paper

Stable Object Reorientation using Contact Plane Registration

arXiv:2208.08962 · doi:10.1109/ICRA46639.2022.9811655

Abstract

We present a system for accurately predicting stable orientations for diverse rigid objects. We propose to overcome the critical issue of modelling multimodality in the space of rotations by using a conditional generative model to accurately classify contact surfaces. Our system is capable of operating from noisy and partially-observed pointcloud observations captured by real world depth cameras. Our method substantially outperforms the current state-of-the-art systems on a simulated stacking task requiring highly accurate rotations, and demonstrates strong sim2real zero-shot transfer results across a variety of unseen objects on a real world reorientation task. Project website: \url{https://richardrl.github.io/stable-reorientation/}

7 pages, 1 additional page for references

References in corpus (5)

Stable Object Reorientation using Contact Plane Registration · wovepaper