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pro vyhledávání: '"Knoedler, Luzia"'
Autor:
Knoedler, Luzia, So, Oswin, Yin, Ji, Black, Mitchell, Serlin, Zachary, Tsiotras, Panagiotis, Alonso-Mora, Javier, Fan, Chuchu
Control Barrier Functions (CBFs) have proven to be an effective tool for performing safe control synthesis for nonlinear systems. However, guaranteeing safety in the presence of disturbances and input constraints for high relative degree systems is a
Externí odkaz:
http://arxiv.org/abs/2410.11157
Autor:
Martinez-Baselga, Diego, de Groot, Oscar, Knoedler, Luzia, Alonso-Mora, Javier, Riazuelo, Luis, Montano, Luis
Robot navigation methods allow mobile robots to operate in applications such as warehouses or hospitals. While the environment in which the robot operates imposes requirements on its navigation behavior, most existing methods do not allow the end-use
Externí odkaz:
http://arxiv.org/abs/2409.13393
Autor:
Martinez-Baselga, Diego, de Groot, Oscar, Knoedler, Luzia, Riazuelo, Luis, Alonso-Mora, Javier, Montano, Luis
Navigating mobile robots in social environments remains a challenging task due to the intricacies of human-robot interactions. Most of the motion planners designed for crowded and dynamic environments focus on choosing the best velocity to reach the
Externí odkaz:
http://arxiv.org/abs/2404.16705
As robots shift from industrial to human-centered spaces, adopting mobile manipulators, which expand workspace capabilities, becomes crucial. In these settings, seamless interaction with humans necessitates compliant control. Two common methods for s
Externí odkaz:
http://arxiv.org/abs/2403.13079
Control Barrier Functions (CBFs) that provide formal safety guarantees have been widely used for safety-critical systems. However, it is non-trivial to design a CBF. Utilizing neural networks as CBFs has shown great success, but it necessitates their
Externí odkaz:
http://arxiv.org/abs/2311.10438
In this paper, we address the problem of real-time motion planning for multiple robotic manipulators that operate in close proximity. We build upon the concept of dynamic fabrics and extend them to multi-robot systems, referred to as Multi-Robot Dyna
Externí odkaz:
http://arxiv.org/abs/2310.12816
Autonomous mobile robots require accurate human motion predictions to safely and efficiently navigate among pedestrians, whose behavior may adapt to environmental changes. This paper introduces a self-supervised continual learning framework to improv
Externí odkaz:
http://arxiv.org/abs/2202.07606
Akademický článek
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Autor:
Bai, Xiaoshan, Fielbaum, Andres, Kronmuller, Maximilian, Knoedler, Luzia, Alonso-Mora, Javier
Publikováno v:
IEEE Transactions on Automation Science and Engineering: A Publication of the IEEE Robotics and Automation Society; 2023, Vol. 20 Issue: 2 p1292-1303, 12p
Akademický článek
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