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An intelligent navigational strategy for mobile robots in uncertain environments using smart cuckoo search algorithm

机译:使用Smart Cuckoo搜索算法在不确定环境中的移动机器人智能导航策略

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This paper presents the implementation of smart cuckoo search (SCS) algorithm for intelligent path planning of mobile robots. A new fitness function is modeled and optimized by SCS algorithm to generate collision free optimal route for the mobile robots. The simulation results are illustrated to verify the ability of robot to deal with different environment conditions and reach to the target in all the time. Also the results obtained using SCS algorithm is compared with results of Adaptive Particle Swarm Optimization (APSO). It is noticed that SCS algorithm showed better results as compared to APSO. Finally the simulation platform results are validated with Khepera-IV mobile robot experimental results and it is revealed that proposed algorithm is valid and feasible in the mobile robot path planning problems.
机译:本文介绍了移动机器人智能路径规划的智能咕咕案例(SCS)算法。通过SCS算法建模和优化了新的健身功能,为移动机器人产生碰撞最佳路径。示出了仿真结果以验证机器人处理不同环境条件的能力,并一直在达到目标。此外,使用SCS算法获得的结果与自适应粒子群优化(APSO)的结果进行了比较。注意到,与APSO相比,SCS算法显示出更好的结果。最后,使用Khepera-IV移动机器人实验结果验证了模拟平台结果,揭示了在移动机器人路径规划问题中有效和可行的提出算法。

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