Motion planning for multitarget surveillance with mobile sensor agents

Abstract

In the surveillance of multiple targets by mobile sensor agents (MSAs), system performance relies greatly on the motion-control strategy of the MSAs. This paper investigates the motion-planning problem for a limited resource of M MSAs in an environment of N targets (M<N). The kinematics of the MSA is modeled as a point mass moving at a constant speed with a bounded turning radius. Based on the fact that the track information of each target degrades over time, the motion-planning problem is formulated as an optimization problem whose objective is to minimize the average time duration between two consecutive observations of each target. In the case of a single MSA, the motion-planning problem is further interpreted so as to find a time-optimal loop path to traverse the targets. A gradient-approximation algorithm is then proposed to generate a suboptimal loop path for a mobile agent to traverse a sequence of target points. For the multi-MSA-multitarget case, a cooperative online motion-planning approach is developed.