Abstract
We consider the scenario where a mobile robot needs to visit a number of points of interest (POIs) in a workspace, gathers its generated bits of information, and successfully transmits them to a remote station, while operating in a realistic communication environment, minimizing its total energy consumption (including both motion and communication costs), and under time and reception quality constraints. We are interested in the co-optimization of the communication and motion strategies of the robot such that it finds the optimal trajectory (the order in which it visits all of the POIs) and optimally co-plans its communication and motion strategies, including motion speed, stop times, communication transmission rate, and power. By co-optimizing the usage of both communication and motion energy costs and using realistic probabilistic link metrics that go beyond the commonly used disk models, we show how the overall problem can be posed as a mixed integer linear program (MILP) and characterize several properties of the co-optimized solution. For instance, we derive conditions under which the optimal trajectory becomes the minimum-length trajectory as well as conditions under which the trajectory deviates from the minimum length one to visit areas with very high connectivity. We further characterize if/when it is beneficial for the robot to incur motion energy to find a better spot for communication. Moreover, we derive conditions that relate the co-optimized communication and motion strategies and clearly show the interplay between the two. Finally, our simulation results with real channel and motion parameters confirm the analysis and show considerable energy savings.
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