Motion planning for fast locomotion of compliantly actuated robotic legs is generally considered to be a challenging issue, posing considerable real-time problems. This is at least the case if time-continuous trajectories need to be generated online. In this paper we take advantage of a simple controller structure, which reduces the motion planning to a discrete-time planning problem, in which only a small set of input parameters need to be determined for each step. We show that for a planar leg with serial elastic actuation, hopping on a ground with stairs of irregular length and height can be planned online, based on a parameter mapping which has been learned in a data-driven manner by performing hopping trials with an adaptive exploration algorithm to evenly sample the parameter space. Experiments on a planar hopping leg prototype validate the approach.


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    Title :

    Data-Driven Discrete Planning for Targeted Hopping of Compliantly Actuated Robotic Legs


    Contributors:

    Conference:

    2019 ; Madrid, Spain



    Publication date :

    2018-10-01



    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    German





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