6 papers
Multi-Embodiment Robotic Retargeting via Guided Diffusion Model
Zhefeng Cao, Ben Liu, Shunpeng Yang +3
Motion retargeting for specific robot from existing motion datasets is one critical step in transferring motion patterns from human behaviors to and across various robots. However,…
AISPO: Enhancing Depth Reliability for Robotic Manipulation of Non-Lambertian Objects via Affine-Invariant Shape Prior
Zhiming Chen, Linfang Zheng, Kun Zhang +4
Reliable depth perception is critical for robotic manipulation, especially for non-Lambertian objects such as transparent or highly specular surfaces, where raw depth measurements…
LIPM-Guided Reinforcement Learning for Stable and Perceptive Locomotion in Bipedal Robots
Haokai Su, Haoxiang Luo, Shunpeng Yang +3
Achieving stable and robust perceptive locomotion for bipedal robots in unstructured outdoor environments remains a critical challenge due to complex terrain geometry and susceptib…
Learning Whole-Body Loco-Manipulation for Omni-Directional Task Space Pose Tracking with a Wheeled-Quadrupedal-Manipulator
Kaiwen Jiang, Zhen Fu, Junde Guo +2
In this paper, we study the whole-body loco-manipulation problem using reinforcement learning (RL). Specifically, we focus on the problem of how to coordinate the floating base and…
Multi-Loco: Unifying Multi-Embodiment Legged Locomotion via Reinforcement Learning Augmented Diffusion
Shunpeng Yang, Zhen Fu, Zhefeng Cao +4
Generalizing locomotion policies across diverse legged robots with varying morphologies is a key challenge due to differences in observation/action dimensions and system dynamics.…
A Practical Introduction to Deep Reinforcement Learning
Yinghan Sun, Hongxi Wang, Hua Chen +1
Deep reinforcement learning (DRL) has emerged as a powerful framework for solving sequential decision-making problems, achieving remarkable success in a wide range of applications,…