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Motion-Communication Co-Optimization With Cooperative Load Transfer in Mobile Robotics: An Optimal Control Perspective

This paper considers the co-optimization of motion and communication in mobile robotic networks operating under energy constraints. More specifically, we consider a team of robots tasked with collectively transmitting a given amount of data to a remote station, while operating in realistic communication environments that experience path loss, shadowing, and multipath fading. We are interested in designing the load distribution, paths, and transmission power/rate schedules of the robots in a way that minimizes the total energy required for motion and communication. We use realistic models to quantify the motion and transmission power. We then show how this multiagent problem can be efficiently solved using an optimal control framework and mathematically characterize properties of the optimal solution. We further extend the problem to an online adaptation setting, where the robots need to keep adjusting their communication and motion decisions (e.g., paths, loads to transfer, and transmission rates/power) as more information on the channel quality becomes available during the operation. We show how this problem can be effectively solved in a distributed manner and prove that this online distributed approach provides performance guarantees. Extensive simulations with real channel parameters demonstrate the efficacy of the proposed approach and validate the theoretical results.