Max Robotics — Global Service Robot Directory + US Certification

About

Marios Avgeris is a researcher specializing in edge computing, edge robotics, and intelligent resource management for autonomous systems, with a particular focus on bridging the gap between computational constraints and real-time performance in Industry 4.0 environments. His work addresses one of the most pressing challenges in modern robotics: enabling resource-constrained mobile robots to execute complex, time-critical tasks by leveraging edge computing infrastructures for computational offloading. Among his most notable contributions is the development of switching offloading mechanisms for robotic path planning and localization, which has garnered 14 citations, alongside a set-based approach for resource-aware estimation and control in edge robotics with 12 citations. His 2019 work on single vision-based self-localization demonstrated practical, landmark-assisted positioning methods for autonomous agents in indoor environments. More recently, Avgeris has explored deep reinforcement learning for trajectory planning and sensor scheduling, reflecting his commitment to adaptive, intelligent solutions. His research also extends to 5G network slicing orchestration for collaborative edge robotics, underscoring his interdisciplinary reach. Collectively, his contributions have meaningfully advanced the deployment of intelligent robotic systems in real-world industrial settings.