Manipulator Dynamic

Manipulator dynamics research focuses on accurately modeling and controlling the movement and forces of robotic arms, aiming for precise trajectory tracking and safe interaction with the environment. Current efforts involve developing hybrid models combining physics-based approaches (e.g., Lagrangian mechanics) with data-driven techniques (like XGBoost) to improve accuracy and reduce reliance on precise physical parameters. These advancements enable improved motion planning, sensorless control strategies, and robust impedance control, leading to more efficient and adaptable robots for diverse applications in manufacturing, healthcare, and other fields.