Distributed Connectivity Maintenance and Recovery for Quadrotor Motion Planning

Maintaining connectivity is crucial in many multi-robot applications, yet fragile to obstacles and visual occlusions. We present a real-time distributed framework for multi-robot navigation certified by high-order control barrier functions (HOCBFs) that controls inter-robot proximity to maintain connectivity while avoiding collisions. We incorporate control Lyapunov functions to enable connectivity recovery from initial disconnected configurations and temporary losses, providing robust connectivity during navigation in obstacle-rich environments. Our trajectory generation framework concurrently produces planning and control through a Bezier-parameterized trajectory, which naturally provides smooth curves with arbitrary degree of derivatives. The main contribution is the unified MPC-CLF-CBF framework, a continuous-time trajectory generation and control method for connectivity maintenance and recovery of multi-robot systems. We validate the framework through extensive simulations and a physical experiment with 4 Crazyflie nano-quadrotors.