Sensor-based robot path planning using harmonic function-based probabilistic roadmaps

Abstract

We present a new sensor-based robot motion planning framework for mobile robot navigation in unknown environments. The main idea of the proposed planning approach, inspired by our recent works on using harmonic function-based probabilistic roadmaps (HFPRM) for robotic navigation in known environments (model-based cases) (Kazemi et al., 2004, 2005), is to utilize a fluid dynamic (FD) paradigm based on potential flows to identify and prioritize critical regions, i.e. narrow passages and hard-to-navigate regions, at the scan planning stage of a sensor-based probabilistic roadmap (PRM). The PRM, which efficiently captures the connectivity of the free space, is incrementally expanded as the robot senses the physical workspace. Computer simulations and experimental results obtained using a mobile robot equipped with ultrasonic range finders are presented