Max Robotics — Global Service Robot Directory + US Certification

About

Carlos Azevedo is a robotics researcher whose work centers on multi-robot coordination, domestic service robotics, and formal methods for planning under uncertainty. He is a key contributor to the SocRob project, developing autonomous systems for home environments, with notable publications on people perception, following, and pick-and-place tasks. Azevedo has advanced the use of Generalized Stochastic Petri Nets (GSPN) as a software framework for modeling, analyzing, and verifying robot task plans, providing structural and performance metrics that enable systematic design. His research on multi-robot coordination addresses long-horizon tasks with time uncertainty, offering scalable and formal solutions for real-world applications like monitoring and surveillance. Azevedo also contributed to the euROBIN first-year robotics hackathon, demonstrating heterogeneous robot teams for door-to-door parcel delivery. His work on the Petri Net Toolbox for multi-robot planning under uncertainty provides a developer-friendly package integrating modeling, planning, and execution algorithms. With over 19 citations across his most-cited papers, Azevedo’s impact lies in bridging formal verification with practical robotics, and he has been recognized for his role in robot contests as catalysts for advancing robotics science.