Dynamic Coverage via Multi-Robot Cooperation

Abstract : The coverage problem in the context of multi-robot teams can be defined as the maximization of the total area covered by the sensors of all robots in the team. Some coverage algorithms cause a robot group to converge to a static configuration, such that every point under the robots' sensor shadow is covered at every instant of time. We term such a coverage task static, since as soon as the desired dispersion is achieved, the system is at equilibrium. For complete static coverage of an environment the robot team should have a certain critical number of robots (depending on environment size, complexity, and robot sensor ranges). Determining the critical number is difficult or impossible if the environment is unknown a priori. In this paper we address the dynamic coverage problem, which requires all areas of free space in the environment to be covered by sensors with as high a frequency as possible, given a fixed number of robots. Our solution to the problem relies on the deployment of beacons (small stationary nodes with radios) into the environment as support infrastructure which the mobile robots use to solve the coverage problem. Robots explore the environment, and based on certain local criteria, drop a beacon into the environment, from time to time. Each beacon is equipped with a small processor and a radio of limited range. The proposed algorithm is decentralized and performs the coverage task successfully using only local sensing and local interactions between the mobile robots and beacons. The mobile robots interact through the environment by deploying the beacons and changing their state when in the communication vicinity of beacons. The fundamental constraint that we impose on the solution is the lack of global information about the environment. We also do not require the robots to be localized. We measure coverage using a frequency coverage metric that measures frequency of every-point coverage over time.