DynaVIG: Monocular Vision/INS/GNSS Integrated Navigation and Object Tracking for AGV in Dynamic Scenes

TL;DR

DynaVIG is a multi-sensor system integrating monocular vision, INS, and GNSS to improve navigation and object tracking accuracy for autonomous ground vehicles in dynamic environments, addressing long-term drift and dynamic object challenges.

Contribution

The paper introduces DynaVIG, a novel integrated system that combines monocular vision, INS, and GNSS with a scale estimation method for accurate navigation and object tracking in dynamic scenes.

Findings

Enhanced accuracy of navigation and object tracking on KITTI dataset

Effective handling of objects with changing speed or direction

Improved long-term stability over traditional VIO systems

Abstract

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.