Eye in Hand

Eye-in-hand robotics focuses on calibrating the precise spatial relationship between a robot's end-effector and a camera mounted on it, enabling accurate visual feedback for tasks like grasping and manipulation. Current research emphasizes developing robust and efficient calibration methods, often employing 3D vision, structure-from-motion techniques, or learning-based approaches to eliminate the need for external markers or manual calibration. These advancements are crucial for improving the accuracy and autonomy of robots in various applications, including manufacturing, autonomous vehicles, and minimally invasive surgery, by enabling more precise and adaptable control.