Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | IFAC-PapersOnLine |
| Herausgeber/-innen | Hideaki Ishii, Yoshio Ebihara, Jun-ichi Imura, Masaki Yamakita |
| Herausgeber (Verlag) | Elsevier B.V. |
| Seiten | 1017-1022 |
| Seitenumfang | 6 |
| Auflage | 2 |
| ISBN (elektronisch) | 9781713872344 |
| Publikationsstatus | Veröffentlicht - 1 Juli 2023 |
| Veranstaltung | 22nd IFAC World Congress - Yokohama, Japan Dauer: 9 Juli 2023 → 14 Juli 2023 |
Publikationsreihe
| Name | IFAC-PapersOnLine |
|---|---|
| Nummer | 2 |
| Band | 56 |
| ISSN (elektronisch) | 2405-8963 |
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.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
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- BibTex
- RIS
IFAC-PapersOnLine. Hrsg. / Hideaki Ishii; Yoshio Ebihara; Jun-ichi Imura; Masaki Yamakita. 2. Aufl. Elsevier B.V., 2023. S. 1017-1022 (IFAC-PapersOnLine; Band 56, Nr. 2).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › 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.
N1 - Funding Information: This work was supported in part by the Region Hannover in the project roboterfabrik.
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 - 10.48550/arXiv.2212.05815
DO - 10.48550/arXiv.2212.05815
M3 - Conference contribution
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 -