In this paper, we propose an autonomous mobile robot navigation system that considers pedestrian flow in a crosswalk. Recently, autonomous mobile robots have been introduced into the real world. Such a robot is required to move efficiently; however, it should avoid pedestrians and obstacles safely. On a normal sidewalk, if there is a risk of a collision with a pedestrian, the mobile robot can wait until this danger is gone. However, at crosswalks, there is a high risk of collision with pedestrians due to multiple pedestrians coming and going. There is a time constraint of having to cross while the signal is green. The conventional mobile robot navigation methods cannot be used in this situation. The pedestrians move in the direction of each other in response to their movements. This walking way enables a large number of people to pass through the crosswalk in a short period when the signal is green. Therefore, this study analyses the movement of pedestrians passing through the crosswalk in a group. We investigate a mechanism of generating pedestrian flow on a crosswalk. Furthermore, we propose a mobile robot navigation method that can avoid the risk of collisions with pedestrians and pass through crosswalks while the signal is green, using an algorithm to guide a mobile robot along the pedestrian flow that we investigated.


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    Titel :

    Modelling of Pedestrians Crossing a Crosswalk and Robot Navigation Based on Its Characteristics


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Chugo, Daisuke (Herausgeber:in) / Tokhi, Mohammad Osman (Herausgeber:in) / Silva, Manuel F. (Herausgeber:in) / Nakamura, Taro (Herausgeber:in) / Goher, Khaled (Herausgeber:in) / Yamada, Shunsuke (Autor:in) / Chugo, Daisuke (Autor:in) / Muramatsu, Satoshi (Autor:in) / Yokota, Sho (Autor:in) / She, Jin-Hua (Autor:in)

    Kongress:

    Climbing and Walking Robots Conference ; 2021 August 30, 2021 - September 01, 2021



    Erscheinungsdatum :

    04.09.2021


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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