2022/11/26 by Ronghe Jin, Yan Wang, Jin, Ronghe +9
Computer Science · Earth and Planetary Sciences · Engineering · #3D Surveying and Cultural Heritage #FOS: Computer and information sciences #Robotic Path Planning Algorithms #Robotics (cs.RO) #Robotics and Sensor-Based Localization
paper · pdf · doi:10.48550/arxiv.2211.14478
openalex publication_date 2022/11/26 · openalex created_date 2022/12/10 · openalex updated_date 2026/07/28
Visual-Inertial Odometry (VIO) usually suffers from drifting over long-time runs, the accuracy is easily affected by dynamic objects. We propose DynaVIG, a navigation and object tracking system based on the integration of Monocular Vision, Inertial Navigation System (INS), and Global Navigation Satellite System (GNSS). Our system aims to provide an accurate global estimation of the navigation states and object poses for the automated ground vehicle (AGV) in dynamic scenes. Due to the scale ambiguity of the object, a prior height model is proposed to initialize the object pose, and the scale is continuously estimated with the aid of GNSS and INS. To precisely track the object with complex moving, we establish an accurate dynamics model according to its motion state. Then the multi-sensor observations are optimized in a unified framework. Experiments on the KITTI dataset demonstrate that the multisensor fusion can effectively improve the accuracy of navigation and object tracking, compared to state-of-the-art methods. In addition, the proposed system achieves good estimation of the objects that change speed or direction.