A decentralized multi-robot system for intruder detection in security defense

In security defense tasks, multiple robots need work cooperatively to detect offensive intrusion to protect some sensitive areas. In this paper, we propose a distributed algorithm for a multi-robot system with some static sensors. The system concept is that static sensors sense intrusions and act as a cueing sensor to an ensemble of robots. These robots in turn engage the potential intruder, performing surveillance and/or neutralization of the intrusion. To minimize the intruder missing rate and average response time, a STAGS (Shame-level Task Allocation and Gap-based Self-deployment) method is proposed, which is a decentralized method without a central control unit. To further improve the system adaptability under dynamic environments, a multi-objective optimization (MOO) method is proposed to adjust the system parameters of STAGS. Extensive simulation results demonstrate the effectiveness and robustness of the proposed algorithm in a dynamic intruder detection task.