Abstract
In this article, a decentralized planning scheme is proposed to determine simultaneously communication and motion strategies for a team of mobile robots. These robots accomplish a collection of target visiting tasks in a complex environment with optimal energy consumption and guaranteed end-to-end connectivity. Information generated during the team deployment is transmitted to an operation center via a multihop wireless network whose channels are modeled by stochastic variables. For each announced task, mobile robots adopt different roles depending on the task’s nature and the team’s current configuration; then, each robot determines its communication and motion policies by solving a convex optimization problem. Avoiding inter-robot collisions and obstacles is also taken into account. The suggested approach leads to the efficient use of available robots and their energy resources compared to the rival methods in the literature. Effectiveness of the proposed algorithm is illustrated by computer simulations.
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