Steffen Limmer,
"Empirical Study of Stability and Fairness of Schemes for Benefit Distribution in Local Energy Communities",
Energies, vol. 16, no. 4, 2023.
Abstract
The concept of local energy communities is receiving increasing attention. However, the question of how to distribute the benefit of a community among its members is still open. It is commonly desired that the benefit distribution is fair and stable. While benefit distribution schemes such as the nucleolus, Shapley value and Shapley-core are known to perform well in terms of fairness and stability, studies have shown that none of them can guarant...
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Zahra Foroozandeh, Steffen Limmer, Fernando Lezama, Ricardo Faia, Sergio Ramos, Joao Soares,
"A MBNLP Method for Centralized Energy Pricing and Scheduling in Local Energy Community",
IEEE PES Generation, Transmission and Distribution Conference & Exposition 2022 – Latin America (IEEE GTD 2022), 2023.
Abstract
This paper proposes a new optimization model for pricing and demand scheduling in a grid-connected local energy community (LEC), including residential homes (consumers and prosumers), and combined heat and power (CHP) generation units. It is assumed that some homes have photovoltaic (PV) generation, electric vehicles (EVs), or both. A central entity is responsible for managing the EVs' charging and discharging process, and for scheduling energy e...
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Chao Wang, Anna Belardinelli, Daniel Tanneberg, Stephan Hasler, Theodoros Stouraitis, Michael Gienger,
"Enhancing Incremental-learning process of Robotic with Augmented Reality",
CHI 2023, 2023.
Abstract
This interactivity proposal plans to show how the augmented reality (AR) technology can enhance the user experience in teaching and interacting with the robots in the home environment via 3 examples: 1. A demonstration of teaching the robot to utilize some appliance via AR glass. 2. A demonstration that the robot use learned knowledge to accomplish certain task. 3. A demonstration of robotics display its intention and ergonomic consideration via...
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Xilu Wang, Yaochu Jin, Sebastian Schmitt, Markus Olhofer,
"Recent Advances in Bayesian Optimization",
ACM Computing Surveys, 2023.
Abstract
Bayesian optimization has emerged at the forefront of expensive black-box optimization due to its data efficiency. Recent years have witnessed a proliferation of studies on the development of new Bayesian optimization algorithms and their applications. Hence, this paper attempts to provide a comprehensive and updated survey of recent advances in Bayesian optimization and identify interesting open problems. We categorize the existing work on Bayes...
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Chao Wang,
"Design for Collaborative Intelligence: From Connected Vehicle, Autonomous Driving, Robotics to AI",
Shanghai Jiaotong University (Shanghai, China) master course online presentation, 2023.
Abstract
The goal of the intelligent system should be to enhance human capabilities, not replace them. There is much more scope for humans and AI to complement each other than to compete, as their advantages lie in different aspects. This complementarity can be called Collaborative Intelligence (CI), which enables machines to achieve goals together with humans in complex environments. CI requires mutual understanding and seamless communication between the...
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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.
Abstract
Physically 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.
Abstract
As 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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Anna Belardinelli,
"Action in the eye of the beholder: what the gaze reveals about intentions and how it can be used",
NA, 2023.
Abstract
This is an invited talk at the University Carlos III Madrid...
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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.
Abstract
Nowadays, 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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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.
Abstract
In 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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