3 papers
cs.RO2026
Micro Neural Policies for Safe Real-Time Robotic Control
Hongpeng Cao, Riccardo Curcio, Daniele Ottaviano +1
In this paper, we investigate the synthesis of Micro Neural Policies (MNP) to enable safe and robust real-time robotic control on computationally constrained embedded devices. We d…
cs.RO2026
Safe and Robust Neural Policy Learning with Statistical Verification for Sim-to-Real Deployment in Robotics
Riccardo Curcio, Hongpeng Cao, Marco Caccamo
Synthesizing safe and robust neural controllers in simulation for reliable sim-to-real deployment remains a critical challenge in robotics. Existing learning-based methods typicall…
cs.AI2026
SMC-ES: Automated synthesis of formally verified control policies
Riccardo Curcio, Toni Mancini, Enrico Tronci
The deployment of autonomous cyber-physical systems in safety-critical environments requires closed-loop control strategies (i.e., policies) that are not only performant but also p…