  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.
