Turn and orientation Sensitive A* for Autonomous Vehicles in Intelligent Material Handling Systems

Abstract

Autonomous mobile robots are taking on more tasks in warehouses, speeding up operations and reducing accidents that claim many lives each year. This paper proposes a dynamic path planning algorithm, based on $\mathrm{A}^{*}$ search method for large autonomous mobile robots such as forklifts, and generates an optimized, time-efficient path. Simulation results of the proposed turn and orientation sensitive $\mathrm{A}^{*}$ algorithm show that it has a 94% success rate of computing a better or similar path compared to that of default $\mathrm{A}^{*}$. The generated paths are smoother, have fewer turns, resulting in faster execution of tasks. The method also robustly handles unexpected obstacles in the path.