Zobrazeno 1 - 10
of 206
pro vyhledávání: '"Mouret, Jean-Baptiste"'
This paper presents Words2Contact, a language-guided multi-contact placement pipeline leveraging large language models and vision language models. Our method is a key component for language-assisted teleoperation and human-robot cooperation, where hu
Externí odkaz:
http://arxiv.org/abs/2407.14229
Humanoid robots could benefit from using their upper bodies for support contacts, enhancing their workspace, stability, and ability to perform contact-rich and pushing tasks. In this paper, we propose a unified approach that combines an optimization-
Externí odkaz:
http://arxiv.org/abs/2407.12381
Autor:
Anne, Timothée, Mouret, Jean-Baptiste
Optimizing a set of functions simultaneously by leveraging their similarity is called multi-task optimization. Current black-box multi-task algorithms only solve a finite set of tasks, even when the tasks originate from a continuous space. In this pa
Externí odkaz:
http://arxiv.org/abs/2402.01275
Publikováno v:
IEEE Robotics and Automation Letters, 2024, 9 (6), pp.5639-5646
Many humanoid and multi-legged robots are controlled in positions rather than in torques, which prevents direct control of contact forces, and hampers their ability to create multiple contacts to enhance their balance, such as placing a hand on a wal
Externí odkaz:
http://arxiv.org/abs/2312.16465
Autor:
Rouxel, Quentin, Wen, Ruoshi, Li, Zhibin, Tiseo, Carlo, Mouret, Jean-Baptiste, Ivaldi, Serena
This short paper outlines two recent works on multi-contact teleoperation and the development of the SEIKO (Sequential Equilibrium Inverse Kinematic Optimization) framework. SEIKO adapts commands from the operator in real-time and ensures that the re
Externí odkaz:
http://arxiv.org/abs/2308.03479
Quality Diversity (QD) algorithms such as MAP-Elites are a class of optimisation techniques that attempt to find many high performing points that all behave differently according to a user-defined behavioural metric. In this paper we propose the Baye
Externí odkaz:
http://arxiv.org/abs/2307.09326
Humanoid robots could replace humans in hazardous situations but most of such situations are equally dangerous for them, which means that they have a high chance of being damaged and falling. We hypothesize that humanoid robots would be mostly used i
Externí odkaz:
http://arxiv.org/abs/2203.00316
Grasping made impressive progress during the last few years thanks to deep learning. However, there are many objects for which it is not possible to choose a grasp by only looking at an RGB-D image, might it be for physical reasons (e.g., a hammer wi
Externí odkaz:
http://arxiv.org/abs/2203.00384
Reinforcement learning agents perform well when presented with inputs within the distribution of those encountered during training. However, they are unable to respond effectively when faced with novel, out-of-distribution events, until they have und
Externí odkaz:
http://arxiv.org/abs/2112.09670
Humanoid robots could be versatile and intuitive human avatars that operate remotely in inaccessible places: the robot could reproduce in the remote location the movements of an operator equipped with a wearable motion capture device while sending vi
Externí odkaz:
http://arxiv.org/abs/2107.01281