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 dyna...Show MoreMetadata
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.
Date of Conference: 20-21 August 2020
Date Added to IEEE Xplore: 08 October 2020
ISBN Information: