Behavior-based navigation for an indoor mobile robot

Abstract

Reports the implementation of a mobile robot system for autonomous indoor navigation. The system architecture is based on a hybrid approach, which combines a-priori knowledge stored in a hierarchical world model with reactive behavior-based control for navigation guidance and obstacle avoidance. The robot position estimation in the world frame is performed by an iconic matching algorithm and based on scanning laser rangefinder measurements.