activity
20182024
most citedASE: Large-Scale Reusable Adversarial Skill Embeddings for Physically Simulated Characters

211 citations · 517 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.RO2024

Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control

Zhongyu Li, Xue Bin Peng, Pieter Abbeel +3

This paper presents a comprehensive study on using deep reinforcement learning (RL) to create dynamic locomotion controllers for bipedal robots. Going beyond focusing on a single l…

cs.RO2022

Creating a Dynamic Quadrupedal Robotic Goalkeeper with Reinforcement Learning

Xiaoyu Huang, Zhongyu Li, Yanzhen Xiang +6

We present a reinforcement learning (RL) framework that enables quadrupedal robots to perform soccer goalkeeping tasks in the real world. Soccer goalkeeping using quadrupeds is a c…

cs.RO202217 cited

GenLoco: Generalized Locomotion Controllers for Quadrupedal Robots

Gilbert Feng, Hongbo Zhang, Zhongyu Li +8

Recent years have seen a surge in commercially-available and affordable quadrupedal robots, with many of these platforms being actively used in research and industry. As the availa…

cs.RO202112 cited

Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots

Zhongyu Li, Xuxin Cheng, Xue Bin Peng +4

Developing robust walking controllers for bipedal robots is a challenging endeavor. Traditional model-based locomotion controllers require simplifying assumptions and careful model…

cs.RO2020

Learning Agile Robotic Locomotion Skills by Imitating Animals

Xue Bin Peng, Erwin Coumans, Tingnan Zhang +3

Reproducing the diverse and agile locomotion skills of animals has been a longstanding challenge in robotics. While manually-designed controllers have been able to emulate many com…