The paper “A neuro-inspired control architecture to enhance robot self-preservation and adaptation in autonomous navigation tasks“, published in IEEE Robotics and Automation Letters, by Andrea Usai (Ph.D. student of the Complex Systems Laboratory) and Alessandro Rizzo, has been spotlighted in IEEE Spectrum’s Journal Watch.

The study introduces a bio-inspired control system that mimics the brain’s “low-road” fear response to enable autonomous robots to react rapidly and instinctively to threats in dynamic environments.

The architecture, integrating a reinforcement learning-based amygdala model with nonlinear model predictive control, has been shown to significantly enhance safety and adaptability in obstacle avoidance scenarios compared to conventional approaches.

Lorenzo Calogero, Ph.D. student of the Complex Systems Laboratory, has been recognized as Outstanding Reviewer of 2024 for the IEEE Control Systems Letters (L-CSS).

This recognition is awarded every year to a small, selected group of referees who have stood out with high-quality reviews for papers submitted to the journal, demonstrating a high degree of commitment and a clear evidence of high technical ability in the field of automatic control.