Robotic Manipulator

Robotic manipulators are multi-jointed robotic arms designed to perform a wide variety of tasks, with current research focusing on improving their robustness, adaptability, and ease of programming. Key areas of investigation include enhancing manipulator resilience to joint failures using reinforcement learning and other AI-driven methods, developing more efficient and robust control algorithms (e.g., adaptive control, model predictive control), and improving human-robot interaction through intuitive interfaces and learning from demonstration techniques. These advancements are crucial for expanding the capabilities of robotic manipulators in manufacturing, healthcare, and other fields requiring precise and adaptable automation.