A communication model to decouple the path planning and connectivity optimization and support cooperative sensing

When multiple mobile robots (e.g., robotic equipment and unmanned aerial vehicles (UAVs)) are deployed to work cooperatively, it is usually difficult to jointly optimize the algorithms involving the following two aspects: finding optimal paths and maintaining reliable network connectivity. This is due to the fact that both these objectives require the manipulation of sensors' physical locations. We introduce a new relay-assisted communication model to decouple these two aspects so that each one can be optimized independently. However, using additional relay nodes is at the expense of an increased number of transmissions and reduced spectrum efficiency. Theoretical results based on mutual information and average data rate of the model reveal that such drawbacks can be compensated if the sensor nodes are carefully arranged into groups. Based on these results, we further propose a pairing strategy to maximize the spectrum efficiency gain. Simulation experiments have confirmed the performance of this strategy in terms of improved efficiency. We provide a simple example to demonstrate the application of this model in cooperative sensing scenarios where multiple UAVs are deployed to explore an unknown area.