Riccardo Franceschini
Papers
2
Total Citations
4
H-Index
2
About
Riccardo Franceschini is a robotics researcher whose work sits at the intersection of autonomous navigation, aerial teleoperation, and human-robot collaboration. His research focuses on two critical challenges: enabling safe, efficient robot navigation in complex environments, and maintaining reliable human oversight for aerial robots performing high-stakes tasks. In his 2022 study on navigation, Franceschini pioneered a method that combines the Rapidly-exploring Random Tree* (RRT*) algorithm with Reinforcement Learning, allowing robots to intelligently exploit cost maps to minimize multiple constraints such as safety risks and battery drain—a significant step toward more adaptive autonomous systems. His 2025 work addresses the equally pressing challenge of aerial teleoperation, where he conducted field experiments comparing video streaming protocols to ensure low-latency, reliable visual feedback for pilots controlling drones during manipulation and inspection tasks. This research is vital for keeping human expertise at the center of decision-making in mission-critical scenarios. With his papers already garnering citations, Franceschini is establishing himself as a thoughtful contributor to the practical deployment of intelligent, human-aware robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2