Informed Circular Fields for Global Reactive Obstacle Avoidance of Robotic Manipulators

Marvin Becker; Philipp Caspers; Tom Hattendorf; Torsten Lilge; Sami Haddadin; Matthias A. Müller

doi:10.1016/j.ifacol.2023.10.1698

Informed Circular Fields for Global Reactive Obstacle Avoidance of Robotic Manipulators

Marvin Becker, Philipp Caspers, Tom Hattendorf, Torsten Lilge, Sami Haddadin, Matthias A. Müller

Leibniz Universität Hannover

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

In this paper a global reactive motion planning framework for robotic manipulators in complex dynamic environments is presented. In particular, the circular field predictions (CFP) planner from Becker et al. (2021) is extended to ensure obstacle avoidance of the whole structure of a robotic manipulator. Towards this end, a motion planning framework is developed that leverages global information about promising avoidance directions from arbitrary configuration space motion planners, resulting in improved global trajectories while reactively avoiding dynamic obstacles and decreasing the required computational power. The resulting motion planning framework is tested in multiple simulations with complex and dynamic obstacles and demonstrates great potential compared to existing motion planning approaches.

Original language	English
Title of host publication	IFAC-PapersOnLine
Editors	Hideaki Ishii, Yoshio Ebihara, Jun-ichi Imura, Masaki Yamakita
Publisher	Elsevier B.V.
Pages	1017-1022
Number of pages	6
Edition	2
ISBN (Electronic)	9781713872344
DOIs	https://doi.org/10.1016/j.ifacol.2023.10.1698
State	Published - 1 Jul 2023
Event	22nd IFAC World Congress - Yokohama, Japan Duration: 9 Jul 2023 → 14 Jul 2023

Publication series

Name	IFAC-PapersOnLine
Number	2
Volume	56
ISSN (Electronic)	2405-8963

Conference

Conference	22nd IFAC World Congress
Country/Territory	Japan
City	Yokohama
Period	9/07/23 → 14/07/23

Keywords

Autonomous robotic systems
Guidance navigation and control
Motion Planning
Real-Time Collision Avoidance
Robots manipulators

Access to Document

10.1016/j.ifacol.2023.10.1698

Cite this

Becker, M., Caspers, P., Hattendorf, T., Lilge, T., Haddadin, S., & Müller, M. A. (2023). Informed Circular Fields for Global Reactive Obstacle Avoidance of Robotic Manipulators. In H. Ishii, Y. Ebihara, J. Imura, & M. Yamakita (Eds.), IFAC-PapersOnLine (2 ed., pp. 1017-1022). (IFAC-PapersOnLine; Vol. 56, No. 2). Elsevier B.V.. https://doi.org/10.1016/j.ifacol.2023.10.1698

@inproceedings{68e2c660264841ca9a58d6fb7bae8181,

title = "Informed Circular Fields for Global Reactive Obstacle Avoidance of Robotic Manipulators",

abstract = "In this paper a global reactive motion planning framework for robotic manipulators in complex dynamic environments is presented. In particular, the circular field predictions (CFP) planner from Becker et al. (2021) is extended to ensure obstacle avoidance of the whole structure of a robotic manipulator. Towards this end, a motion planning framework is developed that leverages global information about promising avoidance directions from arbitrary configuration space motion planners, resulting in improved global trajectories while reactively avoiding dynamic obstacles and decreasing the required computational power. The resulting motion planning framework is tested in multiple simulations with complex and dynamic obstacles and demonstrates great potential compared to existing motion planning approaches.",

keywords = "Autonomous robotic systems, Guidance navigation and control, Motion Planning, Real-Time Collision Avoidance, Robots manipulators",

author = "Marvin Becker and Philipp Caspers and Tom Hattendorf and Torsten Lilge and Sami Haddadin and M{\"u}ller, \{Matthias A.\}",

note = "Publisher Copyright: Copyright {\textcopyright} 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/); 22nd IFAC World Congress ; Conference date: 09-07-2023 Through 14-07-2023",

year = "2023",

month = jul,

day = "1",

doi = "10.1016/j.ifacol.2023.10.1698",

language = "English",

series = "IFAC-PapersOnLine",

publisher = "Elsevier B.V.",

number = "2",

pages = "1017--1022",

editor = "Hideaki Ishii and Yoshio Ebihara and Jun-ichi Imura and Masaki Yamakita",

booktitle = "IFAC-PapersOnLine",

edition = "2",

}

Becker, M, Caspers, P, Hattendorf, T, Lilge, T, Haddadin, S & Müller, MA 2023, Informed Circular Fields for Global Reactive Obstacle Avoidance of Robotic Manipulators. in H Ishii, Y Ebihara, J Imura & M Yamakita (eds), IFAC-PapersOnLine. 2 edn, IFAC-PapersOnLine, no. 2, vol. 56, Elsevier B.V., pp. 1017-1022, 22nd IFAC World Congress, Yokohama, Japan, 9/07/23. https://doi.org/10.1016/j.ifacol.2023.10.1698

Informed Circular Fields for Global Reactive Obstacle Avoidance of Robotic Manipulators. / Becker, Marvin; Caspers, Philipp; Hattendorf, Tom et al.
IFAC-PapersOnLine. ed. / Hideaki Ishii; Yoshio Ebihara; Jun-ichi Imura; Masaki Yamakita. 2. ed. Elsevier B.V., 2023. p. 1017-1022 (IFAC-PapersOnLine; Vol. 56, No. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Informed Circular Fields for Global Reactive Obstacle Avoidance of Robotic Manipulators

AU - Becker, Marvin

AU - Caspers, Philipp

AU - Hattendorf, Tom

AU - Lilge, Torsten

AU - Haddadin, Sami

AU - Müller, Matthias A.

PY - 2023/7/1

Y1 - 2023/7/1

N2 - In this paper a global reactive motion planning framework for robotic manipulators in complex dynamic environments is presented. In particular, the circular field predictions (CFP) planner from Becker et al. (2021) is extended to ensure obstacle avoidance of the whole structure of a robotic manipulator. Towards this end, a motion planning framework is developed that leverages global information about promising avoidance directions from arbitrary configuration space motion planners, resulting in improved global trajectories while reactively avoiding dynamic obstacles and decreasing the required computational power. The resulting motion planning framework is tested in multiple simulations with complex and dynamic obstacles and demonstrates great potential compared to existing motion planning approaches.

AB - In this paper a global reactive motion planning framework for robotic manipulators in complex dynamic environments is presented. In particular, the circular field predictions (CFP) planner from Becker et al. (2021) is extended to ensure obstacle avoidance of the whole structure of a robotic manipulator. Towards this end, a motion planning framework is developed that leverages global information about promising avoidance directions from arbitrary configuration space motion planners, resulting in improved global trajectories while reactively avoiding dynamic obstacles and decreasing the required computational power. The resulting motion planning framework is tested in multiple simulations with complex and dynamic obstacles and demonstrates great potential compared to existing motion planning approaches.

KW - Autonomous robotic systems

KW - Guidance navigation and control

KW - Motion Planning

KW - Real-Time Collision Avoidance

KW - Robots manipulators

UR - http://www.scopus.com/inward/record.url?scp=85181631254&partnerID=8YFLogxK

U2 - 10.1016/j.ifacol.2023.10.1698

DO - 10.1016/j.ifacol.2023.10.1698

M3 - Conference contribution

AN - SCOPUS:85181631254

T3 - IFAC-PapersOnLine

SP - 1017

EP - 1022

BT - IFAC-PapersOnLine

A2 - Ishii, Hideaki

A2 - Ebihara, Yoshio

A2 - Imura, Jun-ichi

A2 - Yamakita, Masaki

PB - Elsevier B.V.

T2 - 22nd IFAC World Congress

Y2 - 9 July 2023 through 14 July 2023

ER -

Informed Circular Fields for Global Reactive Obstacle Avoidance of Robotic Manipulators

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this