26 citations · 43 across the 8 of their papers we have counts for
8 papers
PALo: Learning Posture-Aware Locomotion for Quadruped Robots
Xiangyu Miao, Jun Sun, Hang Lai +4
With the rapid development of embodied intelligence, locomotion control of quadruped robots on complex terrains has become a research hotspot. Unlike traditional locomotion control…
World Model-based Perception for Visual Legged Locomotion
Hang Lai, Jiahang Cao, Jiafeng Xu +5
Legged locomotion over various terrains is challenging and requires precise perception of the robot and its surroundings from both proprioception and vision. However, learning dire…
LoopSR: Looping Sim-and-Real for Lifelong Policy Adaptation of Legged Robots
Peilin Wu, Weiji Xie, Jiahang Cao +2
Reinforcement Learning (RL) has shown its remarkable and generalizable capability in legged locomotion through sim-to-real transfer. However, while adaptive methods like domain ran…
Bridging the Sim-to-Real Gap from the Information Bottleneck Perspective
Haoran He, Peilin Wu, Chenjia Bai +5
Reinforcement Learning (RL) has recently achieved remarkable success in robotic control. However, most works in RL operate in simulated environments where privileged knowledge (e.g…
Sim-to-Real Transfer for Quadrupedal Locomotion via Terrain Transformer
Hang Lai, Weinan Zhang, Xialin He +4
Deep reinforcement learning has recently emerged as an appealing alternative for legged locomotion over multiple terrains by training a policy in physical simulation and then trans…
A Survey on Model-based Reinforcement Learning
Fan-Ming Luo, Tian Xu, Hang Lai +3
Reinforcement learning (RL) solves sequential decision-making problems via a trial-and-error process interacting with the environment. While RL achieves outstanding success in play…