A Spatial Pose Measurement Scheme by Using IMU and AprilTag Technologies

In many workspaces, robots need to obtain their own speed and precise pose for motion control, navigation, and interaction with the environment. The inertial measurement unit (IMU) is inaccurate due to its own accumulated error which can obtain spatial information of the six degrees of freedom, but its advantage is that it can obtain real-time spatial information. AprilTags are designed for high localization accuracy and the precise 3D position of the AprilTag with respect to the camera can be computed; due to the slow update rate, its real-time performance is relatively poor. In order to get accurate and real-time spatial pose, an extended Kalman filter is implemented to fuse visual and inertial data, which provides accurate estimates.