Efficient computation of optimal navigation functions for nonholonomic planning

Prashanth Konkimalla, Steven M. La Valle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a fast, numerical approach to computing optimal feedback motion strategies for a nonholonomic robot in a cluttered environment. Although many techniques exist to compute navigation functions that can incorporate feedback, none of these methods is directly able to determine optimal strategies for general nonholonomic systems. Our approach builds on previous techniques in numerical optimal control, and on our previous efforts in developing algorithms that compute feedback strategies for problems that involve nondeter-ministic and stochastic uncertainties in prediction. The proposed approach efficiently computes an optimal navigation function for nonholonomic systems by exploiting two ideas: 1) the principle of Dijkstra's algorithm can be generalized to continuous configuration spaces and nonholonomic systems, and 2) a simplicial mesh representation can be used to reduce the complexity of numerical interpolation.

Original languageEnglish (US)
Title of host publicationProceedings of the 1st Workshop on Robot Motion and Control, RoMoCo 1999
EditorsK. Tchon
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages187-192
Number of pages6
ISBN (Electronic)0780356551, 9780780356559
DOIs
StatePublished - 1999
Externally publishedYes
Event1st Workshop on Robot Motion and Control, RoMoCo 1999 - Kiekrz, Poland
Duration: Jun 28 1999Jun 29 1999

Publication series

NameProceedings of the 1st Workshop on Robot Motion and Control, RoMoCo 1999

Other

Other1st Workshop on Robot Motion and Control, RoMoCo 1999
Country/TerritoryPoland
CityKiekrz
Period6/28/996/29/99

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Efficient computation of optimal navigation functions for nonholonomic planning'. Together they form a unique fingerprint.

Cite this