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Gang Han

8 accepted papers

2026

Compose Your Policies! Improving Diffusion-based or Flow-based Robot Policies via Test-time Distribution-level Composition

ICLR 2026poster

Diffusion-based models for robotic control, including vision-language-action (VLA) and vision-action (VA) policies, have demonstrated significant capabilities. Yet their advancement is constrained by the high cost of acquiring large-scale interaction datasets. This work introduces an alternative par…

Cited by 0SourcecodeScholar
2025

Distillation-PPO: A Novel Two-Stage Reinforcement Learning Framework for Humanoid Robot Perceptive Locomotion

IROS 2025

In recent years, humanoid robots have garnered significant attention from both academia and industry due to their high adaptability to environments and human-like characteristics. With the rapid advancement of reinforcement learning, substantial progress has been made in the walking control of human

Cited by 10SourceScholar
2025

Mamba Policy: Towards Efficient 3D Diffusion Policy with Hybrid Selective State Models

IROS 2025

Diffusion models have been widely employed in the field of 3D manipulation due to their efficient capability to learn distributions, allowing for precise prediction of action trajectories. However, diffusion models typically rely on large parameter UNet backbones as policy networks, which can be cha

Cited by 22SourcecodeScholar
2024

Reinforcement Learning with Generalizable Gaussian Splatting

IROS 2024poster

An excellent representation is crucial for reinforcement learning (RL) performance, especially in vision-based reinforcement learning tasks. The quality of the environment representation directly influences the achievement of the learning task. Previous vision-based RL typically uses explicit or imp…

Cited by 2SourceScholar
2024

Whole-body Humanoid Robot Locomotion with Human Reference

IROS 2024poster

Recently, humanoid robots have made significant advances in their ability to perform challenging tasks due to the deployment of Reinforcement Learning (RL), however, the inherent complexity of humanoid robots, including the difficulty of designing complicated reward functions and training entire sop…

Cited by 33SourceScholar
2022

Recursive Hierarchical Projection for Whole-Body Control with Task Priority Transition

IROS 2022poster

Whole-body control (WBC) with task priority transition is an important technology for robots to switch multiple behaviors, change different objectives, and adapt to various environments. Many methods have solved the problem of control continuity in the priority transition process. However, they eith…

Cited by 5SourceScholar
2022

Whole-Body Control with Motion/Force Transmissibility for Parallel-Legged Robot

IROS 2022poster

For achieving kinematically suitable configurations and highly dynamic task execution, an efficient way is to consider robot performance indices in the whole-body control (WBC) of robots. However, current WBC methods have not considered the intrinsic features of parallel robots, especially motion/fo…

Cited by 3SourceScholar