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Inter-robot communication enables multi-robot systems to coordinate andexecute complex missions efficiently. Thus, maintaining connectivity of thecommunication network between robots is essential for many multi-robot systems.In this paper, we present a trajectory planner for connectivity maintenance ofa multi-robot system. We first define a weighted undirected graph to representthe connectivity of the system. Unlike previous connectivity maintenance works,we explicitly account for robot motion and sensing uncertainties whileformulating the graph edge weights. These uncertainties result in uncertainrobot positions which directly affect the connectivity of the system. Next, thealgebraic connectivity of the weighted undirected graph is maintained above aspecified lower limit using a trajectory planner based on a distributedalternating direction method of multipliers (ADMM) framework. Here we derive anapproximation for the Hessian matrices required within the ADMM optimizationstep to reduce the computational load. Finally, simulation results arepresented to statistically validate the connectivity maintenance of ourtrajectory planner.

Connectivity Maintenance for Multi-Robot Systems Under Motion and Sensing Uncertainties Using Distributed ADMM-based Trajectory Planning