This paper proposes free-space motion tubes, a motion primitive for the local navigation of mobile robots equipped with range sensors. The geometry of a candidate motion tube captures the free-space required such that the robot may execute a maneuver without colliding with obstacles. Computational efficiency is achieved by selecting meaningful samples of the tube and evaluating them at run-time in the sensor space. Increasing the sensor resolution or the number of obstacles do not have any impact in the computational cost. Experimental results with a mobile platform show that free-space motion tubes are well-suited for navigating in cluttered environments and narrow passages.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Clutter-Resilient Autonomous Mobile Robot Navigation with Computationally Efficient Free-Space Features


    Additional title:

    Springer Proceedings in Advanced Robotics


    Contributors:

    Conference:

    The International Symposium of Robotics Research ; 2022 ; Geneva, Switzerland September 25, 2022 - September 30, 2022


    Published in:

    Robotics Research ; Chapter : 35 ; 522-537


    Publication date :

    2023-03-08


    Size :

    16 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Autonomous Navigation for Mobile Robot

    Peng, Gang / Lam, Tin Lun / Hu, Chunxu et al. | Springer Verlag | 2023


    Towards Resilient Autonomous Navigation of Drones

    Agha-mohammadi, Ali-akbar / Morrell, Benjamin / Fan, David D. et al. | NTRS | 2019


    Towards Resilient Autonomous Navigation of Drones

    Santamaria-Navarro, Angel / Thakker, Rohan / Fan, David D. et al. | TIBKAT | 2022


    Autonomous Navigation by a Mobile Robot

    Huntsberger, Terrance / Aghazarian, Hrand | NTRS | 2005


    Computationally Efficient Autonomous Overtaking on Highways

    Karlsson, Johan / Murgovski, Nikolce / Sjoberg, Jonas | IEEE | 2020