Distributed Multiple Hypothesis Tracker for Mobile Sensor Networks

Pujie Xin, Philip M. Dames

Abstract: This paper proposes a distributed estimation and control algorithm to allow a team of robots to search for and track an unknown number of targets. The number of targets in the area of interest varies over time as targets enter or leave, and there are many sources of sensing uncertainty, including false positive detections, false negative detections, and measurement noise. The robots use a novel distributed Multiple Hypothesis Tracker (MHT) to estimate both the number of targets and the states of each target. A key contribution is a new data association method that reallocates target tracks across the team. The distributed MHT is compared against another distributed multi-target tracker to test its utility for multi-robot, multi-target tracking.