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A Method for Generating Robot Control Systems

Bishop, Russell C.
http://rave.ohiolink.edu/etdc/view?acc_num=ysu1222394834

Abstract Details

2008, Master of Science in Engineering, Youngstown State University, Department of Electrical and Computer Engineering.
This thesis presents a method of generating neural-network based control systems for walking robots. A genetic learning rule is combined with a physics simulation and scoring system in order to find appropriate weights for these networks. This approach produces highly robust neural-network control mechanisms that are capable of handling a wide variety of conditions, such as rough terrain and randomly varying robot proportions. In each of two test runs, the system was able to make the robot walk approximately 1.75 meters (5.8 body lengths) in the physics simulation, over very rough terrain, in 14 seconds of simulation-world time.
Jalal Jalali, PhD (Advisor)
Frank Li, PhD (Committee Member)
Philip Munro, PhD (Committee Member)
105 p.
Robots
genetic algorithm; neural network; walking robot

Recommended Citations

Citations

  • Bishop, R. C. (2008). A Method for Generating Robot Control Systems [Master's thesis, Youngstown State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1222394834

    APA Style (7th edition)

  • Bishop, Russell. A Method for Generating Robot Control Systems. 2008. Youngstown State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ysu1222394834.

    MLA Style (8th edition)

  • Bishop, Russell. "A Method for Generating Robot Control Systems." Master's thesis, Youngstown State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1222394834

    Chicago Manual of Style (17th edition)

ysu1222394834
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© 2008, all rights reserved.
This open access ETD is published by Youngstown State University and OhioLINK.