Braking Control

Braking control research focuses on optimizing braking systems for various applications, from autonomous vehicles and electric aircraft to robotic arms and even insect-computer hybrid robots. Current efforts concentrate on developing accurate predictive models, often employing neural networks (including variations like Normalizing Flows and MobileNet SSD) and advanced control algorithms (e.g., model predictive control) to achieve efficient, safe, and energy-conscious braking under diverse conditions, including non-planar roads and varying tire-road friction. These advancements are crucial for enhancing safety, efficiency, and performance in numerous domains, ranging from improving autonomous driving systems to optimizing energy consumption in electric vehicles.