Effective tracking of unknown clustered targets using a distributed team of mobile robots

IF 3.7 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jun Chen, Philip Dames, Shinkyu Park
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引用次数: 0

Abstract

Distributed multi-target tracking is a canonical task for multi-robot systems, encompassing applications from environmental monitoring to disaster response to surveillance. In many situations the unknown distribution of the targets in a search area is non-uniform, e.g., herds of animals moving together. This paper develops a novel distributed multi-robot multi-target tracking algorithm to effectively search for and track clustered targets. There are two key features. First, there are two parallel estimators, one to provide the best guess of the current states of targets and a second to provide a coarse, long-term distribution of clusters. Second, robots use the power diagram to divide the search space between agents in a way that effectively trades off between tracking detected targets within high density areas and searching for other potential targets. Extensive simulation experiments demonstrate the efficacy of the proposed method and show that it outperforms other approaches in tracking accuracy of clustered targets while maintain good performance for uniformly distributed targets.

使用分布式移动机器人团队有效跟踪未知集群目标
分布式多目标跟踪是多机器人系统的典型任务,涵盖了从环境监测到灾难响应再到监视的应用。在许多情况下,未知目标在搜索区域的分布是不均匀的,例如,一群动物一起移动。为了有效地搜索和跟踪聚类目标,提出了一种新的分布式多机器人多目标跟踪算法。有两个关键特性。首先,有两个并行估计器,一个用于提供目标当前状态的最佳猜测,另一个用于提供聚类的粗略长期分布。其次,机器人使用功率图在代理之间划分搜索空间,从而有效地在高密度区域内跟踪检测到的目标和搜索其他潜在目标之间进行权衡。大量的仿真实验证明了该方法的有效性,并表明该方法在对均匀分布目标保持良好跟踪性能的同时,在对聚类目标的跟踪精度方面优于其他方法。
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来源期刊
Autonomous Robots
Autonomous Robots 工程技术-机器人学
CiteScore
7.90
自引率
5.70%
发文量
46
审稿时长
3 months
期刊介绍: Autonomous Robots reports on the theory and applications of robotic systems capable of some degree of self-sufficiency. It features papers that include performance data on actual robots in the real world. Coverage includes: control of autonomous robots · real-time vision · autonomous wheeled and tracked vehicles · legged vehicles · computational architectures for autonomous systems · distributed architectures for learning, control and adaptation · studies of autonomous robot systems · sensor fusion · theory of autonomous systems · terrain mapping and recognition · self-calibration and self-repair for robots · self-reproducing intelligent structures · genetic algorithms as models for robot development. The focus is on the ability to move and be self-sufficient, not on whether the system is an imitation of biology. Of course, biological models for robotic systems are of major interest to the journal since living systems are prototypes for autonomous behavior.
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