Control of Multiple UAVs for Persistent Surveillance: Algorithm and Flight Test Results

TLDR

Interest in multi‑UAV control for persistent surveillance has grown, driven by applications such as weather monitoring, mapping, and exploration, yet continuous coverage demands new strategies that address vehicle dynamics, endurance limits, and stochastic failures. The study aims to develop scalable, reliable, and efficient high‑level control techniques for multi‑UAV persistent surveillance, including dynamic‑constraint‑aware policy modifications and an endurance‑aware health‑monitoring component. These techniques were implemented on Boeing’s Vehicle Swarm Technology Laboratory testbed, where the control policy was adapted to aircraft dynamics and a health‑monitoring module was added, and the system was evaluated in a realistic surveillance scenario. The policies were successfully validated on the VSTL hardware testbed, confirming their feasibility for realistic persistent‑surveillance operations.

Abstract

Interest in control of multiple autonomous vehicles continues to grow for applications such as weather monitoring, geographical mapping fauna surveys, and extra-terrestrial exploration. The task of persistent surveillance is of particular significance in that the target area needs to be continuously surveyed, minimizing the time between visitations to the same region. This distinction from one-time coverage does not allow a straightforward application of most exploration techniques to the problem, though ideas from these methods can still be used. The aerial vehicle dynamic and endurance constraints add additional complexity to the autonomous control problem, whereas stochastic environments and vehicle failures introduce uncertainty. In this work, we investigate techniques for high-level control, that are scalable, reliable, efficient, and robust to problem dynamics. Next, we suggest a modification to the control policy to account for aircraft dynamic constraints. We also devise a health monitoring policy and a control policy modification to improve performance under endurance constraints. The Vehicle Swarm Technology Laboratory-a hardware testbed developed at Boeing Research and Technology, Seattle, WA, for evaluating a swarm of unmanned air vehicles-is then described, and these control policies are tested in a realistic scenario.