In this paper, we present a quantitative performance investigation and repeatability assessment of a mobile robotic system for 3D mapping. With the aim of a more efficient and automatic data acquisition process with respect to well-established manual topographic operations, a 3D laser scanner coupled with an inertial measurement unit is installed on a mobile platform and used to perform a high-resolution mapping of the surrounding environment. Point clouds obtained with the use of a mobile robot are compared with those acquired with the device carried manually as well as with a terrestrial laser scanner survey that serves as a ground truth. Experimental results show that both mapping modes provide similar accuracy and repeatability, whereas the robotic system compares favorably with respect to the handheld modality in terms of noise level and point distribution. The outcomes demonstrate the feasibility of the mobile robotic platform as a promising technology for automatic and accurate 3D mapping.


    Access

    Download


    Export, share and cite



    Title :

    Performance Investigation and Repeatability Assessment of a Mobile Robotic System for 3D Mapping



    Publication date :

    2022-01-01



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



    Thermal Mapping - Reliability and Repeatability

    Shao, J. / Lister, P. J. / Hart, G. D. et al. | British Library Conference Proceedings | 1996


    Experimental investigation of spatial repeatability

    O'Connor, T. / O'Brien, E.J. / Jacob, B. | Tema Archive | 2000


    An experimental investigation of spacial repeatability

    OConner,T. / OBrien,E. / Jacob,B. et al. | Automotive engineering | 2000


    Accuracy and Repeatability of Mobile Phone LiDAR Capture

    Miller, Seth Higgins / Hashemian, Alireza / Gillihan, Robert et al. | British Library Conference Proceedings | 2023


    Accuracy and Repeatability of Mobile Phone LiDAR Capture

    Hashemian, Alireza / Gillihan, Robert / Benes, Saylor et al. | SAE Technical Papers | 2023