Alessio De Luca
Papers
10
Total Citations
73
H-Index
5
About
Alessio De Luca is a roboticist whose work is driving the future of autonomous navigation and human-robot collaboration, particularly for complex, unstructured environments. His research centers on developing advanced planning and control strategies for wheeled-legged robots, enabling them to tackle challenging terrains through innovative techniques like behavior trees and hybrid locomotion planners. De Luca’s contributions are significant: he has pioneered methods for autonomous obstacle crossing and recovery behaviors, allowing robots to navigate cluttered spaces and even recover from blocked scenarios without human intervention. His most cited work, “Autonomous Navigation With Online Replanning and Recovery Behaviors for Wheeled-Legged Robots Using Behavior Trees” (17 citations), exemplifies this impact. Beyond navigation, De Luca has advanced human-robot interaction, designing a unified multimodal interface for high-payload collaborative robots and studying gestural and touchscreen controls. His systematic mapping study on mobile robot exploration strategies (9 citations) provides a critical framework for the field. A notable achievement includes his participation in the euROBIN first-year robotics hackathon, where he contributed to a heterogeneous robot team for door-to-door parcel delivery. With over 70 total citations, De Luca is a rising figure in robotics, pushing the boundaries of what autonomous systems can achieve in the real world.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10