C-CBF: Communication-Aware Control Barrier Functions for Resilient Multi-Robot Connectivity

Ensuring resilient operation in networked multi-robot systems is critical when both physical safety and wireless communication are challenged by environmental uncertainty or adversarial interference. This paper presents Communication-Aware Control Barrier Function (C-CBF), a scalable control framework that integrates probabilistic communication constraints into safety-critical control synthesis using Control Barrier Functions (CBFs). By modeling wireless degradation via Rician fading, we formulate a reception-aware constraint that is optimized jointly with inter-agent collision avoidance through local Quadratic Programs (QPs). Each robot computes its control input using only neighbor state information. A decoupled approximation of globally coupled constraints ensures real-time feasibility. Adaptive slack variables enable the system to remain feasible even under conflicting demands, enhancing robustness in complex environments. Simulation results demonstrate that C-CBF ensures safe and connected operation across large-scale, cluttered environments under severe fading conditions. A confidence-tightened variant guarantees forward invariance in probability under channel-model mismatch. This leads to graceful degradation of safety without additional runtime cost. This framework provides a scalable foundation for resilient multi-robot autonomy and can be integrated with distributed optimal control solvers in future work.