Exact motion estimation is a major task in autonomous navigation. The integration of Inertial Navigation Systems (INS) and the Global Positioning System (GPS) can provide accurate location estimation, but cannot be used in a GPS denied environment. In this paper, we present a tight approach to integrate a stereo camera and low-cost inertial sensor. This approach takes advantage of the inertial sensor's fast response and visual sensor's slow drift. In contrast to previous approaches, features both near and far from the camera are simultaneously taken into consideration in the visual-inertial approach. The near features are parameterised in three dimensional (3D) Cartesian points which provide range and heading information, whereas the far features are initialised in Inverse Depth (ID) points which provide bearing information. In addition, the inertial sensor biases and a stationary alignment are taken into account. The algorithm employs an Iterative Extended Kalman Filter (IEKF) to estimate the motion of the system, the biases of the inertial sensors and the tracked features over time. An outdoor experiment is presented to validate the proposed algorithm and its accuracy.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Fusing Stereo Camera and Low-Cost Inertial Measurement Unit for Autonomous Navigation in a Tightly-Coupled Approach



    Published in:

    The journal of navigation ; 68 , 3 ; 434-452


    Publication date :

    2015




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    53.84 Ortungstechnik, Radartechnik / 55.44 Schiffsführung / 53.84 / 42.89 / 55.20 / 55.44 / 55.86 / 55.54 / 55.86 Schiffsverkehr, Schifffahrt / 55.20 Straßenfahrzeugtechnik / 42.89 Zoologie: Sonstiges / 55.54 Flugführung
    Local classification TIB:    275/5680/7035



    Tightly Coupled Stereo Vision Aided Inertial Navigation Using Continuously Tracked Features for Land Vehicles

    Liu, Fei / Sarvrood, Yashar Balazadegan / Gao, Yang | British Library Conference Proceedings | 2015



    Visual-Inertial Tightly Coupled Fusion and Nonlinear Optimization for UAVs Navigation

    You, Zhenxing / Cai, Zhihao / Zhao, Jiang et al. | British Library Conference Proceedings | 2018



    FUSING LOW-COST IMAGE AND INERTIAL SENSORS FOR PASSIVE NAVIGATION

    Veth, M. / Raquet, J. | British Library Online Contents | 2007