3 citations · 4 across the 9 of their papers we have counts for
4 papers · 1 filter
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…
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…
RoboChallenge: Large-scale Real-robot Evaluation of Embodied Policies
Adina Yakefu, Bin Xie, Chongyang Xu +34
Testing on real machines is indispensable for robotic control algorithms. In the context of learning-based algorithms, especially VLA models, demand for large-scale evaluation, i.e…
FlowPolicy: Enabling Fast and Robust 3D Flow-based Policy via Consistency Flow Matching for Robot Manipulation
Qinglun Zhang, Zhen Liu, Haoqiang Fan +3
Robots can acquire complex manipulation skills by learning policies from expert demonstrations, which is often known as vision-based imitation learning. Generating policies based o…