Summer School on Autonomous Systems

Embodied Intelligence for Safe Autonomous Systems

The Summer School on Autonomous Systems targets doctoral candidates and early-stage researchers in autonomous systems, distributed systems, robotics, artificial intelligence, and cyber-physical systems, providing advanced interdisciplinary training at the intersection of embodied and physical AI, distributed and data-driven intelligence, as well as safety and trustworthiness in autonomous systems. The program is organized around three core themes: (1) enhancing efficiency, sustainability, and safety through trustworthy and explainable AI; (2) enabling the integration of autonomous systems in complex environments; (3) and advancing data-driven and distributed AI approaches for autonomous systems. It addresses the inherently physical nature of autonomy across land systems (intelligent transport and infrastructure), air systems (UAVs and aerial mobility), and space systems (robotics and satellites). A central premise of the Summer School is that autonomy is fundamentally embodied: intelligence arises from the closed-loop interaction between perception, actuation, physical dynamics, and environmental constraints.

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