首页> 外文期刊>Transactions of the Institute of Measurement and Control >Route planning algorithm for autonomous underwater vehicles based on the hybrid of particle swarm optimization algorithm and radial basis function
【24h】

Route planning algorithm for autonomous underwater vehicles based on the hybrid of particle swarm optimization algorithm and radial basis function

机译:基于粒子群优化算法混合的自主水下车辆路线规划算法和径向基函数

获取原文
获取原文并翻译 | 示例
           

摘要

The mission route plays an essential role for the mission security and reliability of an unmanned system. This paper gives a route planning method for autonomous underwater vehicles (AUVs) based on the hybrid of particle swarm optimization (PSO) algorithm and radial basis function (RBF). In the improved PSO algorithm, metropolis criterion is used to prevent the improved PSO algorithm from falling into local optimum and RBF is used to smooth the path planned by PSO algorithm. Compared with classic PSO algorithm, the hybrid algorithm of PSO and RBF can avoid falling into the local optimum effectively and plan an anti-collision route. Moreover, based on the simulation results, it can be seen that the approach presented here is more efficient in convergence performance, and the planned route requires lower performance of AUVs.
机译:任务路线为无人驾驶系统的任务安全性和可靠性发挥着重要作用。 本文为基于粒子群优化(PSO)算法(PSO)算法(RBF)的杂交种提供了一种用于自主水下车辆(AUV)的路线规划方法。 在改进的PSO算法中,MetroPopol标准用于防止改进的PSO算法落入局部最佳,RBF用于平滑PSO算法计划的路径。 与经典PSO算法相比,PSO和RBF的混合算法可以避免有效地落入局部最佳,并计划防撞路线。 此外,基于模拟结果,可以看出,这里呈现的方法在收敛性能方面更有效,计划的路线需要降低AUV的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号