31 citations · 120 across the 8 of their papers we have counts for
6 papers · 1 filter
HERD: Continuous Human-to-Robot Evolution for Learning from Human Demonstration
Xingyu Liu, Deepak Pathak, Kris M. Kitani
The ability to learn from human demonstration endows robots with the ability to automate various tasks. However, directly learning from human demonstration is challenging since the…
Legged Locomotion in Challenging Terrains using Egocentric Vision
Ananye Agarwal, Ashish Kumar, Jitendra Malik +1
Animals are capable of precise and agile locomotion using vision. Replicating this ability has been a long-standing goal in robotics. The traditional approach has been to decompose…
Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion
Zipeng Fu, Xuxin Cheng, Deepak Pathak
An attached arm can significantly increase the applicability of legged robots to several mobile manipulation tasks that are not possible for the wheeled or tracked counterparts. Th…
Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning
Wenlong Huang, Igor Mordatch, Pieter Abbeel +1
Dexterous manipulation of arbitrary objects, a fundamental daily task for humans, has been a grand challenge for autonomous robotic systems. Although data-driven approaches using r…
Minimizing Energy Consumption Leads to the Emergence of Gaits in Legged Robots
Zipeng Fu, Ashish Kumar, Jitendra Malik +1
Legged locomotion is commonly studied and expressed as a discrete set of gait patterns, like walk, trot, gallop, which are usually treated as given and pre-programmed in legged rob…
Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion
Tianyu Li, Roberto Calandra, Deepak Pathak +3
Hierarchical learning has been successful at learning generalizable locomotion skills on walking robots in a sample-efficient manner. However, the low-dimensional "latent" action u…