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Sensor-Based Recognition Fuzzy Mobile Robot Systems Designs

机译:基于传感器的识别模糊移动机器人系统设计

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Evolutionary particle swarm optimization (PSO) machines with hybrid sensors (i.e., radio frequency identification (RFID) and E-compass wireless network sensors) and the concepts of traveling salesman problems (TSPs) are applied to recognize the optimal routing paths in a dynamic space. Four active RFID tags and an E-compass indicate the robot position. The PSO algorithm with the guides of specific fitness functions simultaneously develops the proper fuzzy rules, avoids obstacles, and approaches the shortest routing path. The practice mobile robot control problems are considered to demonstrate the efficiency of the fuzzy control system. An illustrated simulation shows that the mobile robot system with the evolutional learning scheme can acquire the appropriate fuzzy rules to overcome multiple obstacles and achieve desired goals in dynamic and nonlinear environments.
机译:具有混合传感器(即射频识别(RFID)和电子罗盘无线网络传感器)的进化粒子群优化(PSO)机器和旅行商问题(TSP)的概念被应用于识别动态空间中的最佳路由路径。四个活动的RFID标签和一个电子罗盘指示机器人的位置。以特定适应度函数为指导的PSO算法可同时开发适当的模糊规则,避免障碍并接近最短的路由路径。考虑了实践中的移动机器人控制问题,以证明模糊控制系统的效率。图示的仿真表明,具有演化学习方案的移动机器人系统可以获取适当的模糊规则,以克服多个障碍,并在动态和非线性环境中实现期望的目标。

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