Experimental Validation of Patrolling Strategies in an Automated Surveillance Environment

Abstract The Autonomous Robotic Patrolling and Surveillance environment (AuRoPaS) is a testbed at the Automatic Control Laboratory of ETH Zurich to experimentally validate tracking, observation, and monitoring strategies for security systems. The setup comprises two high performance closed-circuit television (CCTV) cameras and mobile robots to simulate different types of surveillance scenarios. We propose a velocity based model predictive control scheme for the camera movements, which allows us to generate smooth trajectories and acquire stable images from targets. Experimental results demonstrate the successful reference tracking of the camera controller. We illustrate the integration of high level algorithms into the testbed by applying two stochastic patrolling strategies. The patrolling performances are evaluated on a scenario with moving targets visiting prioritized regions.