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cs.RO2024
Maximizing Alignment with Minimal Feedback: Efficiently Learning Rewards for Visuomotor Robot Policy Alignment
Ran Tian, Yilin Wu, Chenfeng Xu +3
Visuomotor robot policies, increasingly pre-trained on large-scale datasets, promise significant advancements across robotics domains. However, aligning these policies with end-use…
cs.RO2024
HACMan++: Spatially-Grounded Motion Primitives for Manipulation
Bowen Jiang, Yilin Wu, Wenxuan Zhou +2
Although end-to-end robot learning has shown some success for robot manipulation, the learned policies are often not sufficiently robust to variations in object pose or geometry. T…