Terrain assessment and path planning for mobile robots are intrinsically linked. There exists a variety of terrain assessment algorithms and these methods follow the trend of low-fidelity at low-cost and high-fidelity at high-cost. We present a modular path-planning algorithm that uses a hierarchy of terrain-assessment methods, from low-fidelity to high-fidelity. Using the available sensor data, the visible terrain is first assessed with the low-fidelity, low-cost method. The decision to assess a piece of terrain with the high-fidelity, high-cost method is made considering potential path benefits and the cost of assessment. This can be thought of as providing a means to triage large amounts of terrain data. The result is a lower combined cost of the path and terrain assessment that exploits the capabilities of the robot chassis where prudent. We demonstrate a system using one implementation of the technique on a large number of simulated path planning problems in fractal terrain. Additionally, we provide results and system details from an experimental field test carried out on Devon Island, Canada.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Path planning with variable-fidelity terrain assessment


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2012


    Format / Umfang :

    14 Seiten




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




    Accuracy Assessment of Two Gps Fidelity Prediction Services in Urban Terrain

    A. Moore / J. Gutierrez / E. Dill et al. | NTIS | 2023


    Accuracy Assessment of Two GPS Fidelity Prediction Services in Urban Terrain

    Andrew J. Moore / Julian Gutierrez / Evan Dill et al. | NTRS


    Accuracy Assessment of Two Gps Fidelity Prediction Services in Urban Terrain

    Andrew Moore / Julian Gutierrez / Evan Dill et al. | NTRS


    UAV Path Planning With Terrain Constraints for Aerial Scanning

    Yuan, Jinbiao / Liu, Zhenbao / Xiong, Xiaoyu et al. | IEEE | 2024


    Rough Terrain Path Planning for Autonomous Ground Robot

    Truong, Xuan-Phat / Hong, Seong Hyeon | AIAA | 2024