M2T2 (Multi-Task Masked Transformer) is a unified transformer model for learning different primitive actions.
Primary Use Cases
Given a raw point cloud observation of the scene, M2T2 reasons about contact points and predicts collision-free gripper poses for 6-DoF object-centric grasping and orientation-aware placement.
If you find our work helpful, please consider citing our paper.
@inproceedings{yuan2023m2t2,
title = {M2T2: Multi-Task Masked Transformer for Object-centric Pick and Place},
author = {Yuan, Wentao and Murali, Adithyavairavan and Mousavian, Arsalan and Fox, Dieter},
booktitle = {7th Annual Conference on Robot Learning},
year = {2023}
}
