Explore cutting-edge developments in autonomous robotics for dynamic tasks in this Stanford seminar featuring Joel Burdick from Caltech. Delve into innovative projects like SQUID, a self-stabilizing drone, and PARSEC, an aerial manipulator for sensor network deployment. Learn about advanced techniques in fluid-structure interaction modeling using Koopman spectral methods and their integration into real-time nonlinear model predictive control. Discover how risk-aware approaches enhance robot performance in uncertain environments, from terrain analysis in the DARPA Subterranean Challenge to obstacle avoidance using distributionally robust chance constraints. Gain insights into fast online learning of dynamical disturbances through risk surfaces, enabling drones to adapt to wind conditions rapidly. This comprehensive talk covers a wide range of topics, including machine learning in vehicle control, planning under uncertainty, and introspective control, providing a thorough overview of the latest advancements in robotic systems for complex, dynamic environments. Read more