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LIQUID STATE MACHINE TO GENERATE THE MOVEMENT PROFILES FOR THE GAIT CYCLE OF A 6 DOF BIPEDAL ROBOT IN A SAGITTAL PLANE

机译:液体状态机生成矢状平面中6自由度双足机器人步态运动的轮廓

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In this paper, a neuronal system with the ability to generate motion profiles and profiles of the ZMP in a 6D0F bipedal robot in the sagittal plane, is presented. The input time series for LSM training are movement profiles of the oscillating foot trajectory obtained by forward kinematics performed by a previously trained ANN multilayer perceptron. The profiles of objective movement for training are acquired from the analysis of the human walk. Based on a previous simulation of the bipedal robot, a profile of the objective ZMP will be generated for the y- axis and another for the z-axis to know its behavior during the training walk. As an experimental result, the LSM generates new motion profiles and ZMP, given a different trajectory with which it was trained. With the LSM it will be possible to propose new trajectories of the oscillating foot, where it will be known if this trajectory will be stable, by the ZMP, and what movement profile for each articulation will be required to reach this trajectory.
机译:在本文中,提出了一种神经元系统,该系统具有在矢状面中的6D0F双足机器人中生成运动轮廓和ZMP轮廓的能力。用于LSM训练的输入时间序列是由先前训练过的ANN多层感知器执行的正向运动学获得的摆动脚轨迹的运动曲线。用于训练的客观运动曲线是通过对人的步行进行分析而获得的。基于双足机器人的先前模拟,将为y轴生成目标ZMP的轮廓,为z轴生成另一个ZMP轮廓,以了解其在训练步行过程中的行为。作为实验结果,LSM生成了新的运动曲线和ZMP,并给出了与它训练时不同的轨迹。使用LSM,将有可能提出摆动脚的新轨迹,通过ZMP可以知道该轨迹是否稳定,以及达到该轨迹需要每个关节的运动轮廓。

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