Informed Circular Fields for Global Reactive Obstacle Avoidance of Robotic Manipulators

verfasst von

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

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.

Organisationseinheit(en)

Institut für Regelungstechnik

Externe Organisation(en)

Technische Universität München (TUM)

Typ

Aufsatz in Konferenzband

Seiten

1017-1022

Anzahl der Seiten

6

Publikationsdatum

01.07.2023

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Steuerungs- und Systemtechnik

Elektronische Version(en)

https://doi.org/10.48550/arXiv.2212.05815 (Zugang: Offen)
https://doi.org/10.1016/j.ifacol.2023.10.1698 (Zugang: Geschlossen)