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Jiyuan Shi

7 accepted papers

2026

Kungfubot2: Learning Versatile Motion Skills for Humanoid Whole-Body Control

ICRA 2026poster

Learning versatile whole-body skills by tracking various human motions is a fundamental step toward general-purpose humanoid robots. This task is particularly challenging because a single policy must master a broad repertoire of motion skills while ensuring stability over long-horizon sequences. To …

2026

X-Loco: Towards Generalist Humanoid Locomotion Control via Synergetic Policy Distillation

RSS 2026poster

While recent advances have demonstrated strong performance in individual humanoid skills such as upright locomotion, fall recovery and whole-body coordination, learning a single policy that masters all these skills remains challenging due to the diverse dynamics and conflicting control objectives in…

Cited by 0SourceScholar
2025

Adversarial Locomotion and Motion Imitation for Humanoid Policy Learning

NeurIPS 2025poster

Humans exhibit diverse and expressive whole-body movements. However, attaining human-like whole-body coordination in humanoid robots remains challenging, as conventional approaches that mimic whole-body motions often neglect the distinct roles of upper and lower body. This oversight leads to computa…

Cited by 0SourcecodeScholar
2025

Forward KL Regularized Preference Optimization for Aligning Diffusion Policies

AAAI 2025technical

Diffusion models have achieved remarkable success in sequential decision-making by leveraging the highly expressive model capabilities in policy learning. A central problem for learning diffusion policies is to align the policy output with human intents in various tasks. To achieve this, previous me…

Cited by 3SourcePDFScholar
2025

Humanoid Whole-Body Locomotion on Narrow Terrain via Dynamic Balance and Reinforcement Learning

IROS 2025

Humans possess delicate dynamic balance mechanisms that enable them to maintain stability across diverse terrains and under extreme conditions. However, despite significant advances recently, existing locomotion algorithms for humanoid robots are still struggle to traverse extreme environments, espe

Cited by 17SourcecodeScholar
2025

KungfuBot: Physics-Based Humanoid Whole-Body Control for Learning Highly-Dynamic Skills

NeurIPS 2025poster

Humanoid robots are promising to acquire various skills by imitating human behaviors. However, existing algorithms are only capable of tracking smooth, low-speed human motions, even with delicate reward and curriculum design. This paper presents a physics-based humanoid control framework, aiming to…

Cited by 0SourcecodeScholar
2024

Robust Quadrupedal Locomotion via Risk-Averse Policy Learning

ICRA 2024poster

The robustness of legged locomotion is crucial for quadrupedal robots in challenging terrains. Recently, Reinforcement Learning (RL) has shown promising results in legged locomotion and various methods try to integrate privileged distillation, scene modeling, and external sensors to improve the gene…

Cited by 13SourceScholar