activity
20192025
most citedAdversary A3C for Robust Reinforcement Learning

20 citations · 30 across the 5 of their papers we have counts for

collaborators

7 papers

cs.RO2025

Phy-Tac: Toward Human-Like Grasping via Physics-Conditioned Tactile Goals

Shipeng Lyu, Lijie Sheng, Fangyuan Wang +5

Humans naturally grasp objects with minimal level required force for stability, whereas robots often rely on rigid, over-squeezing control. To narrow this gap, we propose a human-i…

cs.RO20222 cited

SWheg: A Wheel-Leg Transformable Robot With Minimalist Actuator Realization

Cunxi Dai, Xiaohan Liu, Jianxiang Zhou +2

This article presents the design, implementation, and performance evaluation of SWheg, a novel modular wheel-leg transformable robot family with minimalist actuator realization. SW…

cs.RO2022

Predict the Rover Mobility over Soft Terrain using Articulated Wheeled Bevameter

Wenyao Zhang, Shipeng Lv, Feng Xue +3

Robot mobility is critical for mission success, especially in soft or deformable terrains, where the complex wheel-soil interaction mechanics often leads to excessive wheel slip an…

cs.RO20202 cited

Manipulation with Shared Grasping

Yifan Hou, Zhenzhong Jia, Matthew T. Mason

A shared grasp is a grasp formed by contacts between the manipulated object and both the robot hand and the environment. By trading off hand contacts for environmental contacts, a…

cs.RO20196 cited

Reorienting Objects in 3D Space Using Pivoting

Yifan Hou, Zhenzhong Jia, Matthew T. Mason

We consider the problem of reorienting a rigid object with arbitrary known shape on a table using a two-finger pinch gripper. Reorienting problem is challenging because of its non-…

cs.LG201920 cited

Adversary A3C for Robust Reinforcement Learning

Zhaoyuan Gu, Zhenzhong Jia, Howie Choset

Asynchronous Advantage Actor Critic (A3C) is an effective Reinforcement Learning (RL) algorithm for a wide range of tasks, such as Atari games and robot control. The agent learns p…