103 citations · 170 across the 14 of their papers we have counts for
4 papers · 1 filter
Touch begins where vision ends: Generalizable policies for contact-rich manipulation
Zifan Zhao, Siddhant Haldar, Jinda Cui +2
Data-driven approaches struggle with precise manipulation; imitation learning requires many hard-to-obtain demonstrations, while reinforcement learning yields brittle, non-generali…
Feel the Force: Contact-Driven Learning from Humans
Ademi Adeniji, Zhuoran Chen, Vincent Liu +5
Controlling fine-grained forces during manipulation remains a core challenge in robotics. While robot policies learned from robot-collected data or simulation show promise, they st…
Towards Embodiment Scaling Laws in Robot Locomotion
Bo Ai, Liu Dai, Nico Bohlinger +7
Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…
Point Policy: Unifying Observations and Actions with Key Points for Robot Manipulation
Siddhant Haldar, Lerrel Pinto
Building robotic agents capable of operating across diverse environments and object types remains a significant challenge, often requiring extensive data collection. This is partic…