most citedMulti-expert learning of adaptive legged locomotion

198 citations · 225 across the 4 of their papers we have counts for

collaborators

7 papers

cs.RO2020198 cited

Multi-expert learning of adaptive legged locomotion

Chuanyu Yang, Kai Yuan, Qiuguo Zhu +2

Achieving versatile robot locomotion requires motor skills which can adapt to previously unseen situations. We propose a Multi-Expert Learning Architecture (MELA) that learns to ge…

cs.RO2020

Learning natural locomotion behaviors for humanoid robots using human knowledge

Chuanyu Yang, Kai Yuan, Shuai Heng +2

This paper presents a new learning framework that leverages the knowledge from imitation learning, deep reinforcement learning, and control theories to achieve human-style locomoti…

cs.RO20204 cited

Reaching, Grasping and Re-grasping: Learning Multimode Grasping Skills

Wenbin Hu, Chuanyu Yang, Kai Yuan +1

The ability to adapt to uncertainties, recover from failures, and coordinate between hand and fingers are essential sensorimotor skills for fully autonomous robotic grasping. In th…

cs.RO20202 cited

Learning Pregrasp Manipulation of Objects from Ungraspable Poses

Zhaole Sun, Kai Yuan, Wenbin Hu +2

In robotic grasping, objects are often occluded in ungraspable configurations such that no pregrasp pose can be found, eg large flat boxes on the table that can only be grasped fro…

cs.RO202021 cited

Learning Whole-body Motor Skills for Humanoids

Chuanyu Yang, Kai Yuan, Wolfgang Merkt +3

This paper presents a hierarchical framework for Deep Reinforcement Learning that acquires motor skills for a variety of push recovery and balancing behaviors, i.e., ankle, hip, fo…

cs.RO2020

Force-guided High-precision Grasping Control of Fragile and Deformable Objects using sEMG-based Force Prediction

Ruoshi Wen, Kai Yuan, Qiang Wang +2

Regulating contact forces with high precision is crucial for grasping and manipulating fragile or deformable objects. We aim to utilize the dexterity of human hands to regulate the…