• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Aerospace and Electronic Systems, IEEE Transactions on >Two-stage trajectory planning for stable image acquisition of a fixed wing uav
【24h】

Two-stage trajectory planning for stable image acquisition of a fixed wing uav

机译：两阶段轨迹规划，用于固定翼无人机的稳定图像采集

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We propose a two-stage trajectory planning (TSTP) method using monocular vision for keeping continuous surveillance or reconnaissance of a target, and for relaying communication between a ground vehicle and an unmanned aerial vehicle (UAV). The cost function for optimal trajectory includes the variation of the altitude and speed of the UAV to prevent sudden maneuvering. The position of the target in the image is also included in a cost function for continuous observation. A virtual image can be calculated from the relationship between the coordinates of the UAV and those of the camera. The proposed cost function can be affected to a greater degree than in generic optimization problems because it has the position of the target in the image. Therefore, TSTP is introduced to mitigate the problem induced by the image included in the cost function. TSTP consists of two stages of optimization. The stability of the UAV, and the relative distance between the target and the UAV on the horizontal plane, are optimized in the first stage. The results are used as initial guesses for the second stage to improve optimality. The second stage optimizes the stability of the UAV and the position of the target in the image. Proportional-integral-derivative (PID) controllers are employed to follow the optimized trajectory in both the lateral and longitudinal directions. Our simulation results show stable optimized trajectories, with a stable image and target tracking performance.
机译：我们提出了一种使用单眼视觉的两阶段轨迹规划（TSTP）方法，以保持对目标的连续监视或侦察，以及中继地面车辆和无人机之间的通信。最优轨迹的成本函数包括无人机的高度和速度的变化，以防止突然的机动。图像中目标的位置也包含在成本函数中，以进行连续观察。可以根据无人机的坐标与摄像机的坐标之间的关系来计算虚像。与通用优化问题相比，建议的成本函数受到的影响更大，因为它在图像中具有目标的位置。因此，引入TSTP以减轻由成本函数中包括的图像引起的问题。 TSTP包括两个优化阶段。在第一阶段中优化了无人机的稳定性以及目标和无人机在水平面上的相对距离。结果将用作第二阶段的初始猜测，以提高最佳性。第二阶段优化了无人机的稳定性和目标在图像中的位置。比例积分微分（PID）控制器用于跟踪横向和纵向的优化轨迹。我们的仿真结果显示稳定的优化轨迹，具有稳定的图像和目标跟踪性能。

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