Multi-robot patrolling is the potential application for robotic systems to survey wide areas efficiently without human burdens and mistakes. However, such systems have few examples of real-world applications due to their lack of human predictability. This paper proposes an algorithm: Local Reactive (LR) for multi-robot patrolling to satisfy both needs: (i)patrol efficiently and (ii)provide humans with better situation awareness to enhance system predictability. Each robot operating according to the proposed algorithm selects its patrol target from the local areas around the robot's current location by two requirements: (i)patrol location with greater need, (ii)report its achievements to the base station. The algorithm is distributed and coordinates the robots without centralized control by sharing their patrol achievements and degree of need to report to the base station. The proposed algorithm performed better than existing algorithms in both patrolling and the base station's situation awareness.

翻译：多机器人巡逻是机器人系统在广阔区域中高效执行监视任务、减少人为负担与错误的潜在应用。然而，由于缺乏人类可预测性，此类系统在现实世界中的应用实例较少。本文提出一种名为局部反应式（Local Reactive, LR）的多机器人巡逻算法，旨在同时满足两个需求：（i）高效巡逻，（ii）为人类提供更好的态势感知以增强系统可预测性。根据所提算法运行的每个机器人，通过两个条件从当前位置周围的局部区域中选择巡逻目标：（i）选择需求度更高的巡逻位置，（ii）向基站报告其任务完成情况。该算法采用分布式架构，通过共享巡逻完成程度及向基站报告的需求度，无需集中控制即可协调机器人。实验表明，所提算法在巡逻效率与基站态势感知方面均优于现有算法。