Sampling based time efficient path planning algorithm for mobile platforms
Tarek Taha, Jaime Valls Miró, Gamini Dissanayake · UTS ePRESS (University of Technology Sydney) · 2006
In this paper we present a time efficient one step path planning algorithm for navigating a large robotic platform in indoor environments. The proposed strategy, based on the generation of a novel search space [1], relies on non-uniform density sampling of the free areas to direct the computational resources to troubled and difficult regions, such as narrow passages, leaving the larger open spaces sparsely populated. A smoothing penalty is also associated to the nodes to encourage the generation of gentle paths along the middle of the empty spaces. Collision detection is carried out off-line during the creation of the configuration space to speed up the actual search for the path, which is done on-line. Results compared to currently available path planning algorithms such as Randomly-exploring Random Trees (RRTs) and Probabilistic Road Maps (PRMs) proved that the proposed approach considerably reduces the searching time and produces smoother paths with less jagged path segments than those from randomized planners.