Turn and orientation Sensitive A* for Autonomous Vehicles in Intelligent Material Handling Systems
Rashmi Ballamajalu, Maojia Li, Ferat Sahin, Clark G. Hochgraf, Raymond Ptucha, Michael E. Kuhl · 2020
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.