An adaptive artificial potential function approach for geometric sensing

In this paper, a novel artificial potential function is proposed for planning the path of a robotic sensor in a partially observed environment containing multiple obstacles and multiple targets. The sensor planning problem considered in this paper consists of planning the motion of a robot with an on-board sensor that is deployed in order to support a sensing objective, such as, target detection and classification, by gathering sensor measurements over time. An adaptive potential function approach is presented such that the sensor path accounts for prior information on the target geometry and information profit, by traveling a minimum distance.