An Incremental Harmonic Function-based Probabilistic Roadmap Approach to Robot Path Planning

A new hybrid motion planning technique based on Harmonic Functions (HF) and Probabilistic Roadmaps (PRM) is presented. The proposed approach consists of incrementally building a Probabilistic Roadmap using information obtained about the workspace topology through the Fluid Dynamic (FD) paradigm based on HFs. The crux of our approach is to identify narrow passages using FD paradigm and pass the information obtained over to a PRM method to build a roadmap to capture the connectivity of free configuration space (C-space) especially in narrow regions. As an extension to our recent works on using Harmonic Function-based Probabilistic Roadmaps (HFPRM) for robotic navigation [1], we propose an Incremental HFPRM (IHFPRM) technique which is more general and can be applied to virtually any type of robot. Simulation results presented in this paper show that the combination of the HF and the PRM works better than each individual in terms of finding a collision free path in environments where narrow passages exist. This technique can be extended to the sensor-based motion planning of robots (mobile and/or articulated) which is the long-term objective in carrying out this research.