Contact Interaction

Contact interaction research focuses on understanding and controlling the physical contact between robots and their environments, aiming to improve robot dexterity, safety, and efficiency in tasks requiring manipulation and interaction. Current research emphasizes developing robust models and algorithms, such as deep learning-based approaches for human intention recognition and adaptive control, and efficient contact solvers for simulation and control. These advancements are crucial for enabling robots to perform complex tasks in various domains, including manufacturing, healthcare, and human-robot collaboration, by improving both the precision and safety of physical interactions.