首页> 外文会议>IEEE International Conference on Robotics and Automation >Wind-energy based path planning for Unmanned Aerial Vehicles using Markov Decision Processes
【24h】

Wind-energy based path planning for Unmanned Aerial Vehicles using Markov Decision Processes

机译:基于马尔可夫决策过程的基于风能的无人机航路规划

获取原文

摘要

Exploiting wind-energy is one possible way to extend the flight duration of an Unmanned Aerial Vehicle. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain, time-varying wind fields and plan a path through them that exploits the energy the field provides. A Gaussian distribution is used to determine uncertainty in the time-varying wind fields. We use a Markov Decision Process to plan a path based upon the uncertainty of the Gaussian distribution. Simulation results are presented to compare the direct line of flight between a start and target point with our planned path for energy consumption and time of travel. The result of our method is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.
机译:利用风能是延长无人机飞行时间的一种可能方法。风能还可以用于最大程度地减少计划路径的能耗。在本文中,我们考虑了不确定的随时间变化的风场,并规划了一条利用风场提供的能量的路径。高斯分布用于确定随时间变化的风场中的不确定性。我们使用马尔可夫决策过程根据高斯分布的不确定性来规划路径。给出了仿真结果,以比较起点和目标点之间的直线飞行与我们计划的能耗和行驶时间的路径。我们的方法的结果是在访问每个单元中的风场的高斯分布时,使用访问量最大的单元的路径很健壮。

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