Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Verghese, Mrinal"'
Autor:
Verghese, Mrinal, Atkeson, Christopher
This study explores the utility of various internet data sources to select among a set of template robot behaviors to perform skills. Learning contact-rich skills involving tool use from internet data sources has typically been challenging due to the
Externí odkaz:
http://arxiv.org/abs/2409.15172
Our research investigates the capability of modern multimodal reasoning models, powered by Large Language Models (LLMs), to facilitate vision-powered assistants for multi-step daily activities. Such assistants must be able to 1) encode relevant visua
Externí odkaz:
http://arxiv.org/abs/2408.03160
Autor:
Verghese, Mrinal, Atkeson, Chris
Tasks where the set of possible actions depend discontinuously on the state pose a significant challenge for current reinforcement learning algorithms. For example, a locked door must be first unlocked, and then the handle turned before the door can
Externí odkaz:
http://arxiv.org/abs/2303.04327
Real-time robot motion planning in complex high-dimensional environments remains an open problem. Motion planning algorithms, and their underlying collision checkers, are crucial to any robot control stack. Collision checking takes up a large portion
Externí odkaz:
http://arxiv.org/abs/2201.04314
We present an orientation adaptive controller to compensate for the effects of highly constrained environments on continuum manipulator actuation. A transformation matrix updated using optimal estimation techniques from optical flow measurements capt
Externí odkaz:
http://arxiv.org/abs/1909.00450