cost of volume production strategy. Hence, considering assembly aspects too late or in a trial-and-error way is no longer an option. All companies involved in the user group of this project indicate a clear need to support their engineers with methods and software tools enabling assessment of assembly complexity in an early design stage, allowing co-optimization of product performance with ease-of-assembly in a quantitative way, and allowing trade-off analysis of various solutions. As these software tools are beyond the state-of-the-art, the research partners (FM-CodesignS, FM-ProductionS, AnSyMo/CoSys-lab, DMMS, and EEDT) will join forces to shift the state-of-the-art in product-assembly co-design, aiming at the following innovation goals: (1) a software environment for the formalization of assembly knowledge (e.g. Design-for-Assembly rules, assembly complexity metrics), (2) tools and algorithms for automated multi-objective optimization of the early-stage design of a product, taking into account the product performance and its assembly complexity, (3) tools and algorithms to automatically find the optimal assembly process (order of steps) and assembly system (resources allocation), for a given product design and a framework for the co-design of both product and its assembly system by combining both 1) and 2) in a semi-automated workflow.

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High-efficiency Sensorless Control of a BLDC Motor using Sinusoidal Currents. 01/07/2018 - 31/12/2019

Abstract

A Brushless DC Machine (BLDC) is the optimal motor to use in applications where a more or less constant, controlled, high rotational speed is required. Typical examples include driving: the compressor of a cooling system including refrigerators and air-conditioning, the propellers of a drone, fans and pumps in general, …. The BLDC is responsible for the lion share energy usage of these applications. Moreover, cooling systems consume a lot of energy worldwide because of their ubiquitous presence. On the other hand, for battery fed systems such as drones there is strong desire for increased autonomy. This means there is a strong desire to reduce the energy usage of BLDC driven systems. BLDC motors are typically driven with a square wave current. On the other hand, using sine wave currents could result in an energy efficiency increase of 10%. However, typical BLDC algorithms lack feedback to drive the machine with sine waves. Using an encoder to obtain this position feedback would increase the cost and complexity of the drive system and can be impossible due to limited mounting space. Therefore, so-called sensorless algorithms which estimate feedback signals based on easily measurable voltage and current signals, are of interest. Consequently, the central research question of this STIMPRO is formulated as: Develop and implement a sensorless algorithm to provide feedback for a BLDC drive algorithm using sinusoidal current waveforms and validate its energy saving potential. As a starting point this STIMPRO will consider an estimation algorithm, developed by the promotor, for stepping motors, to use in BLDC drives. This STIMPRO will be used as a kick-start to initiate electrical motor control research at UAntwerp. This project will serve as leverage to move the activities off the promotor in motor control, who started at ZAP at UAntwerp the 1st of September 2018, previously established at UGent to UAntwerp. To do so, the STIMPRO will be used to hire a researcher who will submit an FWO SB proposal. However, if FWO funding is rejected we will not finish this project empty handed. Given the work plan defined in the STIMPRO, and the experience of the promotor the project will certainly result in publications, a test bench, added experience for the hired researcher and the exploration of possible bilateral collaboration with Flemish companies on the subject. The work done in this STIMPRO will be beneficial for the Op3Mech research group as adding research on electrical motors is a vital in the broader robotics research. Moreover, the education on drivelines at the Faculty of Applied Engineering is currently not supported by academic research. Therefore, the research activities initiated in this STIMPRO are vital to continue education on these topics.

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AirLeakSLAM: On-line detection of pressured-air leaks in industrial environments using passive and active ultrasonic sensing. 01/05/2018 - 30/06/2019

Abstract

A large amount of energy is lost annually due to leaks in compressed air networks. The combination of SLAM and 3D-ultrasonic measurement techniques enables to automate the measurement and registration of these leaks without requiring manpower. Therefore, measurements can be conducted in a continuous (on line) instead of an incidentally manner. The goal of the project is to demonstrate the power and the opportunities of the system for the user of the compressed air system, and to further quantify the value creation opportunity.

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Automated and simulation based functional safety engineering methodology (aSET_ICON). 01/03/2018 - 31/08/2020

Abstract

Due to the trend towards more complex safety-related products combining mechanics, electric components, electronics and software, their design and development become more complex, leading to longer development times and higher costs as well as higher risks on errors with highly manual safety engineering processes. The goal of the aSET-project to develop methodologies to automate the functional safety engineering process to make the process less error prone and to reduce the required design time and cost compared to the current manual state-of-the-practice. More specifically, the objectives of the project are: (i) the development of a Functional Safety Formal model implemented in a persistent way enabling the intrinsic coupling between all Functional Safety artefacts requested by ISO26262; (ii) the development of a method and demonstrator tooling for the translation of textual requirements into mathematical equations (that can serve as a design contract for the actual hardware design) that describe functionality of E/E/PE enabling the automation of HARA with the help of a functional E/E/PE model and plant model; (iii) the validation of these methods in a generic use case as well as in different industrial use cases demonstrating their functionality and the targeted design time and cost gains.

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Avoidance of collisions and obstacles in narrow lanes (AVCON_ICON). 01/02/2018 - 31/01/2020

Abstract

In this project, we will investigate various methods for implementing obstacle avoidance in narrow corridors. We design a suite of sensors which provide the control algorithms with the required information.

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Dotation for the structural collaboration with Flanders Make. 01/01/2018 - 31/12/2020

Abstract

Flanders Make's mission is to strengthen the international competitiveness of the Flemish manufacturing industry on the long term through industry-driven, precompetitive, excellent research in the field of mechatronics, product development methods and advanced production technologies and by maximizing valorisation in these areas.

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Concurrent design of control, embedded hardware and software for mechatronic and cyber-physical systems (CSE_codesign_ICON). 01/01/2018 - 31/12/2020

Abstract

General objective: The main goal of this project is to develop a design approach and the necessary computational tools that enable the concurrent design of application software, embedded software and hardware platforms, ensuring the targeted closed-loop performance of cyber physical systems. This with the aim to increase the efficiency of the design process and yet reducethe costs of the associated embedded software and hardware platforms. Concrete goals: More specifically, the innovation goals of this project are to: 1. Develop a methodology and software tools to support the concurrent design of application software and embedded platform for individual cyber-physical product variants:  - enabling both control engineers and embedded platform engineers to perform a trade-off analysis between various design choices on application and platform level in an agile manner, i.e. without long iteration loops, thereby reducing the typical development time of an embedded control application with at least 25%. - improving the cost-effectiveness of embedded platforms by at least 10%, by considering stochastic delays instead of using 'worst case' response times and bus delays, without sacrificing the stability, performance and robustness of the closed-loop behaviour. 2. Investigate the feasibility of extending the above approach with design space exploration techniques that automatically select the most optimal design alternative in terms of application/platform design choices in the large space of possible solution alternatives.  3. Develop an approach and software tools to support trade-off analysis and design space exploration for the embedded platform selection and design in the case of complete mechatronic/cyber-physical controller product lines. Building further on these methods and tools, the company partners in this project aim to realize the following targets: Atlas Copco's main goal is to create an approach, a software framework and the accompanying development tools that support their designers responsible for implementing the compressor room control to select the most appropriate software and hardware platform deployment and configuration, guaranteeing the required compressor room performance under all circumstances. Picanol wants to increase the performance and quality of its weaving machines by improving the co-design between the control software and embedded platform engineers. More specifically, Picanol wants to deploy this co-design approach to the yarn insertion subsystem of all machine variants, thereby increasing the production capacity of these variants with 2% or reducing the air consumption with the same amount. Tenneco's main goal is to select a set of embedded and power electronics hardware platforms that cost-optimally cover their complete product line of electro-magnetic shock absorbers from low-end to high-end vehicles. The approach and tools that allows to select this set of platforms should also be applicable to other Tenneco product lines. Michel Van de Wiele (MVDW) wants to select a new, durable and modular embedded hardware and software platformthat is capable of controlling today's and tomorrow's weaving machinery. Specifically, for the same loom requirements a reduction of the hardware cost by at least 10 % is targeted or with the same hardware cost, the target is to realize an increase in machine speed of 10 to 50 % or being able to deal with at least 10 % more sensors / actuators. Next to this, MVDW also aims to update their design approach and tools such that designers can easily predict a priori if the embedded controller for a particular variant

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  • Research Project

INES - Innovation in the development of Electronic Systems for Aeronautics . 01/09/2017 - 31/08/2019

Abstract

The INES project, a project consortium with its Flemish component Siemens Industry Software (with its subcontractor Siemens CT) and University of Antwerp, and its Spanish component Boeing Research & Technology Europe (with its subcontractors GMV and Skylife), coordinated through the Eureka program, aims to develop a realistic, innovative and implementable MBSE process as well as identify a series of software tool innovations that cover the complete development and life cycle of avionics systems (understood as the electronic systems of the aircraft including its avionics controller algorithm, software and hardware), which would, within two years, offer an paradigm shift for the development of aircraft electronic systems (avionics), whose objective would be to achieve much higher levels of quality at a reduced development cost with respect to current technology.

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  • Research Project

European initiative to enable validation for highly automated safe and secure systems (Enable S3). 01/06/2017 - 31/05/2020

Abstract

In this project, CoSys-Lab provides support for embedded realisations with AUTOSAR and Hardware-in-the-Loop testing. By means of practical case studies, best practices on the engineering methods and related tooling is collected. The application field is mechatronics and automotive engineering.

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RAAK-MBK program "COMBINE". 01/04/2017 - 01/10/2018

Abstract

In this project, we contribute to the technology transfer of Hardware-in-the-Loop test technology for embedded systems in automotive. The focus is on process modelling of the test strategies and demonstrating them in industry-relevant applications.

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  • Research Project

Biologically-inspired 3D radar sensor supporting intelligent robotic behavior in complex and cluttered environments. 01/01/2017 - 25/01/2021

Abstract

The goal of this research is to produce a compact, light-weight sensor which will enable an unmanned aerial vehicle to autonomously traverse trajectories through cluttered environments, such as a forest, while sensing and avoiding objects. The sensor is inspired by biological echolocation as performed by bats, which involves emitting an ultrasonic signal and closely listening to its reflections. By analyzing how each received echo differs from the emitted signal and how they mutually vary between its two ears, the bat can determine where the object which reflected the signal is located. Additionally, using sequences of these echoes makes is possible to determine the movement through the environment. We will mimic these features in our system to achieve the same results. For our application we use radio waves (radar) instead of sound (sonar), because these travel at a much greater speeds, while allowing the sensor to operate under circumstances where optical cameras would fail, such as at night, in rain, fog, smoke, etc. Furthermore, we propose a control scheme inspired by cognition, such as insect intelligence, to steer the robot. The idea is to implement a layered system of behavioral units, each with its own goal. Examples of these units include, stopping to avoid a collision, dodging an obstacle, and following a corridor. The system will then execute the behavior with the highest priority which is active at each given moment, creating an overall emergent intelligence.

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Advanced array signal processing for industrial in-air sonar applications. 01/01/2017 - 31/12/2020

Abstract

This basic research project seeks to advance our knowledge of in-air sonar sensing towards new industrial applications where traditional sensing techniques (optical, radar) suffer from physical limitations such as the environment (dust, mist) or limited object reflectivity (RF penetration). The knowledge gaps, identified by previous industrial collaborations, are to be answered by a mix of algebraic analysis, numerical computations and experimental prototype engineering. The focus will be on the application of advanced array signal processing techniques and real-time embedded systems. The outcome of this project will be a strengthened knowledge of in-air sonar sensing and additional background IP for future projects concerning economic exploitation of our technology.

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TCO optimal system design for energy and power storage in dynamic load applications (EnPower_ICON) 01/01/2017 - 31/12/2018

Abstract

The goal of this project is to develop and validate a system design methodology for drivetrains and energy systems combining multiple energy sources and storages. The methodology will deliver an optimal system design in respect to TCO, Performance and Functional Safety cost.

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  • Research Project

Localization system for accurate tracking and navigation for autonomous operation (LOCATOR_ICON) 01/11/2016 - 31/10/2018

Abstract

In order to choose the right combination and placement of sensors to perform sensor-fusion based indoor localization in industrial environments, a framework for designing systems for global and relative localization can facilitate the development. To quantify the performance of various sensors in this operational context, models of these sensors need to be developed. These models will be probabilistic in nature in order to be used with the aforementioned sensor fusion techniques and to calculate confidence intervals where safety is an issue. The sensor models will be parametrized and will be able to incorporate in-situ experimental measurements to make the simulations more accurate.

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  • Research Project

Scale-free passive acoustic localization using a wireless synchronized sensor network. 01/10/2016 - 30/09/2020

Abstract

During this project we will develop a framework which allows passive localization of acoustic sources using a synchronized wireless sensor network. Synchronization of the wireless microphone array will be performed using a distributed synchronization scheme absent of a master time representation. The framework will support automatic calibration of the microphone array with minimal human intervention. The location estimate of the acoustic sources will be performed using a probabilistic localization algorithm in combination with known statistics about the behavior of the acoustic source. The framework will be virtually scale-free, which means that the sensor network can be used for tracking a wide variety of acoustic sources in a wide variety of application domains.

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  • Research Project

Model based force measurements (MoForM). 01/02/2016 - 01/02/2020

Abstract

Knowledge on (internal and external) dynamic forces and torques is of crucial importance, both during the prototype development phases of mechatronic products, machines and processes, as well as during their operational lifetimes. Measuring forces is a time consuming, error-prone, expensive and often intrusive process. Furthermore, it occurs regularly that force measurements at the desired locations are prohibited due to space limitations or too harsh circumstances. The main goal of the project is to develop a breakthrough force/torque measurement technology by adopting a virtual sensing strategy. This involves the evaluation and development of single (Kalman filter based) and multistep (Moving Horizon Estimation based) estimators that combine high-fidelity physical models and physically inspired grey box models with affordable non-intrusive sensors to retrieve unknown forces in a fast (possibly real-time), accurate, in-situ and on-line manner. The targeted performance is defined in cooperation with industry and spans from real-time in-situ force estimation with a 10 Hz bandwidth and a 20 dB dynamic range to on-line in-situ force estimation with a 200 Hz bandwidth and an 80 dB dynamic range. The estimation technologies should be able to account for the non-linear dynamic effects as encountered in mechatronic drivetrains and systems.

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  • Research Project

Embedded and distributed systems. 01/12/2015 - 30/11/2020

Abstract

Distributed embedded systems play a very important role in everyday life, now and even more so in the near future. Many of these embedded systems have one or more sensors for measuring physical quantities like the room's temperature or the position of a person in the building. Due to the increasing functional complexity of the desired applications in combination with the intricate interplay between the components of the system, it can become difficult to optimize the overall performance manually. Furthermore, the current desire for quick time-to-market demands quick design processes focused on adaptability of the design. One way to achieve this quick time-to-market is the (partial) automation of the design process. Distributed embedded systems play a very important role in everyday life, now and even more so in the near future. Many of these embedded systems have one or more sensors for measuring physical quantities like the room's temperature or the position of a person in the building. Due to the increasing functional complexity of the desired applications in combination with the intricate interplay between the components of the system, it can become difficult to optimize the overall performance manually. Furthermore, the current desire for quick time-to-market demands quick design processes focused on adaptability of the design. One way to achieve this quick time-to-market is the (partial) automation of the design process. As the system has to operate in real environments using real sensors, the environment where the system operates in has to be included in the model as well. Simulating physical quantities and realistic environments can become very complex very quickly. The time that has to be invested for achieving accurate simulation results can become too much. Experimental setups can provide the data which is needed to avoid the need for complex simulations. Therefore, a Hardware-in-the-loop and Sensor-in-the-loop approach will be adopted to provide the relevant data at the right time of the modeling process. Strategies for the right spatio-temporal sampling and the right moment to apply HIL/SIL methods are important questions to answer. Once the complete system has been modeled using the realistic models and the platform-specific constraints, hardware generation (VHDL, analog schematics, etc.) and code generation (C-code for embedded processors) from the high-level model can be used to accelerate the design cycle. Large functional changes often translate to small changes in the high-level model, and results often in large changes in the low-level representation. Using the right type of code- and hardware-generation can accelerate the design cycle significantly. Code generation can also be used in the form of prototyping platforms such as large FPGA's to accelerate certain sub-models of the MBD-design. HIL/SIL systems also allow for real-time performance to give rise to sensor flow, which is very important in a wide range of applications.

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  • Research Project

Timing Analysis for Real-Time Embedded Multicore Software. 01/10/2015 - 30/09/2019

Abstract

Multicore processors are increasingly used in mechatronic applications and need to endorse the realtime requirements of the related embedded software. In spite of their huge processing power, certain operational conditions may arise in which they show longer software execution times than reasonably expected. In this project, we will elaborate software timing analysis techniques which will lead to better configurations of multicore platforms with respect to the software execution time and more specifically to the unexpected outliers mentioned above. To this purpose, we will propose a modelling language that will allow for a formal description of the timing properties of real-time embedded multicore software. This modelling language will enable formal methods for schedulability analysis and design space exploration methods, such that timing outliers can be eliminated by suggesting alternative configurations for the multicore platform.

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Cost-effective vibroacoustic monitoring (vibmon_icon). 01/10/2015 - 31/12/2017

Abstract

The Cost effective vibroacoustic monitoring project will attempt to prove the technical and economic feasibility of cost effective vibroacoustic monitoring systems for continuous online condition and process monitoring of rotating machine elements in quasi stationary conditions. The project will make use of new opportunities enabled by the advent of cost effective sensors, like MEMS accelerometers, microphones, and microphone arrays, and cost effective embedded platforms that in combination can provide an efficient solution for continuous monitoring. The generic part of the project will assess the technical limitations of cost effective sensors compared with high-end ones and will overcome this limitations by develop novel digital signal processing algorithms for: • Automatic pre-processing and data cleaning of raw data recorded by cost-effective sensors in order to eliminate non-physical features present in the signals generated by certain cost effective sensors; • Feature extraction for fault detection and identification that can provide reliable diagnostic information and can deal the technical limitations of cost-effective sensors like limited bandwidth, high noise density, and lower sensitivity; • Online tachometer-less estimation of rotational speed in order to reduce the cost of the total solution by eliminating high precision speed sensors; • Reducing of the amount of data generated by the monitoring system while maximizing the amount of information to diminish the communication and data stream handling costs; The project will develop a technology validation platform for a cost effective vibroacoustic monitoring system including sensors, acquisition hardware, embedded processing unit and local digital signal processing software.

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Mobile Robotic Platform for Embodied Sensor Development 01/02/2015 - 31/12/2015

Abstract

This project aims at implementing a mobile robotic platform for supporting our research effort concentrated at the development of intelligent sensors for healthcare applications. The robotic platform will support our research effort by enabling the collection of large amounts of experimental data for extracting sensor models, calibration algorithms and in the development of sensors aimed at the application in autonomous robotic systems.

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Dotation for the structural collaboration with Flanders Make. 01/06/2014 - 31/12/2017

Abstract

Flanders Make's mission is to strengthen the international competitiveness of the Flemish manufacturing industry on the long term through industry-driven, precompetitive, excellent research in the field of mechatronics, product development methods and advanced production technologies and by maximizing valorisation in these areas.

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Service/Reuse for Assistive technology Delivery/design (SeRenADe). 01/01/2014 - 31/12/2017

Abstract

This project represents a formal research agreement between UA and on the other hand Gouverneur Kinsbergen Centre. UA provides Gouverneur Kinsbergen Centreresearch results mentioned in the title of the project under the conditions as stipulated in this contract.

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MBSE4 Mechatronics. 01/01/2014 - 31/12/2017

Abstract

This project represents a research agreement between the UA and on the onther hand IWT. UA provides IWT research results mentioned in the title of the project under the conditions as stipulated in this contract.

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  • Research Project