ReorientBot: learning object reorientation for specific-posed placement

Publication available at: https://arxiv.org/pdf/2202.11092
Title: ReorientBot: learning object reorientation for specific-posed placement
Authors: Wada, K
James, S
Davison, AJ
Item Type: Conference Paper
Abstract: Robots need the capability of placing objects in arbitrary, specific poses to rearrange the world and achieve various valuable tasks. Object reorientation plays a crucial role in this as objects may not initially be oriented such that the robot can grasp and then immediately place them in a specific goal pose. In this work, we present a vision-based manipulation system, ReorientBot, which consists of 1) visual scene understanding with pose estimation and volumetric reconstruction using an onboard RGB-D camera; 2) learned waypoint selection for successful and efficient motion generation for reorientation; 3) traditional motion planning to generate a collision-free trajectory from the selected waypoints. We evaluate our method using the YCB objects in both simulation and the real world, achieving 93% overall success, 81% improvement in success rate, and 22% improvement in execution time compared to a heuristic approach. We demonstrate extended multi-object rearrangement showing the general capability of the system.
Date of Acceptance: 1-Jul-2022
URI: http://hdl.handle.net/10044/1/99512
DOI: 10.1109/icra46639.2022.9811881
Publisher: IEEE
Journal / Book Title: 2022 International Conference on Robotics and Automation (ICRA)
Copyright Statement: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Dyson Technology Limited
Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: PO 4500501004
EP/S036636/1
Conference Name: 2022 IEEE International Conference on Robotics and Automation (ICRA)
Publication Status: Published
Start Date: 2022-05-23
Finish Date: 2022-05-27
Open Access location: https://arxiv.org/pdf/2202.11092
Appears in Collections:Computing