Sensor Synchronization for Android Phone Tightly-Coupled Visual-Inertial SLAM

At present, the majority of Android phones only support satellite positioning and cellular localization. Both of them are of poor indoor performance, which limits the development of the relevant indoor location based services. In this paper, we attempt to achieve positioning with raw image and Inertial Measurement Unit (IMU) data from Android phone. We first introduce a state-of-the-art framework for tightly-coupled monocular visual-inertial Simultaneous Localization and Mapping (SLAM) using image and IMU data. Then we focus on the unsynchronization problem between camera and IMU of Android phone, and propose a grid search algorithm based on spherical quaternion interpolation for delay estimation. The results of indoor and outdoor experiments show that the algorithm can estimate the delay of image timestamp effectively, and the percentage of positioning plane error is 0.79% indoors and 8.09% outdoors respectively.