Successful navigation of small, unmanned aerial vehicles (UAVs) in cluttered environments is a challenging task, especially in the presence of turbulent winds and state estimation uncertainty. This paper proposes a probabilistic path planner for UAVs operating in cluttered environments. Unlike previous sampling-based approaches which select robust paths from a set of trajectory candidates, the proposed algorithm seeks to modify an initial desired path so that it satisfies obstacle avoidance constraints. Given a desired path, Monte Carlo uncertainty propagation is performed and obstacle collision risks are quantified at discrete intervals along the trajectory. A numerical optimization algorithm is used to modify the flight path around obstacles and reduce probability of collision while maintaining as much of the originally desired path as possible. The proposed path planner is specifically designed to leverage embedded massively parallel computers for near real-time uncertainty propagation. Thus the planner can be run in real-time in a feedback manner, modifying the path appropriately as new measurements are obtained. Example results for a standard quadrotor show the ability of the path planning scheme to successfully generate trajectories in cluttered environments. Trade studies characterize algorithm performance as a function of obstacle density and collision risk acceptability.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A sampling-based probabilistic path planner for multirotor air vehicles in cluttered environments


    Beteiligte:


    Erscheinungsdatum :

    2017




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    55.50 Luftfahrzeugtechnik / 55.60 Raumfahrttechnik
    Lokalklassifikation TIB:    275/7040




    Design of a Multi-Layer UAV Path Planner for Cluttered Environments

    Galea, Marlon / Zammit, Brian / Gauci, Jason | IEEE | 2018



    Autonomous flight through cluttered outdoor environments using a memoryless planner

    Lee, Junseok / Wu, Xiangyu / Lee, Seung Jae et al. | IEEE | 2021


    Efficient path planing for articulated vehicles in cluttered environments

    Samaniego, Ricardo / Rodríguez, Rodrigo / Vazquez Nuñez, Fernando Antonio et al. | BASE | 2020

    Freier Zugriff