Document Type

Technical Report

Department

Computer Science and Engineering

Publication Date

2011

Filename

WUCSE-2011-20.pdf

Technical Report Number

WUCSE-2011-20

Abstract

This project focuses on using Reinforcement Learning to optimize arm dynamics through muscle control for desired trajectories. The goal of this project was to create a tool that can be used to gain a better understanding of the arm’s muscles and collect information that is useful in many other disciplines such as biomechanics, anthropology, medicine and robotics. I developed biologically realistic models of primate arm's using Stanford’s SimTK software, an open-source tool for modeling musculoskeletal structures. I then made use of Differential Dynamic Programming in order to generate novel movements from first principles and optimize motion over a specified trajectory. Lastly, I demonstrated the usefulness of this tool by examining its effectiveness in discovering the consequences of different muscle groups on the optimal behavior policy.

Comments

Permanent URL: http://dx.doi.org/10.7936/K7RX9983

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