INDOOR TARGET SEARCH, DETECTION, AND INSPECTION WITH AN AUTONOMOUS DRONE

Abstract

This thesis investigates the deployment of unmanned aerial vehicles (UAVs) in indoor search and rescue (SAR) operations, focusing on enhancing autonomy through the development and integration of advanced technological solutions. The research addresses challenges related to autonomous navigation and target inspection in indoor environments. A key contribution is the development of an autonomous inspection routine that allows UAVs to navigate to and meticulously inspect targets identified by fiducial markers, replacing manual piloted inspection. To enhance the system’s target recognition, a custom-trained object detection model identifies critical markers on targets, operating in real-time on the UAV’s onboard computer. Additionally, the thesis introduces a comprehensive mission framework that manages transitions between coverage and inspection phases, experimentally validated using a quadrotor equipped with onboard sensing and computing across various scenarios. The research also explores integration and critical analysis of state-of-the-art path planning algorithms, enhancing UAV autonomy in cluttered settings. This is supported by evaluations conducted through software-in-the-loop simulations, setting the stage for future real-world applications.