Tracking Multiple Ground Objects Using a Team of Unmanned Air Vehicles
Tracking Multiple Ground Objects Using a Team of Unmanned Air Vehicles
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DOI：
10.1007/978-3-319-55372-6_12
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Joshua Y. Sakamaki;R. Beard;M. Rice
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文献类型：
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作者：
Joshua Y. Sakamaki;R. Beard;M. Rice
本文提出了一种利用一组无人机系统（UAS）跟踪多个地面目标的系统架构。在体系结构管道中，视频数据由每个UAS处理以检测图像帧中的运动。使用地理定位算法估计检测到的运动的地面位置。随后的数据点由最近引入的递归RANSAC （R-RANSASC）算法进行处理，以产生一组轨道。然后，这些轨迹通过网络进行通信，并且必须估计车辆之间坐标帧中的误差。在轨迹被放置在同一坐标帧后，使用轨迹到轨迹关联算法来确定每个摄像机中的哪些轨迹对应于其他摄像机中的轨迹。然后使用分布式信息过滤器融合相关的音轨。以两个多旋翼跟踪地面行走者的数据为例进行了验证。
This paper proposes a system architecture for tracking multiple ground-based objects using a team of unmanned air systems (UAS). In the architecture pipeline, video data is processed by each UAS to detect motion in the image frame. The ground-based location of the detected motion is estimated using a geolocation algorithm. The subsequent data points are then process by the recently introduced Recursive RANSAC (R-RANSASC) algorithm to produce a set of tracks. These tracks are then communicated over the network and the error in the coordinate frames between vehicles must be estimated. After the tracks have been placed in the same coordinate frame, a track-to-track association algorithm is used to determine which tracks in each camera correspond to tracks in other cameras. Associated tracks are then fused using a distributed information filter. The proposed method is demonstrated on data collected from two multi-rotors tracking a person walking on the ground.