Multi-dimensional pre-programmed and learned fine motor control for a humanoid robot

Silver, Aaron

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https://hdl.handle.net/2142/34413 Copy

Description

Title

Multi-dimensional pre-programmed and learned fine motor control for a humanoid robot

Author(s)

Silver, Aaron

Issue Date

2012-09-18T21:15:43Z

Director of Research (if dissertation) or Advisor (if thesis)

Levinson, Stephen E.

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• reinforcement learning
• fine motor control
• humanoid robot
• iCub
• proportional–integral–derivative (PID) control
• balancing

Abstract

One of the biggest questions in modern electrical and computer engineering is that of computational intelligence. Can an artificially created mechanism, such as a humanoid robot, become intelligent, adaptable, and possess the ability to learn to classify the world in terms of language as humans do? This thesis discusses an effort to explore one small piece of this puzzle, the use of sensory-motor interaction with the physical world. We postulate that the ability to manipulate and interact with the environment around oneself is integral to achieving intelligence and language. The first part of this study employs a sophisticated iCub humanoid robot and classical control techniques to determine if the robot is capable of performing the necessary fine-motor controlled tasks. The second part of this study goes on to determine if machine reinforcement learning techniques are able to give this robot the same capability.

Graduation Semester

2012-08

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http://hdl.handle.net/2142/34413

Copyright and License Information

Copyright 2012 Aaron Silver

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