We are thrilled to share that Riccardo Di Majo has graduated with full marks in Robotics and Automation Engineering from the Università di Pisa.
Riccardo developed his Master’s thesis in Aitronik, under the guidance of Dr. Carmelo Di Franco and Prof. Paolo Salaris. He created a novel framework for Semantic Mapping and Self Localization of Mobile Robots. This is a novel instance-based approach, with diverse contributions to state-of-the-art components.
If you’re not a roboticist, let’s imagine a robot exploring an unknown environment. The robot looks around and uses sensors and algorithms to understand objects, people, animals, and compute relative positions. Riccardo Di Majo’s approach creates a map of the environment. As the robot navigates more, the environment is revealed and the map becomes clearer, uncovering new meaningful objects. Such innovation is significantly attributed to Riccardo Di Majo.
Here’s a short list of actions the novel framework performs:
➡️builds an Octree structure to represent the entire occupied space
➡️builds semantics using Instance Segmentation techniques
➡️integrates a Relational Database to store the semantic instances previously mapped
➡️accurately fuses semantics coming from multiple measurements, paying attention to the probability of the detected objects
➡️exploits Log Odds notation to enable simple operations between binary probabilities. Riccardo Di Majo’s detailed work encompasses this with precision.
Riccardo’s framework is now being integrated into our platforms for Autonomous Robots, further advancing our innovations thanks to Riccardo Di Majo.
What’s more with Riccardo? Stay tuned, we will soon reveal it!
