State Space Sampling of Feasible Motions for High Performance Mobile Robot Navigation in Highly Constrained Environments

Abstract : Sampling in the space of controls or actions is a well-established method for ensuring feasible local motion plans. However, as mobile robots advance in performance and competence in complex outdoor environments, this classical motion planning technique ceases to be effective. When environmental constraints severely limit the space of acceptable motions or when global motion planning expresses strong preferences, a state space sampling strategy is more effective. While this has been clear for some time, the practical question is how to achieve it while also satisfying the severe constraints of vehicle dynamic feasibility. This paper presents an effective algorithm for state space sampling based on a model-based trajectory generation approach. This method enables high-speed navigation in highly constrained and/or partially known environments such as trails, roadways, and dense off-road obstacle fields.
Type de document :
Communication dans un congrès
6th International Conference on Field and Service Robotics - FSR 2007, Jul 2007, Chamonix, France. Springer, 42, 2007, Springer Tracts in Advanced Robotics
Liste complète des métadonnées

Littérature citée [8 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/inria-00268023
Contributeur : Inria Rhône-Alpes Documentation <>
Soumis le : lundi 31 mars 2008 - 09:22:33
Dernière modification le : lundi 31 mars 2008 - 10:07:07
Document(s) archivé(s) le : vendredi 21 mai 2010 - 01:02:31

Fichier

fsr_72.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : inria-00268023, version 1

Collections

Citation

Thomas Howard, Colin Green, Alonso Kelly. State Space Sampling of Feasible Motions for High Performance Mobile Robot Navigation in Highly Constrained Environments. 6th International Conference on Field and Service Robotics - FSR 2007, Jul 2007, Chamonix, France. Springer, 42, 2007, Springer Tracts in Advanced Robotics. 〈inria-00268023〉

Partager

Métriques

Consultations de la notice

183

Téléchargements de fichiers

219