Limbless locomotion, evidenced by both biological and robotic snakes, capitalizes on these systems' redundant degrees of freedom to negotiate complicated environments. While the versatility of locomotion methods provided by a snake-like form is of great advantage, the difficulties in both representing the high dimensional workspace configuration and implementing the desired translations and orientations makes difficult further development of autonomous behaviors for snake robots. Based on a previously defined average body frame and set of motion primitives, this work proposes locomotive reduction, a simplifying methodology which reduces the complexity of controlling a redundant snake robot to that of navigating a differential-drive vehicle. We verify this technique by controlling a 16-DOF snake robot using locomotive reduction combined with a visual tracking system. The simplicity resulting from the proposed locomotive reduction method allows users to apply established autonomous navigation techniques previously developed for differential-drive cars to snake robots. Best of all, locomotive reduction preserves the advantages of a snake robot's ability to perform a variety of locomotion modes when facing complicated mobility challenges.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Locomotive reduction for snake robots


    Contributors:
    Xuesu Xiao (author) / Cappo, Ellen (author) / Weikun Zhen (author) / Jin Dai (author) / Ke Sun (author) / Chaohui Gong (author) / Travers, Matthew J. (author) / Choset, Howie (author)


    Publication date :

    2015-05-01


    Size :

    1698447 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Snake arm robots for flexible delivery

    Buckingham, R. | Tema Archive | 2002


    ReQuBiS - Reconfigurable Quadrupedal-Bipedal Snake Robots

    Chiddarwar, Shital / Kamat, Ajinkya / Pandya, Karan et al. | NTRS | 2021




    Robotlæring for slangeroboter ; Robot learning for snake robots

    Monzó Brandvold, Christian | BASE | 2011

    Free access