An efficient reduction of IMU drift for registration error free augmented reality maintenance application

Abstract

Augmented reality (AR) is a technology that overlays virtual 3D content in the real world to enhance a user’s perception. This AR virtual content must be registered properly with less jitter, drift or lag to create a more immersive feeling for the user. The object pose can be determined using different pose estimation techniques using the data from sensors cameras and inertial measurement units (IMUs). Camera based vision algorithms detect the features in a given environment to calculate the relative pose of an object with respect to the camera. However, these algorithms often take a longer time to calculate the pose and can only operate at lower rates. On the other hand, an IMU can provide fast data rates from which an absolute pose can be determined with fewer calculations. This pose is usually subjected to drift which leads to registration errors. The IMU drift can be substantially reduced by fusing periodic pose updates from a vision algorithm. This work investigates various factors that affect the rendering registration error and to find the trade-off between the vision algorithm pose update rate and the IMU drift to efficiently reduce this registration error. The experimental evaluation details the impact of IMU drift with different vision algorithm pose update rates. The results show that the careful selection of vision algorithm pose updates not only reduces IMU drift but also reduces the registration error. Furthermore, this reduces the computation required for processing the vision algorithm.