Navigating in complex and highly dynamic environments such as crowds is still a major challenge for autonomous vehicle such as autonomous wheelchairs or even autonomous cars. This article presents a new way of navigating in crowds by using behavioral clustering for the surrounding agents and representing the crowd as a set of moving polygons. Once the environment has been modelled in this way and the robot has all the information it needs, we then propose a navigation algorithm that is able to guide the vehicle through the scene. The key-points of this algorithm are that (1) it can avoid densely-populated areas in order to minimize the risk of being on a collision course with any of the surrounding dynamic obstacles, (2) it generates socially compliant trajectories.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Socially Compliant Navigation in dense crowds


    Contributors:


    Publication date :

    2019-06-01


    Size :

    1202875 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Detecting people in dense crowds

    Sim, C. H. | British Library Online Contents | 2012




    Dense Crowds Detection and Surveillance with Drones using Density Maps

    Gonzalez-Trejo, Javier / Mercado-Ravell, Diego | IEEE | 2020


    Tracking in dense crowds using prominence and neighborhood motion concurrence

    Idrees, H. / Warner, N. / Shah, M. | British Library Online Contents | 2014