4 papers · 1 filter
ForceBand: Learning Forceful Manipulation with sEMG
Botao He, Zhi Wang, Linna Kuang +8
Human demonstrations are a scalable data source for learning robot manipulation policies. However, common sources of human demonstration data, such as motion-capture trajectories a…
Video Generators are Robot Policies
Junbang Liang, Pavel Tokmakov, Ruoshi Liu +4
Despite tremendous progress in dexterous manipulation, current visuomotor policies remain fundamentally limited by two challenges: they struggle to generalize under perceptual or b…
Self-Improving Autonomous Underwater Manipulation
Ruoshi Liu, Huy Ha, Mengxue Hou +2
Underwater robotic manipulation faces significant challenges due to complex fluid dynamics and unstructured environments, causing most manipulation systems to rely heavily on human…
Differentiable Robot Rendering
Ruoshi Liu, Alper Canberk, Shuran Song +1
Vision foundation models trained on massive amounts of visual data have shown unprecedented reasoning and planning skills in open-world settings. A key challenge in applying them t…