There are various trajectory planners for mobile manipulators. It is often challenging to compare their performance under similar circumstances due to differences in hardware, dissimilarity of tasks and objectives, as well as uncertainties in measurements and operating environments. In this paper, we propose a simulation framework to evaluate the performance of the local trajectory planners to generate smooth, and dynamically and kinematically feasible trajectories for mobile manipulators in the same environment. We focus on local planners as they are key components that provide smooth trajectories while carrying a load, react to dynamic obstacles, and avoid collisions. We evaluate two prominent local trajectory planners, Dynamic-Window Approach (DWA) and Time Elastic Band (TEB) using the metrics that we introduce. Moreover, our software solution is applicable to any other local planners used in the Robot Operating System (ROS) framework, without additional programming effort.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Benchmarking local motion planners for navigation of mobile manipulators


    Beteiligte:
    Tafnakaji, S (Autor:in) / Hajieghrary, H (Autor:in) / Teixeira, Q (Autor:in) / Bekiroglu, Y (Autor:in)

    Erscheinungsdatum :

    2023-02-15


    Anmerkungen:

    In: 2023 IEEE/SICE International Symposium on System Integration, SII 2023. IEEE: Atlanta, GA, USA. (2023)


    Medientyp :

    Paper


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    629



    The motion control manipulators on mobile vehicles

    Hootsmans, Norbert A. M. (Norbert Antony Murray) | DSpace@MIT | 1992

    Freier Zugriff

    PERFORMANCE TESTING FOR MOBILE ROBOT TRAJECTORY PLANNERS

    WHITESIDE IAIN / FERRI MARCO | Europäisches Patentamt | 2023

    Freier Zugriff

    PERFORMANCE TESTING FOR MOBILE ROBOT TRAJECTORY PLANNERS

    WHITESIDE IAIN / FERRI MARCO | Europäisches Patentamt | 2024

    Freier Zugriff

    Enhancing Randomized Motion Planners: Exploring with Haptic Hints

    Bayazit, O. B. / Song, G. / Amato, N. M. | British Library Online Contents | 2001