A Framework for Joint Grasp and Motion Planning in Confined Spaces

Martin Rudorfer; Jiri Hartvich; Vojtech Vonasek

doi:10.1109/romoco60539.2024.10604306

A Framework for Joint Grasp and Motion Planning in Confined Spaces

Martin Rudorfer
, Jiri Hartvich
, Vojtech Vonasek

Czech Technical University in Prague

Research output: Chapter in Book/Published conference output › Conference publication

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Abstract

Robotic grasping is a fundamental skill across all domains of robot applications. There is a large body of research for grasping objects in table-top scenarios, where finding suitable grasps is the main challenge. In this work, we are interested in scenarios where the objects are in confined
spaces and hence particularly difficult to reach. Planning how the robot approaches the object becomes a major part of the challenge, giving rise to methods for joint grasp and motion planning. The framework proposed in this paper provides 20 benchmark scenarios with systematically increasing difficulty, realistic objects with precomputed grasp annotations, and tools to create and share more scenarios. We further provide two baseline planners and evaluate them on the scenarios, demonstrating that the proposed difficulty levels indeed offer a meaningful progression. We invite the research community to build upon this framework by making all components publicly
available as open source.

Original language	English
Title of host publication	13th International Workshop on Robot Motion and Control, RoMoCo 2024 - Proceedings
Publisher	IEEE
Pages	96-102
Number of pages	7
ISBN (Electronic)	9798350393965
DOIs	https://doi.org/10.1109/romoco60539.2024.10604306
Publication status	Published - 29 Jul 2024
Event	13th International Workshop on Robot Motion and Control - Poznan, Poland Duration: 2 Jul 2024 → 4 Jul 2024

Publication series

Name	International Workshop on Robot Motion and Control, RoMoCo - Proceedings
Publisher	IEEE

Conference

Conference	13th International Workshop on Robot Motion and Control
Abbreviated title	RoMoCo '24
Country/Territory	Poland
City	Poznan
Period	2/07/24 → 4/07/24

Bibliographical note

Copyright © 2024, 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.

Funding

This work was supported in part by the Czech Science Foundation (GACR) through Research Project under Grant 22-24425S, by the European Union under the project Robotics and Advanced Industrial Production (reg. no. CZ.02.01.01/00/22 008/0004590), by CTU grant no SGS23/177/OHK3/3T/13, and by CHIST-ERA under EPSRC grant no. EP/S032487/1. Computational resources were provided by the e-INFRA CZ project (ID:90254), supported by the Ministry of Education, Youth and Sports of the Czech Republic.

Access to Document

10.1109/romoco60539.2024.10604306

Rudorfer et al_jogramop_framework4romoco_AAM
Copyright © 2024, 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.
Accepted author manuscript, 1.83 MB

Cite this

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abstract = "Robotic grasping is a fundamental skill across all domains of robot applications. There is a large body of research for grasping objects in table-top scenarios, where finding suitable grasps is the main challenge. In this work, we are interested in scenarios where the objects are in confined spaces and hence particularly difficult to reach. Planning how the robot approaches the object becomes a major part of the challenge, giving rise to methods for joint grasp and motion planning. The framework proposed in this paper provides 20 benchmark scenarios with systematically increasing difficulty, realistic objects with precomputed grasp annotations, and tools to create and share more scenarios. We further provide two baseline planners and evaluate them on the scenarios, demonstrating that the proposed difficulty levels indeed offer a meaningful progression. We invite the research community to build upon this framework by making all components publicly available as open source.",

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Rudorfer, M, Hartvich, J & Vonasek, V 2024, A Framework for Joint Grasp and Motion Planning in Confined Spaces. in 13th International Workshop on Robot Motion and Control, RoMoCo 2024 - Proceedings. International Workshop on Robot Motion and Control, RoMoCo - Proceedings, IEEE, pp. 96-102, 13th International Workshop on Robot Motion and Control, Poznan, Poland, 2/07/24. https://doi.org/10.1109/romoco60539.2024.10604306

A Framework for Joint Grasp and Motion Planning in Confined Spaces. / Rudorfer, Martin; Hartvich, Jiri; Vonasek, Vojtech.
13th International Workshop on Robot Motion and Control, RoMoCo 2024 - Proceedings. IEEE, 2024. p. 96-102 (International Workshop on Robot Motion and Control, RoMoCo - Proceedings).

Research output: Chapter in Book/Published conference output › Conference publication

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N1 - Copyright © 2024, 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.

PY - 2024/7/29

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A Framework for Joint Grasp and Motion Planning in Confined Spaces

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