Fault-Tolerant Framework for Dynamic Task Reassignment in Multi-Robot Systems

Multi-robot systems have become integral to a wide range of practical applications, requiring efficient and reliable task allocation to maintain operational performance, particularly in dynamic and unpredictable environments such as disaster response, industrial automation, and autonomous exploration. However, unforeseen task failures due to robot malfunctions or communication breakdowns significantly impact system stability and efficiency. Therefore, we developed a fault-tolerant framework for dynamic task reassignment to ensure minimal disruption in multi-robot operations. System resilience is enhanced by integrating real-time failure detection with an adaptive task reallocation mechanism. The developed framework employs a recovery-driven task reassignment algorithm that redistributes failed tasks among available robots using robust coordination mechanisms and adaptive scheduling strategies. Communication between robots and the central coordination system is facilitated using the message queuing telemetry transport protocol, which offers a lightweight and efficient publish–subscribe communication model optimized for real-time data exchange that ensures low-latency and energy-efficient messaging in constrained environments. Additionally, the framework incorporates actuator redundancy and adaptive control allocation to recover from partial hardware failures without reassigning tasks. Simulations were conducted to evaluate the model’s performance in handling mid-task failures under varying operational conditions. Experimental results indicate that the framework significantly reduces downtime, improves task completion rates, and enhances overall system resilience and highlighting the framework’s potential for deployment in critical real-world applications, such as disaster response, industrial automation, and autonomous exploration, where reliability and adaptability are essential.