Real-time route planning algorithm for unmanned aerial vehicles: an approach for beyond 5G smart cities

• Grant number: 24/03016-0
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: May 01, 2024
• End date: July 31, 2027
• Field of knowledge: Engineering - Electrical Engineering - Telecommunications
• Principal Investigator: Christian Rodolfo Esteve Rothenberg
• Grantee: Mauricio Javier Rodriguez Cesen
• Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Company: Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação (FEEC)
• Associated research grant: 21/00199-8 - SMART NEtworks and ServiceS for 2030 (SMARTNESS), AP.PCPE
• Associated scholarship(s): 25/09908-2 - Design and evaluation of AI/ML algorithms for multi-drone air traffic management under dynamic, close-to-reality scenarios, BE.EP.DR

Abstract

The rapid commercialization of Unmanned Aerial Vehicles (UAVs) in key sectors such as transportation and logistics has resulted in a highly competitive market. In future smart cities, multiple UAVs will operate across limited airspace bringing with them multiple challenges related to aerial traffic management, UAV navigation safety, regulatory compliance, and energy efficiency, among others. Although several companies such as Google and Amazon are developing various proposals for package delivery services using UAVs, scalability and energy efficiency in autonomous route planning remains a major challenge. This research proposal focuses on the development of an algorithm for dynamic drone route planning in smart cities, addressing issues such as scalability, energy efficiency, and resource optimization within realistic and complex scenarios including emergency situations, weather considerations, real-time changes in flight zones, and regulatory compliance. The research objective is to design an intelligent and energy-efficient algorithm for dynamic drone route planning using Artificial Intelligence (AI)-based techniques, which ensures reliability and adaptability in future smart cities connected by 5G (and beyond) networks. This proposal outlines the research objectives, methodology, and possible research plan for each research question. (AU)