Multi-drone Routing Planning: Reinforcement Learning and Metaheuristics for Dynamic and Combinatorial Optimization

• Grant number: 24/04031-2
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: June 01, 2024
• End date: March 31, 2028
• Field of knowledge: Engineering - Electrical Engineering
• Principal Investigator: Fernando José von Zuben
• Grantee: Danielle Abreu Fortunato
• 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

Abstract

The project will develop real-time solutions for managing the movements of multiple aircrafts under dynamic and uncertain real-world conditions, thus contributing to the conception of collaborative air-traffic management, an important step toward autonomous airports. Among the desirable features that a search strategy should exhibit to deal with autonomous functionalities for unmanned aircraft systems are diversity maintenance, a memory of past solutions, and a multipopulation structure of candidate solutions. Firstly, we will proceed adapting and extending the available metaheuristics for dynamic and combinatorial optimization already conceived by the research team. Subsequently, we are going to explore reinforcement learning strategies, successfully proposed in the literature to deal with dynamic and combinatorial optimization, as a complementary approach. All the environments will be simulated, and the real-time conditions will be specified in conjunction with the Ericsson research team.