Three-dimensional risk-aware path planning for unmanned aerial vehicles in urban environments
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/334012
Correu electrònic de l'autorkighdoggmail.com
Tipus de documentTreball Final de Grau
Data2020-11-17
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
:
Reconeixement 3.0 Espanya
Abstract
Context: The use of unmanned aerial vehicles (more popularly known as drones) has experienced a fast growth in the last two decades, especially over urban areas. This led to important safety concerns and thus to the development of a body of astringent regulations aimed to minimize eventual hazards. For this reason, the drone industry must develop suitable strategies to take full advantage of the use of drones, while simultaneously meeting safety and legal requirements. Goals: In line with the former concerns and opportunities, this work focuses on the development of an efficient risk-aware path planning for Unmanned Aerial Systems (UAS) in urban environments. Methods: We use a well-known open-source robotics middleware Robot Operating System (ROS), together with The Open Motion Planning Library, which allow to solve a wide range of complex motion planning problems. Specifically, our proposed strategy is based on the Rapidly-Exploring Random Tree ¿Star¿ algorithm, which allows rapid and efficient exploration of the different paths and, ultimately, convergence to an optimal solution. Our work is actually a 3-dimensional extension of 2-dimension risk-based path planner developed at the Politecnico di Torino. This extension, and some additional optimization goals implied structural changes in the original code which had to be carefully implemented and tested. Results: Given a start and a target position, as well as a 2.5-dimensional risk-based map, the path planner is able to find the optimal path while minimizing the effective risk. The 2.5-dimensional risk-based map quantifies the risks of operating UAS eventually affecting the population on the ground (computed at discrete flight altitudes). In addition, it defines no-flight zones and obstacles at the considered flight altitude. Moreover, the originally proposed approach was extended to consider the Quality of Service of the mobile network used to communicate with the aircraft. In this scenario, the path planner performs an optimization to minimize the risk and to guarantee a communication channel with a minimum Quality of Service. Finally, an energy-aware optimization was also carried out for the path planner to be able to seek for less consuming routes. Conclusions: We met our main goal of devising a method for planning simultaneously efficient and safe UAS paths, and extended it by performing an overall tri-objective optimization, seeking for the optimal path in terms of risk, coverage and energy.
TitulacióGRAU EN ENGINYERIA DE SISTEMES AEROESPACIALS/GRAU EN ENGINYERIA DE SISTEMES DE TELECOMUNICACIÓ (Pla 2015)
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
memoria.pdf | 17,68Mb | Visualitza/Obre |