Persistent Multi-UAV Surveillance with Data Latency Constraints

Abstract

We discuss surveillance with multiple unmanned aerial vehicles (UAV) that minimize idleness (the time between consecutive visits of sensing locations) and constrain latency (the time between capturing data at a sensing location and its arrival at the base station). This is important in persistent surveillance scenarios where sensing locations should not only be visited periodically, but the captured data also should reach the base station in due time even if the area is larger than the communication range. Our approach employs the concept of minimum-latency paths (MLP) to guarantee that the data reaches the base station within a predefined latency bound. To reach the bound, multiple UAVs cooperatively transport the data in a store-and-forward fashion. Additionally, MLPs specify a lower bound for any latency minimization problem where multiple mobile agents transport data in a store-and-forward fashion. We introduce three variations of a heuristic employing MLPs and compare their performance in a simulation study. The results show that extensions of the simplest of our approaches, where data is transported after each visit of a sensing location, show improved performance and the tradeoff between latency and idleness.

References in corpus (4)

• On cooperative patrolling: optimal trajectories, complexity analysis, and approximation algorithms
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Cited by in corpus (3)

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• Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle
• Distributed Algorithm with Emergent Area Partitioning and Base Station's Situation Awareness for Multi-Robot Patrolling