
Explore challenging robotics problems, including backflips, models, perception, and optimization. Gain insights into reinforcement learning, state estimation, and physics-based approaches for advanced robotic systems.

Exploring cheetah-inspired aerodynamic robot tails and state estimation for hybrid systems, enhancing agility in legged robots and improving control during discontinuous impacts.

Learn about PID controllers: their components, applications, and how they achieve stable control systems. Explore mathematical models and live simulations to understand this powerful algorithm.

Explore cyber-physical security, including system models, attack examples, and modern contexts. Learn about securing critical infrastructure and emerging challenges in networked control systems.

Explore FPV drone flight controllers, IMUs, sensor fusion, control systems, and PID. Learn about digital signal processing, filtering, and firmware for advanced drone piloting.

Polynomial approximation of random PDEs using discrete least squares with random point observations. Explores stability, error bounds, and optimal index set selection for metamodel construction in high-dimensional parameter spaces.

Explore geometric control theory's advanced concepts, focusing on mathematical foundations and practical applications in dynamic systems and optimization.

Explore advanced concepts in geometric control theory, focusing on mathematical principles and applications in dynamic systems and optimization.

Explore advanced concepts in geometric control theory, focusing on mathematical principles and applications in dynamic systems and optimization.

Explore geometric control theory fundamentals with expert Andrei Agrachev, covering key concepts and applications in this comprehensive lecture from ICTP Mathematics.

Explores challenges in merging machine learning with control systems, focusing on autonomous vehicles using vision. Discusses uncertainty quantification, robust controller design, and performance guarantees.

Explore neural reinforcement learning for autonomous control, focusing on data-efficient off-policy learning and effective exploration techniques for complex tasks in simulation and reality.

Explore advanced concepts in tame control theory, focusing on phenomena over real fields. Delve into graduate-level mathematical analysis and applications.

Explore fundamental concepts of tame control theory, focusing on real field applications and advanced mathematical principles in this graduate-level lecture.

Explore finite-sample analysis and insights for learning low-order linear dynamical systems using Hankel nuclear norm regularization, with applications in control and reinforcement learning.

Explore vulnerabilities in drinking water control systems, potential cyber threats, and necessary security measures to protect critical water infrastructure.

Discover how to implement next-generation security by leveraging feedback, pushing security left, and making it consumable. Learn strategies to engage developers and address the challenges of securing complex software workloads.

Pioneering insights into nonlinear systems and oscillatory dynamics, exploring emergent phenomena, synchrony, and chaos. Retrospective on key contributions to the field of coupled oscillators and dynamical reduction.

Explore strategies for assessing and mitigating critical infrastructure vulnerabilities, focusing on novel threats and their potential ecosystem-wide impacts across various sectors.

Explore cascading failures in the U.S.-South Canada power grid, identifying vulnerable components and discussing mitigation strategies for improved grid resilience and renewable energy integration.

Exploring the future of dynamic robots with Marc Raibert, discussing advancements in hardware, control systems, and real-world applications. Includes insights on Boston Dynamics' innovations and a live robot demonstration.