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Komplexní Systém pro Rychlé a Spolehlivé Nasazení Spolupracujících Autonomních Letounů
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Komplexní Systém pro Rychlé a Spolehlivé Nasazení Spolupracujících Autonomních Letounů
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Komplexní Systém pro Rychlé a Spolehlivé Nasazení Spolupracujících Autonomních Letounů
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Dissertation
Komplexní Systém pro Rychlé a Spolehlivé Nasazení Spolupracujících Autonomních Letounů
2021
Overview
In time-sensitive scenarios such as disaster response, first responders face increased technical challenges. These challenges may include rugged terrain, unstable structures, degraded environmental conditions, severe communication constraints, and extensive operation areas. To ensure the safety of human responders, autonomous robots such as Unmanned Aerial Vehicles (UAVs) are well suited for this task. At the beginning of the research for this thesis, the testing standard in the UAV community was to use a simulated environment or to conduct short isolated experiments under laboratory conditions relying on a motion capture system with no external disturbances and a stable communication infrastructure without interference. Compared to these approaches, real-world deployment raises additional constraints and challenges to fundamental research problems. A robotic system for a real-world application requires a reliable high-level planning architecture to recover from robot failures and malfunctions of its system parts. This is essential for the UAV and especially for the multi-UAV systems that are the focus of this thesis. Communication between the robots is required to fully access the capabilities of the deployed multi-robot team. As of today however, the technical requirements for an operational communication infrastructure are still a bottleneck. Therefore, the first part of the thesis is dedicated to developing a novel high-level planning architecture that considers different strategies based on the availability of a communication infrastructure in addition to failures of sensors and actuators. When enabled, this maximizes the contributions and tight cooperation of the multi-robot system. The second part of the thesis focuses on motion planning for multiple cooperating UAVs inspired by three real-world scenarios: autonomous delivery of objects by a team of UAVs, autonomous aerial surveys of building interiors, and autonomous firefighting. The object delivery and firefighting scenarios were motivated by challenges in the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 and 2020.
