The 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

• Nurbekov, Batyrlan

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-042516-180724

Advisor

• Gennert, Michael A.

Year

• 2016

Date created

• 2016-04-25

Resource type

• Major Qualifying Project

Major

• Interdisciplinary

Rights statement

• In Copyright

License

• All rights reserved