Detecting, localizing, and tracking an unknown number of moving targets using a team of mobile robots
Detecting, localizing, and tracking an unknown number of moving targets using a team of mobile robots
复制标题
使用移动机器人团队检测、定位和跟踪未知数量的移动目标
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Vijay R. Kumar
中科院分区：
文献类型：
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作者：
P. Dames;Pratap Tokekar;Vijay R. Kumar
Target tracking is a fundamental problem in robotics research and has been the subject of detailed studies over the years. In this paper, we generate a data-driven target model from a real-world dataset of taxi motions. This model includes target motion, appearance, and disappearance from the search area. Using this target model, we introduce a new formulation of the mobile target tracking problem based on the mathematical concept of random finite sets. This formulation allows for tracking an unknown and dynamic number of mobile targets with a team of robots. We show how to employ the probability hypothesis density filter to simultaneously estimate the number of targets and their positions. Next, we present a greedy algorithm for assigning trajectories to the robots to allow them to actively track the targets. We prove that the greedy algorithm is a two-approximation for maximizing submodular tracking objective functions. We examine two such functions: the mutual information between the estimated target positions and future measurements from the robots and a new objective that maximizes the expected number of targets detected by the robot team. We provide extensive simulation evaluations to validate the performance of our data-driven motion model and to compare the behavior and tracking performance of robots using our objective functions.
影响因子：
5.4
作者：
Reuter, Stephan;Vo, Ba-Tuong;Dietmayer, Klaus
通讯作者：
Dietmayer, Klaus