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Optimal trajectory of a mobile robot by a Genetic Design Fuzzy logic controller

机译:遗传设计模糊逻辑控制器的移动机器人的最佳轨迹

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Obstacle avoidance and path planning are the most important problems in mobile robots. Besides, finding methods for controlling and decreasing the real robot error in path have been another target for researchers investigation. Usual methods have two separated parts, research target and path planning with obstacle avoidance. In this context, a fuzzy logic controller has been constructed in order to train an intelligent robot. Genetic algorithms are used to optimize the consequences of a Sugeno fuzzy logic optimal controller for the mobile robot navigation. This is to search a target in an environment with and without obstacles. Simulation results verify successful applications of method for real motion situations. An application have been effected in the Khepera robot demonstrating. The Khepera robot can go to the goal and avoid the obstacles successfully.
机译:障碍避免和路径规划是移动机器人中最重要的问题。此外,寻找控制和减少路径中真正的机器人错误的方法是研究人员调查的另一个目标。通常的方法具有两个分隔的零件,研究目标和路径规划,具有避免避免。在这种情况下,建造了模糊逻辑控制器,以便培训智能机器人。遗传算法用于优化Sugeno模糊逻辑最佳控制器的移动机器人导航的后果。这是在有障碍物的环境中搜索目标。仿真结果验证了真实运动情况的方法的成功应用。在Khepera机器人上表现出了应用。 Khepera机器人可以进入目标并成功避免障碍。

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