On the implementation of area coverage optimization using mobile robots

Consequent to authors' previous work on developing a coverage control algorithm using multiple autonomous agents/robots, this paper focuses on implementing real-time simulations of the previously published coverage control algorithm using differential drive mobile robots. Mobile robots are deployed in a planar area subject to a suitable nonuniform scalar metric. In particular, we deploy multiple P3-DX differential drive mobile robots in a two-dimensional planar workspace to be covered where the non-uniform metric is defined by density function representing scalar measure. A platoon of P3-DX robots is spatially deployed in the workspace in such a way that the area coverage is maximized with respect the scalar field (density). The density in the workspace defines the importance of a point in that workspace. The implementation of the coverage optimization algorithm takes advantage of the Voronoi tessellation technique to partition the workspace. Each robot then moves towards the centroid of the partition (called herein Voronoi cell) it is responsible for. The robots are equipped with multiple sensors. Hence, the objective is to converge a set of P3-DX robots in a workspace such that the coverage is maximized taking into consideration the robots' sensory performance and nonuniform density defined throughout the workspace. The asymptotic convergence is validated by a set of computer simulations using a commercially available robot simulator that mimics a real scenario in an indoor workspace.