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Title page for ETD etd-0329102-161914

Type of Document Master's Thesis
Author Kusumalnukool, Kanok
Author's Email Address kanok.kusumalnukool@vanderbilt.edu
URN etd-0329102-161914
Title The Self Agent for mobile robot
Degree Master of Science
Department Electrical Engineering
Advisory Committee
Advisor Name Title
D. mitch Wilkes Committee Chair
Richard Alan Peter II Committee Member
  • self agent
  • mobile robot
  • robot
  • san
Date of Defense 2002-03-18
Availability unrestricted
In robotics, we need robots which have the ability to understand what a human wants and

can respond accordingly. On the other hand, robot should be able to provide information that is

easy for a human to understand. Therefore, we developed the robot Self Agent to provide these

abilities. The main purpose of the Self Agent is to be the center of the robot. It provides every

basic need that a robot should have. For example, translating high-level command into basic

commands so that a robot can understand and execute them; Self-monitoring of the robot’s

performance; and having an intelligent action selection that will make good decisions.

Since we needed to have a good decision mechanism, we created a new approach which

consists of two algorithms. The first algorithm is Spreading Activation Network (SAN) that

provides the basis for selecting appropriate behaviors (Action Selection) for completing a given task.

To perform well, parameters of the Spreading Activation Network must be manually tuned. The

second algorithm is the Reinforcement Learning (RL) technique that enables a robot to

automatically learn multiple policies. This research will show we trained an ATRV-Jr robot, called

Scooter to learn policies and automatically adapt to unexpected variables.

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