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Integrating Cloud Model in Evolutionary Algorithm for Path Planning of Mobile Robots

机译:集成云模型在移动机器人路径规划中的进化算法中

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Evolutionary algorithms (EA) have been used to solve path planning of mobile robots successfully. However, accuracy and convergence are always topics. The cloud model which transforms qualitative concept into quantitative description, and vice versa, is adept in uncertainty modeling. It can be used in EA for evolving in a uniform and natural way. An EA embedded with cloud model (EACM) for path planning of mobile robots was proposed in this paper. The algorithm adopted floating-point coding and realized fast converging. Simulation results verified the efficiency of our algorithm.
机译:进化算法(EA)已被用于解决移动机器人的路径规划成功。但是,准确性和融合始终是主题。将定性概念转化为定量描述的云模型,反之亦然是擅长不确定性建模的。它可以在EA中使用,以便以统一和自然的方式演变。在本文中提出了嵌入具有云模型(EACM)的EA用于移动机器人的路径规划。该算法采用浮点编码并实现快速收敛。仿真结果验证了我们算法的效率。

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