Motion Control

Motion control research aims to develop algorithms and systems enabling robots to execute precise and adaptable movements. Current efforts focus on improving human-robot collaboration through intuitive interfaces and robust control strategies, often employing model predictive control, Gaussian processes, and dynamical systems (including Riemannian and elastic variations) to handle complex tasks and uncertainties, such as disturbances, communication delays, and actuator failures. These advancements are crucial for enhancing the safety and efficiency of robots in industrial settings, autonomous vehicles, and other applications requiring sophisticated motion capabilities.