Towards Sensor Based Coverage with Robot Teams

We introduce a new algorithm to cover an unknown space with a homogeneous team of circular mobile robots. Our approach is based on a single robot coverage algorithm, a boustrophedon approach, which divides the target two-dimensional space into regions called cells, each of which can be covered with simple back and forth motions. Single robot coverage is then achieved by ensuring that the robot visits each cell. The new multi-robot coverage algorithm uses the same planar cell-based approach as the single robot approach, but also prescribes the methods by which multiple robots cover a cell, teams are allocated among cells, and sub-teams of robots share information in a minimalistic manner. The advantage of this method is that planning occurs in a two dimensional configuration space for a team of n robots, bypassing the need to plan in a 2n dimensional configuration space. The approach is semi-decentralized: robot teams cover the space independent of each other, but robots within a team communicate state and share information. K e y w o r d s : Multi-robot, Distributed Coverage, Sensor Based Planning 1 I n t r o d u c t i o n Coverage planning for a mobile robot deals with the problem of ensuring that the robot's footprint passes over all reachable points in its target environment. In this paper, we describe an algorithm that directs a team of robots to cover an unknown space solely relying on sensor data acquired on-line. Previous sensorbased work on coverage planning relied on randomized and heuristic algorithms that equipped the robot with a set of behaviors (like avoid obstacle, forage and follow waU)[3] which cooperate to a t tempt to cover a target region. Unfortunately, such approaches do not posses any guarantees that the target space can be exhaustively covered. Therefore, we have developed a multi-robot coverage strategy that is complete, one that possesses provable guarantees which ensures that the robot team passes over all points in a target space. Complete approaches have the advantage of removing any doubt that the robot has successfully covered its environment. The use of multiple robots can expedite the coverage mission and thus improve our measure of eft/ciency of the operation, which we measure in terms of area covered in unit time. Guaranteeing the most efficient coverage is impossible because the robots have no prior knowledge of the workspaceit is always possible to deploy antagonistic obstacles and lead them astray. However, we prescribe our algorithm to minimize repeat coverage which we define as the robot passing over already covered space. The approach in this paper is based on prior single robot coverage methods. To obtain provable completeness, most complete single robot coverage planners, either explicitly or implicitly, use a cellular decomposition of the environment to achieve coverage. A cellular decomposition breaks down the target region into cells such that coverage within each cell is simple. Provably complete coverage is then attained by ensuring that the robot visits each cell. Essentially, this paper presents an adaptation of the single robot cellular decomposition approach for multiple robots. We describe a a semi-decentralized sensor based approach to multi-robot coverage which simultaneously covers an unknown space and construct a cellular decomposition, which in turn is used to guarantee complete coverage. A robot team moves in formation to coverage cell. As cells are created and/or completed, team then splits up into smaller teams, each of which continues coverage. Each robot has a knowledge of its position and heading with respect to a global coordinate frame. Communication is restricted to members of a team members communicate to maintain formation and to update their knowledge of the world. We also provide heuristics for different robot teams to merge when they encounter each other.