Improving the Hybrid A* method for a non-holonomic wheeled robot

Abstract

This article proposes and completely describes a modification of the Hybrid A* method used for navigation of a non-holonomic mobile wheeled robot. Our modification allows straightforward multi-criterial adjustment of the algorithm according to the desired behavior considering not only traveled distance but also time, changing of direction, stopping, going backwards while avoiding obstacles. The obstacle avoidance algorithm evaluates the danger of collision smoothly (not-binarily) using danger fields. Such behavior reflects human-like sensing of danger—the closer to the obstacle the robot is, the higher is the danger of collision. A modified uniform state expansion method has been used to cover the state space of the robot more uniformly providing the possibility of precise near-target navigation. A greed factor has been introduced to decrease the computational time and improve the real-time performance of the algorithm.