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| Content Provider | The American Society of Mechanical Engineers (ASME) Digital Collection |
|---|---|
| Author | Franco-Robles, Jesús Lucio-Rangel, Alejandro De Camarillo-Gómez, Karla A. Pérez-Soto, Gerardo I. Rivera-Guillén, Jesús |
| Copyright Year | 2018 |
| Abstract | In this paper, a neuronal system with the ability to generate motion profiles and profiles of the ZMP in a 6DoF 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. |
| Sponsorship | Design Engineering Division Computers and Information in Engineering Division |
| File Format | |
| ISBN | 9780791851814 |
| DOI | 10.1115/DETC2018-86206 |
| Volume Number | Volume 5B: 42nd Mechanisms and Robotics Conference |
| Conference Proceedings | ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference |
| Language | English |
| Publisher Date | 2018-08-26 |
| Publisher Place | Quebec City, Quebec, Canada |
| Access Restriction | Subscribed |
| Subject Keyword | Cycles Simulation Artificial neural networks Kinematics Time series Trajectories (physics) Multilayer perceptron Machinery Robots |
| Content Type | Text |
| Resource Type | Article |
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