Diogo Matos
Papers
8
Total Citations
53
H-Index
5
About
Diogo Matos is a robotics and automation researcher whose work centers on multi-robot systems, autonomous mobile robots, and intelligent fleet management for industrial environments. His research addresses one of the most pressing challenges in modern manufacturing: coordinating fleets of mobile robots efficiently to prevent congestion, minimize downtime, and maximize operational flexibility. Matos has made notable contributions through the development and refinement of real-time path planning frameworks, most prominently demonstrated in his highly cited 2024 paper on centralized fleet coordination, which has already garnered 20 citations. His earlier work extending the Timed Enhanced A* algorithm to tolerate communication failures highlights his focus on building robust, fault-resilient systems for real-world deployment. Across his body of work, he has explored heterogeneous robot fleets, simulated annealing-based scheduling, and comparative analyses of AGV and AMR technologies, providing industry practitioners with actionable insights into robot selection and fleet sizing. With over 50 cumulative citations and publications spanning 2021 to 2025, Matos has established himself as a rising voice in Industry 4.0 robotics research. His decision-making frameworks and coordination algorithms offer valuable tools for engineers and researchers navigating the rapidly evolving landscape of intelligent industrial automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Multi AGV Coordination Tolerant to Communication Failures10 citations · 2021
- 3AGVs vs AMRs: A Comparative Study of Fleet Performance and Flexibility6 citations · 2024
- 4Multi-robot Coordination for a Heterogeneous Fleet of Robots6 citations · 2022
- 5Multiple Mobile Robots Scheduling Based on Simulated Annealing Algorithm5 citations · 2021
- 6
- 7Multi AGV Industrial Supervisory System2 citations · 2021
- 8