概括
本研究提出了一种基于LiDAR的方法,用于估计空间中不合作的目标的相对态度. 这种方法可以准确地估计关键的轨道维修任务的相对位置.
科学领域:
- 机器人和航天器工程 机器人和航天器工程
- 计算机视觉和传感器融合
背景情况:
- 准确的相对态度估计对于在轨维修 (OOS) 任务至关重要.
- 追逐航天器需要精确的相对姿势参数,以与不合作的目标进行近距离作战.
研究的目的:
- 提出一种使用LiDAR的态度估计方案,以获得追逐者和不合作的目标之间的相对态度参数.
- 为了实现有效和准确的相对立场估计,使OOS任务成为可能.
主要方法:
- 使用LiDAR获取非合作目标的3D点云.
- 使用联合最远点抽样和点云特征分析来提取和简化关键点.
- 实施点快特征组图 (FPFH) 和强大的代式最接近点 (ICP) 算法用于点云注册.
- 设计一个扩展卡尔曼波器 (EKF) 框架来更新相对位置,速度,态度和角速度.
主要成果:
- 成功地注册了近距离旋转和转移运动的点云.
- 有效估计目标的运动状态.
- 拟议的态度估计方案的可行性证明.
结论:
- 开发的基于LiDAR的方案为不合作目标的相对态度估计提供了有效的解决方案.
- 这种方法支持用于先进的轨道维修操作所需的精确轨迹规划.
- 过框架确保对目标的动态状态进行可靠的估计.
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