Mobile robots should possess accurate self-localization capabilities in order to be successfully deployed in their environment. A solution to this challenge may be derived from visual odometry (VO), which is responsible for estimating the robot's pose by analysing a sequence of images. The present paper proposes an accurate, computationally-efficient VO algorithm relying solely on stereo vision images as inputs. The contribution of this work is twofold. Firstly, it suggests a non-iterative outlier detection technique capable of efficiently discarding the outliers of matched features. Secondly, it introduces a hierarchical motion estimation approach that produces refinements to the global position and orientation for each successive step. Moreover, for each subordinate module of the proposed VO algorithm, custom non-iterative solutions have been adopted. The accuracy of the proposed system has been evaluated and compared with competent VO methods along DGPS-assessed benchmark routes. Experimental results of relevance to rough terrain routes, including both simulated and real outdoors data, exhibit remarkable accuracy, with positioning errors lower than 2%.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Stereo-Based Visual Odometry for Autonomous Robot Navigation


    Beteiligte:

    Erscheinungsdatum :

    2016-02-10


    Anmerkungen:

    Kostavelis , I , Boukas , E , Nalpantidis , L & Gasteratos , A 2016 , ' Stereo-Based Visual Odometry for Autonomous Robot Navigation ' , International Journal of Advanced Robotic Systems , vol. 13 , no. 1 , 21 . https://doi.org/10.5772/62099



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



    AUTONOMOUS NAVIGATION USING VISUAL ODOMETRY

    LIAO MIAO / LI MING / HONG SOONHAC | Europäisches Patentamt | 2017

    Freier Zugriff

    Visual Odometry for Autonomous Deep-Space Navigation

    Robinson, Shane / Pedrotty, Sam | NTRS | 2016


    Stereo Visual Inertial Odometry for Unmanned Aerial Vehicle Autonomous Flight

    Liu, Quanpan / Wang, Zhengjie / Wang, Huan | Springer Verlag | 2019


    Stereo Visual Inertial Odometry for Unmanned Aerial Vehicle Autonomous Flight

    Liu, Quanpan / Wang, Zhengjie / Wang, Huan | British Library Conference Proceedings | 2020


    Enabling continuous planetary rover navigation through FPGA stereo and visual odometry

    Howard, Thomas M. / Morfopoulos, Arin / Morrison, Jack et al. | IEEE | 2012