Robot Learning
PúblicoThe purpose of the project is to mimic human’s learning and motion mechanisms in order to create an adaptive walking gait on compliant humanoid robot - Atlas. The project applies neural controller theory based on Central Pattern Generators (CPG) to reduce a state (parameter) space from 100 states to an average of 10 states. The goal of the learning mechanism that utilizes unsupervised learning based on self-organizing maps and reward that adapts throughout the learning process is to find global optimal set of parameters for CPG. The learning mechanism also utilizes Covariance Matrix Adaptation – Evolutionary Strategies in order to converge to the parameter region that leads to stable walking gait (success region) quickly.
- This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
- Creator
- Publisher
- Identifier
- E-project-042516-180724
- Advisor
- Year
- 2016
- Date created
- 2016-04-25
- Resource type
- Major
- Rights statement
Las relaciones
- En Collection:
Elementos
Elementos
Miniatura | Título | Visibilidad | Embargo Release Date | Acciones |
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MQP_final_report_edited.pdf | Público | Descargar | |
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Submission.zip | Público | Descargar |
Permanent link to this page: https://digital.wpi.edu/show/qn59q5526