This paper proposes an evaluating and mapping methodology of terrain traversability for off-road navigation of autonomous vehicles in unstructured environments. Terrain features are extracted from RGB images and 3D point clouds to create a traversal cost map. The cost map is then employed to plan safe trajectories. Bayesian generalized kernel inference is employed to assess unknown grid attributes due to the sparse raw point cloud data. A Kalman filter also creates density local elevation maps in real time by fusing multiframe information. Consequently, the terrain semantic mapping procedure considers the uncertainty of semantic segmentation and the impact of sensor noise. A Bayesian filter is used to update the surface semantic information in a probabilistic manner. Ultimately, the elevation map is utilized to extract geometric characteristics, which are then integrated with the probabilistic semantic map. This combined map is then used in conjunction with the extended motion primitive planner to plan the most effective trajectory. The experimental results demonstrate that the autonomous vehicles obtain a success rate enhancement ranging from 4.4% to 13.6% and a decrease in trajectory roughness ranging from 5.1% to 35.8% when compared with the most developed outdoor navigation algorithms. Additionally, the autonomous vehicles maintain a terrain surface selection accuracy of over 85% during the navigation process.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Autonomous Vehicles Traversability Mapping Fusing Semantic–Geometric in Off-Road Navigation


    Beteiligte:
    Bo Zhang (Autor:in) / Weili Chen (Autor:in) / Chaoming Xu (Autor:in) / Jinshi Qiu (Autor:in) / Shiyu Chen (Autor:in)


    Erscheinungsdatum :

    2024




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Traversability mapping in off-road environment using semantic segmentation

    Dabbiru, Lalitha / Sharma, Suvash / Goodin, Chris et al. | SPIE | 2021


    Stereo-Based Tree Traversability Analysis for Autonomous Off-Road Navigation

    Huertas, Andres / Matthies, Larry / Rankin, Arturo | IEEE | 2005


    Traversability mapping in off-road environment using semantic segmentation

    Dabbiru, Lalitha / Sharma, Suvash / Goodin, Chris et al. | British Library Conference Proceedings | 2021


    Semantic scene understanding and traversability estimation for off-road vehicles

    Copado Rodríguez, Jesús | BASE | 2021

    Freier Zugriff

    Autonomous Robot Navigation Using Traversability Indices

    Seraji, H. / International Federation of Automatic Control | British Library Conference Proceedings | 2004