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Vision-based guidance and control of a hovering vehicle in unknown, GPS-denied environments

机译:在未知,GPS拒绝的环境中对悬停的车辆进行基于视觉的引导和控制

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This paper describes the system architecture and core algorithms for a quadrotor helicopter that uses vision data to navigate an unknown, indoor, GPS-denied environment. Without external sensing, an estimation system that relies only on integrating inertial data will have rapidly drifting position estimates. Micro aerial vehicles (MAVs) are stringently weight-constrained, leaving little margin for additional sensors beyond the mission payload. The approach taken in this paper is to introduce an architecture that exploits a common mission payload, namely a video camera, as a dual-use sensor to aid in navigation. Several core algorithms, including a fast environment mapper and a novel heuristic for obstacle avoidance, are also presented. Finally, drift-free hover and obstacle avoidance flight tests in a controlled environment are presented and analyzed.
机译:本文介绍了四旋翼直升机的系统架构和核心算法,该直升机使用视觉数据导航未知的室内GPS拒绝的环境。如果没有外部检测,仅依靠整合惯性数据的估计系统将具有快速漂移的位置估计。微型飞行器(MAV)的重量受到严格限制,超出任务有效载荷的额外传感器几乎没有余地。本文采用的方法是介绍一种利用通用任务有效载荷(即摄像机)作为辅助导航的双重用途传感器的体系结构。还提出了几种核心算法,包括快速环境映射器和新颖的启发式避障技术。最后,提出并分析了在受控环境下的无漂移悬停和避障飞行测试。

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