One-shot Imitation Learning via Interaction Warping
Ondrej Biza, Skye Thompson, Kishore Reddy Pagidi, Abhinav Kumar, Elise van der Pol, Robin Walters, Thomas Kipf, Jan-Willem van de Meent
Abstract
Learning robot policies from few demonstrations is crucial in open-ended applications. We propose a new method, Interaction Warping, for one-shot learning SE(3) robotic manipulation policies. We infer the 3D mesh of each object in the environment using shape warping, a technique for aligning point clouds across object instances. Then, we represent manipulation actions as keypoints on objects, which can be warped with the shape of the object. We show successful one-shot imitation learning on three simulated and real-world object re-arrangement tasks. We also demonstrate the ability of our method to predict object meshes and robot grasps in the wild. Webpage: https://shapewarping.github.io.
BibTeX
@inproceedings{
biza2023oneshot,
title={One-shot Imitation Learning via Interaction Warping},
author={Ondrej Biza and Skye Thompson and Kishore Reddy Pagidi and Abhinav Kumar and Elise van der Pol and Robin Walters and Thomas Kipf and Jan-Willem van de Meent and Lawson L.S. Wong and Robert Platt},
booktitle={7th Annual Conference on Robot Learning},
year={2023},
url={https://openreview.net/forum?id=RaNAaxZfKi8}
}