5 papers
SeedPolicy: Horizon Scaling via Self-Evolving Diffusion Policy for Robot Manipulation
Youqiang Gui, Yuxuan Zhou, Shen Cheng +4
Imitation Learning (IL) enables robots to acquire manipulation skills from expert demonstrations. Diffusion Policy (DP) models multi-modal expert behaviors but degrades when naivel…
Efficient Hybrid SE(3)-Equivariant Visuomotor Flow Policy via Spherical Harmonics for Robot Manipulation
Qinglun Zhang, Shen Cheng, Tian Dan +3
While existing equivariant methods enhance data efficiency, they suffer from high computational intensity, reliance on single-modality inputs, and instability when combined with fa…
Action-Geometry Prediction with 3D Geometric Prior for Bimanual Manipulation
Chongyang Xu, Haipeng Li, Shen Cheng +4
Bimanual manipulation requires policies that can reason about 3D geometry, anticipate how it evolves under action, and generate smooth, coordinated motions. However, existing metho…
HeRO: Hierarchical 3D Semantic Representation for Pose-aware Object Manipulation
Chongyang Xu, Shen Cheng, Haipeng Li +3
Imitation learning for robotic manipulation has progressed from 2D image policies to 3D representations that explicitly encode geometry. Yet purely geometric policies often lack ex…
You Only Look Around: Learning Illumination Invariant Feature for Low-light Object Detection
Mingbo Hong, Shen Cheng, Haibin Huang +2
In this paper, we introduce YOLA, a novel framework for object detection in low-light scenarios. Unlike previous works, we propose to tackle this challenging problem from the persp…