6 papers
GuideWalk: Learning Unified Autonomous Navigation and Locomotion for Humanoid Robots across Versatile Terrains
Haoxuan Han, Chen Chen, Linao Gong +6
Humanoid robots have achieved strong locomotion capabilities, but reliable navigation on versatile terrains remains challenging because obstacle avoidance must be coordinated with…
T-GMP: Terrain-conditioned Generative Motion Priors for Versatile and Natural Humanoid Locomotion
Junhong Guo, Hao Hu, Chen Chen +6
Achieving both anthropomorphic naturalness and robust terrain traversal remains a fundamental challenge in humanoid locomotion. Existing Reinforcement Learning (RL) approaches typi…
Dynamic Whole-Body Dancing with Humanoid Robots -- A Model-Based Control Approach
Shibowen Zhang, Jiayang Wu, Guannan Liu +12
This paper presents an integrated model-based framework for generating and executing dynamic whole-body dance motions on humanoid robots. The framework operates in two stages: offl…
Towards Bridging the Gap between Large-Scale Pretraining and Efficient Finetuning for Humanoid Control
Weidong Huang, Zhehan Li, Hangxin Liu +3
Reinforcement learning (RL) is widely used for humanoid control, with on-policy methods such as Proximal Policy Optimization (PPO) enabling robust training via large-scale parallel…
ECO: Energy-Constrained Optimization with Reinforcement Learning for Humanoid Walking
Weidong Huang, Jingwen Zhang, Jiongye Li +6
Achieving stable and energy-efficient locomotion is essential for humanoid robots to operate continuously in real-world applications. Existing MPC and RL approaches often rely on e…
Path and Motion Optimization for Efficient Multi-Location Inspection with Humanoid Robots
Jiayang Wu, Jiongye Li, Shibowen Zhang +8
This paper proposes a novel framework for humanoid robots to execute inspection tasks with high efficiency and millimeter-level precision. The approach combines hierarchical planni…