Path Quality Improvement of Sampling-Based Planners: An Efficient Optimization-Based Approach Using Analytical Gradients

Jonas Wittmann, Corina Klein, Daniel Rixen

Publikation: Beitrag in Buch/Bericht/KonferenzbandKapitelBegutachtung

3 Zitate (Scopus)

Abstract

Modern collaborative robotic applications require feasible robot motions that are predictable for human coworkers. We propose two path post-processing modules based on nonlinear optimization to improve path quality: the Path Length Post-Processor (PLPP) minimizes the path length; the Path Smoothness Post-Processor (PSPP) improves the path smoothness. Both keep a clearance to obstacles. We derive the analytical gradients of the optimization problem for computational efficiency and we validate our approaches in simulation.

OriginalspracheEnglisch
TitelCISM International Centre for Mechanical Sciences, Courses and Lectures
Herausgeber (Verlag)Springer Science and Business Media Deutschland GmbH
Seiten182-190
Seitenumfang9
DOIs
PublikationsstatusVeröffentlicht - 2022

Publikationsreihe

NameCISM International Centre for Mechanical Sciences, Courses and Lectures
Band606
ISSN (Print)0254-1971
ISSN (elektronisch)2309-3706

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