Reducing the number of mobile sensors for coverage tasks

Abstract

Mobile robots provide new opportunities for research in environment sensing. By combining sensors and robots, we can develop applications to enhance security, search and rescue, and detect hazardous materials. One important problem is to use fewer mobile sensors to cover an area. This paper focuses on two problems in robot sensor deployment: speed management and detouring distance under energy and timing constraints. We determine the robots' traveling speed based on the remaining energy and remaining time before deadline. We use probabilistic models for environments with obstacles and propose an empirical analysis to estimate the extra traveling distance due to detouring. We compute the number of robots (fleet size) needed for cover an area and our approach reduces the fleet size. Compared with two simple heuristics, our method uses 21% fewer robots.