7 papers
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…
HumanEgo: Zero-Shot Robot Learning from Minutes of Human Egocentric Videos
Zhi Wang, Botao He, Kelin Yu +4
Human egocentric video captures rich manipulation demonstrations without any robot hardware, yet transferring these skills to robots remains challenging due to the embodiment gap b…
FEEL (Force-Enhanced Egocentric Learning): A Dataset for Physical Action Understanding
Eadom Dessalene, Botao He, Michael Maynord +5
We introduce FEEL (Force-Enhanced Egocentric Learning), the first large-scale dataset pairing force measurements gathered from custom piezoresistive gloves with egocentric video. O…
Adversarial Game-Theoretic Algorithm for Dexterous Grasp Synthesis
Yu Chen, Botao He, Yuemin Mao +7
For many complex tasks, multi-finger robot hands are poised to revolutionize how we interact with the world, but reliably grasping objects remains a significant challenge. We focus…
NavMoE: Hybrid Model- and Learning-based Traversability Estimation for Local Navigation via Mixture of Experts
Botao He, Amir Hossein Shahidzadeh, Yu Chen +8
This paper explores traversability estimation for robot navigation. A key bottleneck in traversability estimation lies in efficiently achieving reliable and robust predictions whil…
ViewActive: Active viewpoint optimization from a single image
Jiayi Wu, Xiaomin Lin, Botao He +2
When observing objects, humans benefit from their spatial visualization and mental rotation ability to envision potential optimal viewpoints based on the current observation. This…