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Daniel Gordon, Andreas Christou, Theodoros Stouraitis, Michael Gienger, Sethu Vijayakumar , "Learning Personalised Human Sit-to-Stand Motion Strategies via Inverse Musculoskeletal Optimal Control ", IEEE International Conference on Robotics and Automation, 2023.
AbstractPhysically assistive robots and exoskeletons have great potential to help humans with a wide variety of collabora- tive tasks. However, a challenging aspect of the control of such devices is to accurately model or predict human behaviour, which can be highly individual and personalised. In this work, we implement a framework for learning subject-specific models of underlying human motion strategies using inverse musculoskeletal optimal con...
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Chao Wang, Jörg Deigmöller, Pengcheng An, Julian Eggert , "A User Interface for Sense-making of the Reasoning Process while Interacting with Robots", CHI 2023, 2023.
AbstractAs knowledge graph has the potential to bridges the gap between commonsense knowledge and reasoning over actionable capabilities of mobile robotic platforms, incorporating knowledge graph into robotic system attracted increasing attention in recent years. Previously, graph visualization is has been used wildly for developer to make sense of knowledge graph. However, due to lacking the link between abstract knowledge with real world environment...
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Sebastian Brulin and Markus Olhofer , "Bi-level Network Design for UAM Vertiport Allocation Using Activity-Based Transport Simulations", The 6th International Electric Vehicle Technology Conference, 2023.
AbstractThe design of a future Urban Air Mobility (UAM) infrastructure plays an essential role when introducing a new mode of transportation. One key question is where to optimally allocate vertiport facilities to offer the best coverage, mode integration, and highest utilization for a new aerial transportation service. This paper presents a bi-level network design study in which the discrete decisions of the network design planner are optimized based on...
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Tobias Rodemann, Hiroaki Kataoka , Thomas Jatschka, Guenther Raidl, Steffen Limmer, Hiromu Meguro , "Optimizing the positions of battery swapping stations - Pilot studies and layout optimization algorithm ", International Electric Vehicle Technology Conference (EVTeC) 2023, 2023.
AbstractFor electric scooters, battery swapping is a promising alternative to battery charging due to the lower weight and volume of their batteries that allow a manual replacement at battery swapping stations. Mobile batteries are shared between all users and the target of the operator is therefore to maximize the customer satisfaction while minimizing system set-up and operation costs. Here we give an overview of Honda’s activities for a Battery as a S...
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Anna Belardinelli , "Action in the eye of the beholder: what the gaze reveals about intentions and how it can be used", NA, 2023.
AbstractOur refined ability to act in the environment and to interact with manipulable objects relies on the prediction capabilities of our sensorimotor system. Our eyes typically anticipate the next segment in an action sequence, by targeting the relevant object for the following step. Yet, how the final goal, or the way we intend to achieve it, is reflected in the early visual exploration of each object has been less investigated. I will present a se...
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Christian Internó , "Robust Non-Intrusive Load Monitoring for Industrial settings with high fidelity Simulations and Deep Learning ", Universita degli Studi di Milano-Bicocca , 2023.
AbstractNowadays, we are observing the fourth industrial revolution 4.0, which integrates new production technologies to increase productivity and production quality. As a result, new Smart Companies are emerging, with data monitoring systems that are increasingly advanced and interconnected. Therefore, there is a growing need to develop advanced energy monitoring techniques to identify machinery behaviors by observing time series of generated data. Mode...
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Christopher Mower, Theodoros Stouraitis, Joao Moura, Christian Rauch, Lei Yan, Nazanin Zamani Behabadi, Michael Gienger, Tom Vercauteren, Christos Bergeles, Sethu Vijayakumar , "ROS-PyBullet Interface: A framework for reliable contact simulation and human-robot interaction", Conference on Robot Learning, 2023.
AbstractReliable contact simulation plays a key role in the development of (semi-) autonomous robots, especially when dealing with contact-rich manipulation scenarios, an active robotics research topic. Besides simulation, components such as sensing, perception, data collection, robot hardware control, human interfaces, etc. are all key enablers towards applying machine learning algorithms or model-based approaches in real world systems. However, there i...
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Jonathan Jakob, André Artelt, Martina Hasenjäger, Barbara Hammer , "Interpretable SAM-kNN Regressor for Incremental Learning on High-Dimensional Data Streams", Applied Artificial Intelligence, vol. 37, no. 1, 2023.
AbstractIn many real world scenarios, data is provided as a potentially infinite stream of samples, that are subject to changes in the underlying data distribution, a phenomenon often referred to as concept drift. A specific facet of concept drift is feature drift, where the relevance of a feature to the problem at hand changes over time. High-dimensionality of the data poses an additional challenge to learning algorithms operating in such environments....
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Steffen Limmer, Johannes Varga, Guenther Raidl , "An Evolutionary Approach for Scheduling a Fleet of Shared Electric Vehicles", Applications of Evolutionary Computation 2023, Springer Nature Switzerland, pp. 3-18, 2023.
AbstractIn the present paper, we investigate the management of a fleet of electric vehicles. We propose a hybrid evolutionary approach for solving the problem of simultaneously planning the charging of electric vehicles and the assignment of electric vehicles to a set of reservations. The reservation assignment is optimized with an evolutionary algorithm while linear programming is used to compute optimal charging schedules. The evolutionary algorithm us...
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Can Wang, Mitra Baratchi, Thomas Bäck, Holger Hoos, Steffen Limmer, Markus Olhofer , "Towards time series feature engineering in automated machine learning for multi-step forecasting", Proc. of International Conference on Time Series and Forecasting (ITISE2022), vol. 18, no. 1, 2022.
AbstractFeature engineering is an essential step in the pipelines used for many machine learning tasks, including time-series forecasting. Although existing AutoML approaches partly automate feature engineering, they do not support specialised approaches for time-series data such as multi-step forecasting. Multi-step forecasting is the task of predicting a sequence of values in a time series. Two kinds of approaches are commonly used for multi-step forec...
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