57 citations · 57 across the 4 of their papers we have counts for
4 papers
An Efficient Model-Based Approach on Learning Agile Motor Skills without Reinforcement
Haojie Shi, Tingguang Li, Qingxu Zhu +3
Learning-based methods have improved locomotion skills of quadruped robots through deep reinforcement learning. However, the sim-to-real gap and low sample efficiency still limit t…
Learning Highly Dynamic Behaviors for Quadrupedal Robots
Chong Zhang, Jiapeng Sheng, Tingguang Li +6
Learning highly dynamic behaviors for robots has been a longstanding challenge. Traditional approaches have demonstrated robust locomotion, but the exhibited behaviors lack diversi…
Learning Terrain-Adaptive Locomotion with Agile Behaviors by Imitating Animals
Tingguang Li, Yizheng Zhang, Chong Zhang +5
In this paper, we present a general learning framework for controlling a quadruped robot that can mimic the behavior of real animals and traverse challenging terrains. Our method c…
Lifelike Agility and Play in Quadrupedal Robots using Reinforcement Learning and Generative Pre-trained Models
Lei Han, Qingxu Zhu, Jiapeng Sheng +16
Knowledge from animals and humans inspires robotic innovations. Numerous efforts have been made to achieve agile locomotion in quadrupedal robots through classical controllers or r…