356 citations · 1.9k across the 37 of their papers we have counts for
6 papers · 1 filter
Hybrid Random Features
Krzysztof Choromanski, Haoxian Chen, Han Lin +10
We propose a new class of random feature methods for linearizing softmax and Gaussian kernels called hybrid random features (HRFs) that automatically adapt the quality of kernel es…
Multi-Task Learning with Sequence-Conditioned Transporter Networks
Michael H. Lim, Andy Zeng, Brian Ichter +5
Enabling robots to solve multiple manipulation tasks has a wide range of industrial applications. While learning-based approaches enjoy flexibility and generalizability, scaling th…
Implicit Behavioral Cloning
Pete Florence, Corey Lynch, Andy Zeng +7
We find that across a wide range of robot policy learning scenarios, treating supervised policy learning with an implicit model generally performs better, on average, than commonly…
Learning to See before Learning to Act: Visual Pre-training for Manipulation
Lin Yen-Chen, Andy Zeng, Shuran Song +2
Does having visual priors (e.g. the ability to detect objects) facilitate learning to perform vision-based manipulation (e.g. picking up objects)? We study this problem under the f…
XIRL: Cross-embodiment Inverse Reinforcement Learning
Kevin Zakka, Andy Zeng, Pete Florence +3
We investigate the visual cross-embodiment imitation setting, in which agents learn policies from videos of other agents (such as humans) demonstrating the same task, but with star…
Spatial Intention Maps for Multi-Agent Mobile Manipulation
Jimmy Wu, Xingyuan Sun, Andy Zeng +3
The ability to communicate intention enables decentralized multi-agent robots to collaborate while performing physical tasks. In this work, we present spatial intention maps, a new…