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Design and Collaborative Operation of Multimobile Inspection Robots in Smart Microgrids

机译:智能微电网中多用足检测机器人的设计与协作运行

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摘要

This paper investigates the substation inspection problems of multimobile robots for large power stations in smart microgrids. Most multirobot inspection robots generally face the challenge of path planning, while the current widely used biological excitation neural network (BENN) methods often have the defect of the neuronal active field near boundaries and obstacles. To end this, we propose an improved biological excitation neural network (IBENN) method for path planning based on a detailed architecture and ontology framework, through which the single-point inspection, multipoint inspection, and full-area inspection tasks of substations in smart microgrids can be well completed. Simulation results show that the designed IBENN-based multirobot collaboration inspection (MRCI) system can effectively shorten the path as well as the number of turns and then show better performance than most existing results when implementing various substation inspection tasks.
机译:本文研究了智能微电网中大型电站的多媒体机器人变电站检查问题。 大多数多摩托电机检查机器人通常面临路径规划的挑战,而目前广泛使用的生物激发神经网络(Benn)方法通常具有近边界和障碍物的神经元活性场的缺陷。 要结束这一点,我们提出了一种改进的生物激发神经网络(难率)基于详细的体系结构和本体框架的路径规划方法,通过该框架,智能微电网中的单点检查,多点检测和变电站的全域检查任务 可以完整完成。 仿真结果表明,设计的基于IBENN的多机罗电机协作检查(MRCI)系统可以有效地缩短路径以及转弯次数,然后在实现各种变电站检查任务时显示出比大多数现有结果更好的性能。

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