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个人简介
Matthew Travers’ research focuses on developing the intelligence necessary to enable complex platforms to autonomously interact with and perform meaningful work in complex environments. The task areas on which he is currently focusing include biologically inspired dynamic locomotion and learning, compliant manipulation for agriculture and food preparation, managing uncertainty in human-robot interaction, and field-ready search and rescue robotics. The central ideas that underlie the analytical aspects of Travers’ work are drawn from classical control theory, Bayesian inference, practical optimal control, and modern reinforcement learning.
研究兴趣
论文共 96 篇作者统计合作学者相似作者
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CoRR (2024)
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Rohan Thakker,Michael Paton,Marlin Strub, Michael Swan, Tiago Vaquero, Bryson Jones,Guglielmo Daddi, Rob Royce,Joseph Bowkett, Daniel Loret de Mola Lemus, Daniel Pastor Moreno,Yashwanth Kumar Nakka,
AIAA SCITECH 2024 Forum (2024)
Chao Cao,Lucas Nogueira,Hongbiao Zhu,John Keller,Graeme Best,Rohit Garg, David Kohanbash, Jay Maier,Shibo Zhao,Fan Yang, Katarina Cujic, Ryan Darnley,
Field Roboticsno. 1 (2023): 801-836
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Rohan Thakker,Michael Paton,Marlin P. Strub, Michael Swan,Guglielmo Daddi, Rob Royce, Phillipe Tosi,Matthew Gildner, Tiago Vaquero,Marcel Veismann, Peter Gavrilov,Eloise Marteau,
2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)pp.9886-9893, (2023)
IEEE International Conference on Robotics and Automationno. 1 (2022): 9477-9483
Ryan Darnley,Matthew Travers
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