Singularity avoidance with application to online trajectory optimization for serial manipulators

Florian Beck, Minh Nhat Vu, Christian Hartl-Nesic, Andreas Kugi

Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Oral Presentationpeer-review

Abstract

This work proposes a novel singularity avoidance approach for real-time trajectory optimization based on known singular configurations. The focus of this work lies on analyzing kinematically singular configurations for three robots with different kinematic structures, i.e., the Comau Racer 7-1.4, the KUKA LBR iiwa 14 R820, and the Franka Emika Panda, and exploiting these configurations in form of tailored potential functions for singularity avoidance. Monte Carlo simulations of the proposed method and the commonly used manipulability maximization approach are performed for comparison. The numerical results show that the average computing time can be reduced and shorter trajectories in both time and path length are obtained with the proposed approach.
Original languageEnglish
Title of host publicationProceedings of the 22nd IFAC World Congress
Pages284-291
Volume56
Edition2
DOIs
Publication statusPublished - Jul 2023
Event22nd IFAC World Congress - Yokohama, Japan
Duration: 9 Jul 202314 Jul 2023

Publication series

NameIFAC-PapersOnline
PublisherIFAC Secretariat
ISSN (Print)2405-8963

Conference

Conference22nd IFAC World Congress
Country/TerritoryJapan
CityYokohama
Period9/07/2314/07/23

Research Field

  • Complex Dynamical Systems

Keywords

  • singularity avoidance
  • motion planning
  • trajectory optimization
  • manipulability
  • redundant manipulators

Fingerprint

Dive into the research topics of 'Singularity avoidance with application to online trajectory optimization for serial manipulators'. Together they form a unique fingerprint.

Cite this