Abstract
This paper addresses the coverage control problem in environments where several regions of interest exist. To this purpose, a heterogeneous group of robots are deployed to minimize a cost function defined with respect to various spatial probability density functions, each of which describes a desired area for a different group of robots. Each region of interest is assigned to a group of robots with respect to their dynamics and sensing capabilities. A distributed coverage scheme is proposed to allow adjusting to the environment with several important areas in a collaborative way. The regions with higher importance would be covered with an appropriate number of robots. The proposed method also allows for a better allocation of robots to guarantee the desired coverage over the region. Two numerical examples are finally given to examine the proposed coverage approach in case of multiple regions of interest that may need to be covered by a certain number of robots.
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