Multi-Object Rearrangement with Monte Carlo Tree Search: A Case Study on Planar Nonprehensile SortingShow others and affiliations
2020 (English)Conference paper, Published paper (Refereed)
Abstract [en]
In this work, we address a planar non-prehensile sorting task. Here, a robot needs to push many densely packed objects belonging to different classes into a configuration where these classes are clearly separated from each other. To achieve this, we propose to employ Monte Carlo tree search equipped with a task-specific heuristic function. We evaluate the algorithm on various simulated and real-world sorting tasks. We observe that the algorithm is capable of reliably sorting large number of convex and non-convex objects, as well as convex objects in the presence of immovable obstacles.
Place, publisher, year, edition, pages
IEEE Press, 2020. p. 9433-9440
Series
IEEE International Conference on Intelligent Robots and Systems. Proceedings, ISSN 2153-0858, E-ISSN 2153-0866
National Category
Computer graphics and computer vision Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-89040DOI: 10.1109/IROS45743.2020.9341532ISI: 000724145803056Scopus ID: 2-s2.0-85100653666ISBN: 9781728162133 (print)ISBN: 9781728162126 (electronic)OAI: oai:DiVA.org:oru-89040DiVA, id: diva2:1523712
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA (Virtual), October 25-29, 2020
Funder
Swedish Foundation for Strategic Research Knut and Alice Wallenberg Foundation
Note
Funding agency:
Government of the Hong Kong Special Administrative Region ITS/018/17FP ITS/104/19FP
2021-01-292021-01-292025-02-01Bibliographically approved