Perception-latency aware distributed target tracking

[摘要] This work is devoted to the problem of distributed target tracking when a team of robots detect the target through a variable perception-latency mechanism. A reference for the robots to track is constructed in terms of a desired formation around the estimation of the target position. However, it is noted that due to the perception-latency, classical estimation techniques have smoothness issues which prevent asymptotic stability for the formation control. We propose a near-optimal smooth-output estimator which circumvents this issue. Moreover, local estimations are fused using novel dynamic consensus techniques. The advantages of the proposal as well as a comparison with a non-smooth optimal alternative are discussed through simulation examples.

[发布日期] 2023-11-01

[关键词] STATE ESTIMATION;NEURAL-NETWORKS;CONSENSUS