Home /Research /Particle swarm optimization of potential fields for obstacle avoidance
SWARM

Particle swarm optimization of potential fields for obstacle avoidance

Rainer Palm, Abdelbaki Bouguerra

Year
2013
Citations
17

Abstract

This paper addresses the safe navigation of multiple nonholonomic mobile robots in shared areas. Obstacle avoidance for mobile robots is performed by artificial potential fields and special traffic rules. In addition, the behavior of mobile robots is optimized by particle swarm optimization (PSO). The control of non-holonomic vehicles is performed using the virtual leader principle together with a local linear controller.

Keywords

Obstacle avoidanceMobile robotParticle swarm optimizationObstacleHolonomicRobotCollision avoidanceController (irrigation)Computer scienceNonholonomic system

Related papers

Browse all SWARM papers