Multirobot Motion Planning using Hybrid Mnhs and Genetic Algorithms
نویسنده
چکیده
Planning the motion of multiple robots deals with computing the motion of all robots avoiding any collision. The paper focuses upon the use of hybrid Multi-Neuron Heuristic Search (MNHS) and Genetic Algorithm (GA). The MNHS is an advancement over the conventional A* algorithm and is suited better for maze-like conditions where there is a high degree of uncertainty. The MNHS contributes towards optimality of the solution, while the GA gives it an iterative nature and enables the approach to be used on high resolution maps. MNHS works over the set of points returned by the GA in its fitness function evaluation. A priority based approach is used, where the priorities are decided by the GA. Path feasibility is speed up by using the concept of coarser to finer lookup called momentum. Experimental results show that the combined approach is able to easily solve the problem for a variety of scenarios. Keywords-robotic path planning; multi-robot planning; multi-robot systems; priority based planning; multi-neuron heuristic search; evolutionary algorithms; genetic algorithm; autonomous robotics; intelligent systems
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عنوان ژورنال:
- Applied Artificial Intelligence
دوره 27 شماره
صفحات -
تاریخ انتشار 2013