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Navigation Based on Adaptive Shuffled Frog-Leaping Algorithm for Underwater Mobile Robot

机译:基于Adaptive Shuffled Frog-Leg-Lem-Liboot算法的导航

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Navigational approach for underwater robot may be inferred as a numerical solution to the nonlinear optimal control problem. Adaptive shuffled frog-leaping algorithm has been chosen as a dynamic path planning scheme for underwater robot to track target position while avoiding obstacles. By introducing adaptation procedure in proposed algorithm, the optimization of path as well as time taken can be done through an iterative process by avoiding local minima situation. Objective function with adaptive parameter set as well as stopping criterion of iteration process has been chosen based on distance between robot and target as well as obstacles to regulate convergence rate toward optimal solution. The simulated as well as experimental analysis may validate the properties of the heuristic navigational approach such as faster decision-making, obstacle avoidance, and target seeking behavior during navigation of underwater robot in a messy environment.
机译:水下机器人的导航方法可以被推断为对非线性最佳控制问题的数值解决方案。已选择自适应播放的青蛙跳跃算法作为水下机器人的动态路径规划方案,以跟踪目标位置,同时避免障碍物。通过在提出算法中引入适应程序,通过避免局部最小情况,可以通过迭代过程来完成路径以及所花费的时间的优化。基于机器人和目标之间的距离以及对最佳解决方案的障碍来选择具有自适应参数集的目标函数以及停止迭代过程的标准。模拟以及实验分析可以验证启发式导航方法的性质,例如更快的决策,避免避免和目标在凌乱环境中的水下机器人航行期间的寻求行为。

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