A Robust Localization Approach Using Multi-sensor Fusion

In recent years, with development of computer vision and robotics, a wide variety of localization approaches have been proposed. However, it is still challenging to design a localization algorithm that performs well in both indoor and outdoor environment. In this paper, an algorithm that fuses camera, IMU, GPS, as well as digital compass is proposed to solve this problem. Our algorithm includes two phases: (1) the monocular RGB camera and IMU are fused together as a VIO that estimates the approximate orientation and position; (2) the absolute position and orientation measured by GPS and digital compass are merged with the position and orientation estimated in first phase to get a refined result in the world coordinate. A bag-of-word based algorithm is utilized to realize loop detection and relocalization. We also built a prototype and did two experiments to evaluate the effectiveness and robustness of the localization algorithm in both indoors and outdoors environment.