Efficient Rescue for Resilient Multi-Robot Systems against Actuation Attacks

The widespread application of intelligent storage systems has put forward higher requirements for security. In this work, we consider the resilience of multi-robot systems (MRSs) in pickup and delivery tasks against actuation attacks. The attacker can disrupt the normal motion of key robots with an intelligent strategy, and thus jeopardize the cooperation among robots. A three-layered decision framework is proposed to suppress the intelligent attacks. The first layer introduces a defense strategy implemented through a counterfactual rescue mode allocation mechanism. The mechanism dynamically assesses the benefit differences between rescuing others for resilience and conducting self-tasks for efficiency. The second layer employs a bi-level programming method for pickup/delivery mode allocations and task assignments. Then, the third layer calculates the robots’ collision-free path using a mixed integer program. The practicality and resilience of this framework against strategic actuation attacks have been demonstrated through numerical simulations involving various MRS scales and task burdens.