Development and research of chaotic mobile robot based on evolution system with GP

在这项研究中，一个新的避障模型的基础上模糊控制进行了讨论。隶属函数是提高模糊控制精度的一个重要因素。为此，提出了建立隶属函数的方法，使其更适合于控制。利用耦合混沌系统的遗传规划进化系统，可以系统地、自主地产生和调整混沌系统。通过计算机仿真和真实的机器运行实验验证了该方法的实用性。获得了以下结果。(1)通过简单的学习，可以自主地创建隶属函数以避免障碍。(2)该方法可以同时生成一系列所需的函数，以应用于更复杂的避障模型。(3)可以应用于安装机器人。

In this study a new obstacle avoidance model based on fuzzy control is discussed. The membership function is a very importantfactor to raise the accuracy of fuzzy control. So, it proposes the method to create the membership function and make it more proper for the control. It can be created and tuned up in a systematic and autonomous way by applying evolution system of *netic programming(GP) that used the coupled chaotic system. The utility of method was examined by the computer *nulation and the real machine running experiment. The following were obtained. (1) The membership function can be created autonomously by easy learning for obstacle avoidance. (2) A series of functions needed can be generated contemporaneously to be applied to more complicated obstacle avoidance model. (3) It is possible to apply to the mounting robot.