Path Planning with Modified a Star Algorithm for a Mobile Robot

TLDR

The article focuses on mobile robot path planning on a grid map, assuming reliable reactive navigation and SLAM, and does not address those underlying issues. The study aims to present modifications to the A* algorithm—Basic Theta*, Phi*, RSR, and JPS—to improve computational speed and path optimality. The authors evaluated each modification across multiple scenarios with varying environmental complexity. The evaluations show that the appropriate path planning method can be selected based on the specific scenario.

Abstract

This article deals with path planning of a mobile robot based on a grid map. Essential assumption for path planning is a mobile robot with functional and reliable reactive navigation and SLAM. Therefore, such issues are not addressed in this article. The main body of the article introduces several modifications (Basic Theta*, Phi*) and improvements (RSR, JPS) of A star algorithm. These modifications are focused primarily on computational time and the path optimality. Individual modifications were evaluated in several scenarios, which varied in the complexity of environment. On the basis of these evaluations, it is possible to choose path planning method suitable for individual scenario.