Max Robotics — Global Service Robot Directory + US Certification

About

Daniel Di Marco is a leading researcher at the intersection of robotics, knowledge representation, and precision agriculture. His most impactful work centers on the RoboEarth project, where he pioneered cloud-enabled, knowledge-based systems that transform simple robots into intelligent, adaptable machines. Di Marco’s major contributions include developing semantic mapping systems that use ontologies to code environmental concepts, creating a globally accessible database for sharing reusable task information, and designing hierarchical action representations that allow service robots to plan and execute complex tasks. His seminal paper, “RoboEarth Semantic Mapping: A Cloud Enabled Knowledge-Based Approach,” has garnered 107 citations, underscoring its foundational role in the field. Beyond service robotics, Di Marco has advanced agricultural robotics through his work on “Cognitive Weeding,” proposing an end-to-end architecture for single-plant specific weed regulation using drones and robots. His research on 3D object modeling and active perception further demonstrates his ability to bridge abstract knowledge with real-world robotic execution. With a portfolio spanning over 150 citations, Di Marco’s work continues to shape how robots perceive, reason, and act in dynamic environments, making him a key figure in both robotic cognition and sustainable farming innovation.