Distance optimal target assignment in robotic networks under communication and sensing constraints

We study the problem of minimizing the total distance incurred in assigning a group of mobile robots to an equal number of static targets. Assuming that the robots have limited, range-based communication and target-sensing capabilities, we present a necessary and sufficient condition for ensuring distance optimality when robots and targets are uniformly randomly distributed. We then provide an explicit, non-asymptotic formula for computing the number of robots needed for guaranteeing optimality in terms of the robots' sensing and communication capabilities with arbitrarily high probabilities. The bound given in the formula is also asymptotically tight. Due to the large number of robots needed for high-probability optimality guarantee, we continue to investigate strategies for cases in which the number of robots cannot be freely chosen. We show that a properly designed strategy can be asymptotically optimal or suboptimal with constant approximation ratios.