A Novel Strategy for Connectivity Maintenance and Recovery in Heterogeneous Multi-Robot Systems

Ensuring connectivity and coordination in heterogeneous multi-robot systems (MRS) navigating complex environments is a critical challenge, especially when communication constraints and obstacles cause robots to become lost or disconnected. This paper presents a novel approach integrating Model Predictive Control (MPC) with Generalized Connectivity Maintenance (GCM) to enable real-time path adaptation while preserving connectivity. We introduce a decentralized decision-making framework that enables robots to recover lost members dynamically. When reconnection is infeasible, the system adapts the mission to continue while accounting for disconnected robots. Our method is evaluated through extensive simulations, showing its scalability and effectiveness in maintaining connectivity and ensuring mission success. Additionally, we propose a new evaluation metric that comprehensively assesses system performance, considering connectivity, coordination, and mission success in challenging environments.