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pro vyhledávání: '"Ji, Yandong"'
Controlling contact forces during interactions is critical for locomotion and manipulation tasks. While sim-to-real reinforcement learning (RL) has succeeded in many contact-rich problems, current RL methods achieve forceful interactions implicitly w
Externí odkaz:
http://arxiv.org/abs/2405.01402
Autor:
Pan, Guoping, Ben, Qingwei, Yuan, Zhecheng, Jiang, Guangqi, Ji, Yandong, Pang, Jiangmiao, Liu, Houde, Xu, Huazhe
Combining the mobility of legged robots with the manipulation skills of arms has the potential to significantly expand the operational range and enhance the capabilities of robotic systems in performing various mobile manipulation tasks. Existing app
Externí odkaz:
http://arxiv.org/abs/2403.17367
Autor:
Liu, Minghuan, Chen, Zixuan, Cheng, Xuxin, Ji, Yandong, Qiu, Ri-Zhao, Yang, Ruihan, Wang, Xiaolong
We study the problem of mobile manipulation using legged robots equipped with an arm, namely legged loco-manipulation. The robot legs, while usually utilized for mobility, offer an opportunity to amplify the manipulation capabilities by conducting wh
Externí odkaz:
http://arxiv.org/abs/2403.16967
Can we enable humanoid robots to generate rich, diverse, and expressive motions in the real world? We propose to learn a whole-body control policy on a human-sized robot to mimic human motions as realistic as possible. To train such a policy, we leve
Externí odkaz:
http://arxiv.org/abs/2402.16796
Knowledge of terrain's physical properties inferred from color images can aid in making efficient robotic locomotion plans. However, unlike image classification, it is unintuitive for humans to label image patches with physical properties. Without la
Externí odkaz:
http://arxiv.org/abs/2311.01405
DribbleBot (Dexterous Ball Manipulation with a Legged Robot) is a legged robotic system that can dribble a soccer ball under the same real-world conditions as humans (i.e., in-the-wild). We adopt the paradigm of training policies in simulation using
Externí odkaz:
http://arxiv.org/abs/2304.01159
Autor:
Ji, Yandong, Li, Zhongyu, Sun, Yinan, Peng, Xue Bin, Levine, Sergey, Berseth, Glen, Sreenath, Koushil
We address the problem of enabling quadrupedal robots to perform precise shooting skills in the real world using reinforcement learning. Developing algorithms to enable a legged robot to shoot a soccer ball to a given target is a challenging problem
Externí odkaz:
http://arxiv.org/abs/2208.01160
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Supplementary Material 1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a24549594b44832a363efeb8a7d7ece1
Akademický článek
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