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Navigation Control of Mobile Robot in Unknown Environments Using Adaptive Cuckoo Search Algorithm

机译:使用自适应Cuckoo搜索算法在未知环境中的移动机器人导航控制

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Navigation is one of the major challenges while designing a mobile robot. This paper introduces a novel path planning method for mobile robot based on Adaptive Cuckoo Search (ACS) algorithm. The classical CS algorithm is modified in terms of step size and local search strategy to make it adaptive approach. We formulate a fitness function considering distance between robot to obstacle and the slope between goal to robot and it is optimized by ACS algorithm to reach the goal in most appropriate path. The performance of the proposed algorithm is verified in simulated environment. It is confirmed that the proposed path planning model successfully completes the navigation control in unknown environments.
机译:导航是设计移动机器人时的主要挑战之一。本文介绍了一种基于自适应覆滤网搜索(ACS)算法的移动机器人的新型路径规划方法。在步骤尺寸和本地搜索策略方面修改了古典CS算法,以使其自适应方法。我们制定了考虑机器人到障碍物之间的距离和目标到机器人之间的坡度的健身功能,并且通过ACS算法优化了在最合适的路径中达到目标。在模拟环境中验证了所提出的算法的性能。确认所提出的路径规划模型成功完成了未知环境中的导航控制。

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