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pro vyhledávání: '"Imdieke, Adam"'
This paper primarily focuses on learning robust visual-force policies in the context of high-precision object assembly tasks. Specifically, we focus on the contact phase of the assembly task where both objects (peg and hole) have made contact and the
Externí odkaz:
http://arxiv.org/abs/2410.14968
Training generalist robot agents is an immensely difficult feat due to the requirement to perform a huge range of tasks in many different environments. We propose selectively training robots based on end-user preferences instead. Given a factory mode
Externí odkaz:
http://arxiv.org/abs/2402.12509