Coordinated Unmanned Aerial Vehicles for Surveillance of Targets

Abstract

This thesis investigates the coordination approaches of multiple mobile and autonomous robots, especially resource-limited small-scale UAVs, for the surveillance of pre-de ned ground targets in a given environment. A key research issue in surveillance task is the coordination among the robots to determine the target's time varying locations. The research focuses on two applications of surveillance: (i) cooperative search of stationary targets, and (ii) cooperative observation of moving targets. The objective in cooperative search is to minimize the time and errors in nding the locations of stationary targets. The objective of cooperative observation is to maximize the collective time and quality of observation of moving targets. The thesis presents a survey of the approaches in a larger domain of multi-robot systems for the surveillance of pre-de ned targets in a given environment. This survey identi es various factors and application scenarios that a ect the performance of multi-robot surveillance systems. The thesis proposes a distributed strategy for merging delayed and incomplete information, which is a result of sensing and communication limitations, collected by di erent UAVs. An analytic derivation of the number of required observations is provided to declare the absence or existence of a target in a region. This number of required observations is integrated into an iterative use of Travelling Salesman Problem (TSP) and Multiple Travelling Salesmen Problem (MTSP) for autonomous path planning of UAVs. Additionally, it performs an exploration of the algorithmic design space and analyzes the e ects of centralized and distributed coordination on the cooperative search of stationary targets in the presence of sensing and communication limitations. The thesis also proposes the application of UAVs for observing multiple moving targets with di erent resolutions. A key contribution is to use the quad-tree data-structure for modelling the environment and movement of UAVs. This modelling has helped in the dynamic sensor placement of UAVs to maximize the observation of the number of moving targets as well as the resolution of observation.