ConnectivityPreserving Swarm Teleoperation With A Tree Network During swarm teleoperation, the operator may threaten the distancedependent interrobot communications and, with them, the connectivity of the slave swarm. To prevent the operator from disconnecting the swarm, this paper develops a constructive strategy to dynamically modulate the interconnections of, and the local damping injections at, all slave robots. Lyapunovbased set invariance analysis shows that the strategy preserves all interaction links in the tree network while synchronizing the slave swarm. By properly limiting the impact of the user command rather than rejecting it entirely, the proposed explicit gain update law enables the operator to guide the motion of the slave swarm to the extent to which it does not endanger swarm connectivity. An experiment illustrates that the proposed strategy can maintain the tree network connectivity of a teleoperated swarm.

Minimum kConnectivity Maintenance for Robust MultiRobot Systems In many multirobot applications, it is critical to maintain connectivity within the robotic team to allow for information exchange and coordination. While most of the existing works focus on connectivity control that ensures robotic team remain connected as one component without faults, we consider the problem of robust connectivity maintenance that seeks to maintain kconnectivity, such that the multirobot network could stay connected with the removal of fewer than k robots. In this paper, we propose provably minimum kconnectivity maintenance algorithms for multirobot systems. This ensures the robustness of the multirobot network connectivity at all time and also in a flexible and optimal way to provide the highest freedom for robots taskrelated controllers. Particularly, we propose a kConnected Minimum Constraints Subgraph (kCMCS) algorithm that activates the minimum kconnectivity constraints to the original controllers, and then revise the original controllers in a minimally invasive fashion. We demonstrate the effectiveness of our approach via simulations of up to 40 robots in the presence of multiple behaviors.