Visual Camouflage and Online Trajectory Planning for Unmanned Aerial Vehicle-Based Disguised Video Surveillance: Recent Advances and a Case Study

Abstract

The applications of unmanned aerial vehicle (UAV)-enabled visual monitoring span the areas of public security, nature resilience, and disaster rescue. Covertness can play an indispensable role in applications demanding UAVs to be unnoticeable by targets, e.g., tailing and interception and police surveillance. This article discusses the types and technical challenges of visual camouflage for UAV-based surveillance. A particular interest is given to an agile disguising method, which adopts both distance keeping and elevation changing and confuses the target by constantly changing its relative position in the target’s view. The path design of the UAV monitor is nonstraightforward under this disguising approach due to nonconvex disguise objectives, UAV propulsion power, and control dynamics. A new control framework is presented to plan and refine the trajectory of the UAV monitor online. The framework employs model predictive control (MPC) to decompose the control decisions between slots, mitigating the impact of the inaccurate prediction of the target’s path and allowing the planned trajectory to be refined online. Simulations validate the merits of the new framework over the benchmark approach with no camouflage and demonstrate the different performances of fixed-wing and rotary-wing UAVs on a covert video surveillance mission.