On March 5h, the HUCEBOT team will have the pleasure of welcoming Marco Ferro, postdoctoral fellow at Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA) in Rennes.
Talk Title:
Control and Estimation in Safety-Critical Robotics: From Perception-Driven Strategies to Optimal Shared Autonomy
Bio:
Marco Ferro is a postdoctoral researcher at the Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA) in Rennes, France. His current research focuses on optimization-based shared autonomy and haptic control strategies for magnetically actuated small-scale robotic systems, with applications in medical robotics and micromanipulation. He received his Ph.D. in Automation, Bioengineering and Operational Research from Sapienza University of Rome in 2019, where he later continued as a postdoctoral researcher at the Department of Computer, Control, and Management Engineering (DIAG). His research trajectory has centered on control and estimation for safety-critical robotic systems, spanning perception-driven navigation in mobile robotics, interaction-aware force estimation in medical procedures, and the development of dynamic simulators and technological demonstrators. In parallel with his research activities, he has contributed to teaching in Master-level robotics and automation courses as a tutor and teaching assistant, and he has supervised several Master and PhD students. He also has served for three years as Associate Editor for ICRA and IROS conferences.
Abstract:
Ensuring safety in robotic systems operating under uncertainty and human interaction is a recurring challenge across multiple application domains. This seminar presents a research trajectory structured around three complementary sources of safety complexity: limited perception and actuation knowledge, critical physical interaction, and shared control authority.
The first part discusses safety under perception and actuation constraints, presenting vision-based navigation strategies that enforce safe motion directly from onboard sensing while accounting for uncertainty.
The second part addresses safety during physical interaction, introducing estimation and force decomposition techniques for needle–tissue procedures, where detecting and rendering critical events enhances operator awareness and risk mitigation.
Then, the core of the presentation focuses on optimization-based shared autonomy frameworks that formally integrate stability, safety constraints, and human commands within a unified control formulation. By leveraging Quadratic Programming approaches combining Control Lyapunov and Control Barrier Functions, these methods provide formal safety guarantees while preserving effective human intervention. Microrobotic systems are shown here as a demanding application domain, where severe actuation limits and multi-agent interactions stress-test the proposed framework.
Moving from perception-driven control to interaction-aware estimation and ultimately to constraint-based shared autonomy, these contributions illustrate a progressive formalization of safety in robotic systems, outlining a coherent direction toward human-centered robotic systems with provable safety properties.
