Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Trevisan, Elia"'
Autor:
Trevisan, Elia, Alonso-Mora, Javier
Motion planning for autonomous robots in dynamic environments poses numerous challenges due to uncertainties in the robot's dynamics and interaction with other agents. Sampling-based MPC approaches, such as Model Predictive Path Integral (MPPI) contr
Externí odkaz:
http://arxiv.org/abs/2401.09241
Autor:
Zhang, Yuezhe, Pezzato, Corrado, Trevisan, Elia, Salmi, Chadi, Corbato, Carlos Hernández, Alonso-Mora, Javier
Task and Motion Planning (TAMP) has made strides in complex manipulation tasks, yet the execution robustness of the planned solutions remains overlooked. In this work, we propose a method for reactive TAMP to cope with runtime uncertainties and distu
Externí odkaz:
http://arxiv.org/abs/2312.02328
Motion planning for autonomous robots in tight, interaction-rich, and mixed human-robot environments is challenging. State-of-the-art methods typically separate prediction and planning, predicting other agents' trajectories first and then planning th
Externí odkaz:
http://arxiv.org/abs/2309.14931
Autor:
Pezzato, Corrado, Salmi, Chadi, Spahn, Max, Trevisan, Elia, Alonso-Mora, Javier, Corbato, Carlos Hernandez
We present a method for sampling-based model predictive control that makes use of a generic physics simulator as the dynamical model. In particular, we propose a Model Predictive Path Integral controller (MPPI), that uses the GPU-parallelizable Isaac
Externí odkaz:
http://arxiv.org/abs/2307.09105
Publikováno v:
2023 International Conference on Robotics and Automation (ICRA)
Autonomous vehicles that operate in urban environments shall comply with existing rules and reason about the interactions with other decision-making agents. In this paper, we introduce a decentralized and communication-free interaction-aware motion p
Externí odkaz:
http://arxiv.org/abs/2302.06547
Autor:
de Vries, Jitske, Trevisan, Elia, van der Toorn, Jules, Das, Tuhin, Brito, Bruno, Alonso-Mora, Javier
Publikováno v:
2022 International Conference on Robotics and Automation (ICRA)
In unstructured urban canals, regulation-aware interactions with other vessels are essential for collision avoidance and social compliance. In this paper, we propose a regulations aware motion planning framework for Autonomous Surface Vessels (ASVs)
Externí odkaz:
http://arxiv.org/abs/2202.12069
Akademický článek
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Publikováno v:
Repositório Institucional da UFSCUniversidade Federal de Santa CatarinaUFSC.
Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-graduação em Engenharia de Produção
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Made available in DSpace on 2013-07-16T00:46:54Z (GMT). No. of bitstreams: 1 214154.pdf: 740538 bytes, check
Externí odkaz:
http://repositorio.ufsc.br/handle/123456789/102372