Path Planning with a Lazy Significant Edge Algorithm (LSEA)

Authors

Joseph Polden, University of WollongongFollow
Zengxi Pan, University of WollongongFollow
Nathan Larkin, University of WollongongFollow
Stephen Van Duin, University of WollongongFollow

RIS ID

78401

Publication Details

Polden, J., Pan, Z., Larkin, N. & Van Duin, S. (2013). Path Planning with a Lazy Significant Edge Algorithm (LSEA). International Journal of Advanced Robotic Systems, 10 (198), 1-8.

Abstract

Probabilistic methods have been proven to be effective for robotic path planning in a geometrically complex environment. In this paper, we propose a novel approach, which utilizes a specialized roadmap expansion phase, to improve lazy probabilistic path planning. This expansion phase analyses roadmap connectivity information to bias sampling towards objects in the workspace that have not yet been navigated by the robot. A new method to reduce the number of samples required to navigate narrow passages is also proposed and tested. Experimental results show that the new algorithm is more efficient than the traditional path planning methodologies. It was able to generate solutions for a variety of path planning problems faster, using fewer samples to arrive at a valid solution.