D* Lite with Reset: Improved Version of D* Lite for Complex Environment

Abstract

One of the most vital aspects of navigation problem is path planning, in which we must be able to find the optimal path with minimum total transitions cost from the start to goal. This paper introduces the state-of-the-art D*Lite algorithm and presents the efficiency problem of D* Lite in complex environments, particularly in dynamic maze-like environments, where the effect of changes is costly. We propose the new algorithm D* Lite with Reset (D*LR) with two different criteria for resetting. We prove experimentally the performance improvement of D*LR over D* Lite in complex environments. Further implementation of D*LR on both Processing simulator and robotics framework ROS is also presented.