Manipulator Control

Manipulator control research focuses on developing effective and safe methods for controlling robotic arms, aiming to improve their precision, speed, and adaptability in diverse tasks. Current efforts concentrate on advanced control algorithms, including computed torque control and deep reinforcement learning, often integrated with sophisticated interfaces like voice control or human motion imitation for intuitive operation. These advancements are crucial for expanding the capabilities of robots in various fields, from minimally invasive surgery and industrial automation to space exploration and assistive technologies, enhancing efficiency and safety in human-robot collaboration.