Joint Control

Joint control research focuses on coordinating multiple degrees of freedom in systems ranging from robotic manipulators and prosthetic limbs to traffic management and UAV networks. Current efforts emphasize developing robust and efficient control strategies, often employing hierarchical control architectures, deep reinforcement learning, and adaptive PID controllers to handle complex dynamics and uncertainties. These advancements are crucial for improving the performance and autonomy of robots, enhancing the effectiveness of assistive technologies, and optimizing resource allocation in various applications. The ultimate goal is to achieve precise, energy-efficient, and adaptable control across diverse systems.