Abstract
In order to minimize the processing time for multiple robots to finish lots of tasks, an optimized multiple robots task allocation and path planning approach is proposed. In this approach, the optimized task sequence is first schemed on the assumption that all the tasks are processed by one robot. While scheming the task sequence. A star algorithm is employed to plan paths and calculate the path cost. Then, according to the number of the robots, the task sequence has been randomly divided into several task segments that will be assigned to robots. At last, the task number of each task segments are averaged according to the time each robot used, so that the optimized task allocation scheme is got. In this approach, not only multiple robot task allocation, but also the optimized path planning is realized to ensure that the robots can finish all the tasks in the shortest time. The experiments and simulation are provided to validate the effectiveness of the approach. The results show that the proposed approach can scheme optimized multiple robots task allocation and path planning scheme.
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