Hybrid FA-GA Controller for Path Planning of Mobile Robot

B. Patle, N. Pagar, D. Parhi, S. Sanap
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Abstract

Recently, in the path planning of mobile robots, navigation in complex areas are still a challenging task using different AI techniques. One such problem of navigation is solved here using the firefly algorithm and the genetic algorithm as a hybrid approach. The proposed approach efficiently handles the sensory information and converts this into taking the accurate decision for solving the challenges of navigation such as obstacle avoidance and target seeking in a static environment. The proposed approach not only ensures path safety but also ensures path optimality on account of navigational parameters such as path length and navigational time. The developed approach has been tested in the simulation environment using the MATLAB software and in the real-time environment using the Khepera robot. The simulation and real-time results in presence of multiple obstacles are presented for the validation of the proposed FA-GA hybrid controller and obtained results are satisfactory in terms of path optimization.
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移动机器人路径规划的混合FA-GA控制器
目前,在移动机器人的路径规划中,使用不同的人工智能技术在复杂区域进行导航仍然是一个具有挑战性的任务。本文采用萤火虫算法和遗传算法作为一种混合方法来解决这类导航问题。该方法有效地处理了感知信息,并将其转化为准确的决策,解决了静态环境下的避障和目标搜索等导航难题。该方法在保证路径安全的同时,考虑路径长度和导航时间等导航参数,保证了路径的最优性。所开发的方法已经在MATLAB软件的仿真环境和Khepera机器人的实时环境中进行了测试。通过多障碍物情况下的仿真和实时结果验证了所提FA-GA混合控制器的有效性,在路径优化方面取得了令人满意的结果。
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