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Towards autonomous tracking and landing on moving target

机译:走向移动目标的自主追踪和降落

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The battery capacity of Unmanned Aerial Vehicle (UAV) is the main limitation, but with the rapid growth of UAV deployment in both military and civilian application, there is an urgent need to development the reliable and automated landing procedure. This paper is aim to propose a basic framework for autonomous landing on moving target for the Vertical Take-off and Landing (VTOL) UAVs. The VTOL vehicle is assumed to equip with a Global Navigation Satellite System (GNSS) system and a stereo vision system which could generate the point cloud within 20 meters. We applied a particle filter based Visual Servo in the UAV vision system to detect and track the moving the target at real time. We also combine the inertial measurement unit (IMU) data with the stereo vision based visual odometry to make the relative accurate pose estimation. The relative position, orientation and velocity to the landing area on the moving carrier is obtained by a modified optical flow method. The control method used in this framework combined tracking and approaching base on the range distance. We has applied our proposed framework on both simulation and landing task on a moving vehicle, and the result shows the efficiency and extended ability of our framework.
机译:无人机(UAV)的电池容量是主要的限制,但随着无人机部署在军事和民用应用的快速增长,迫切需要发展的可靠和自动着陆程序。本文的目的是提出对在垂直起飞和着陆(VTOL)无人机运动目标的自主着陆的基本框架。垂直起降车辆假设与全球导航卫星系统(GNSS)系统和立体视觉系统可能在20米以内生成点云装备。我们在无人机视觉系统所应用的颗粒过滤器的基于视觉伺服检测和跟踪移动实时目标。我们还与立体视觉基于视觉里程相结合的惯性测量单元(IMU)的数据,使相对准确的姿态估计。的相对位置,方位和速度到移动载体上的着陆区域由修改的光流方法获得的。在这个框架中所用的控制方法组合的跟踪和对范围距离接近基地。我们已申请上行驶的车辆模拟和着陆任务我们提出的框架,结果显示的效率和我们的框架的扩展能力。

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