Monocular Feed-forward based 3D Target Aiming Using a 6-DOF Robotic Arm

With the overall development of artificial intelligence technology, the autonomous application of robotic arms has been significantly improved, which places extremely superior requirements on the reliability of algorithms such as target detection and target positioning. In this paper, based on a 6-DOF collaborative manipulator, we propose a 3D target aiming algorithm with high real-time performance through monocular vision feed-forward control. First, we present a coordinate system calibration algorithm to obtain the relative pose relationship between the monocular camera and the laser transmitter. Second, a modified YOLO-v4 algorithm is designed to further improve the speed and accuracy of target detection. Third, we propose a monocular aiming algorithm, which can directly aim at a 3D target based on the target’s 2D pixel deviation. Through experimental verification, the single-frame detection time of our algorithm can be reduced to 14.12 ms, and the response time of monocular aiming algorithm is only 0.61 s.