Luciano Prono
Papers
3
Total Citations
31
H-Index
2
About
Luciano Prono is a robotics researcher at the forefront of neuromorphic computing and event-based vision. His work centers on developing biologically inspired perception and control systems for mobile and manipulator robots. Prono’s major contribution is the creation of **PEDRo**, a pioneering event-based dataset for person detection in robotics, which has garnered 24 citations since 2023. This dataset addresses the critical need for high-speed, low-latency, and low-power perception using neuromorphic sensors, enabling robots to monitor dynamic environments more efficiently than traditional frame-based cameras. In parallel, Prono has advanced adaptive robotic control by implementing **spiking recurrent neural networks (SNNs)** on digital accelerators. His 2024 paper on this topic (5 citations) demonstrates how simplified neuron models can drastically reduce the computational footprint for learning and inference in resource-constrained tasks. By bridging event-based sensing with SNN-based control, Prono is paving the way for a new generation of energy-efficient, autonomous robots capable of real-time interaction with their surroundings.
Research Focus
Key Achievements
Top Papers
- 1PEDRo: an Event-based Dataset for Person Detection in Robotics24 citations · 2023
- 2
- 3