An Augmented Reality-Based Training System for Manual Milling Operations

Abstract

This study created an AR-based training system for manual milling machine operation. Users can operate a full-size virtual milling machine with their natural operating behavior, without additional worn or handheld devices. An Intel RealSense R200 camera was used to get the images and the depth information of the real world scenes. A Leap Motion controller was used to track user’s hand motion. Both Intel RealSense R200 and Leap Motion were mounted on an Oculus Rift head-mounted display so that users can freely walk around in the augmented environment to operate the virtual milling machine. A calibration method was developed to solve the dynamic occlusion problem in real time to increase the realism and immersiveness of the system. The system provided a safe learning-by-doing training environment, which was expected to enhance users’ learning effect and reduce accidents. User test results showed that the system was robust and helpful in improving user learning experience in manual milling machining operation.