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Robustness of a distributed neural network controller for locomotion in a hexapod robotA distributed neural-network controller for locomotion, based on insect neurobiology, has been used to control a hexapod robot. How robust is this controller? Disabling any single sensor, effector, or central component did not prevent the robot from walking. Furthermore, statically stable gaits could be established using either sensor input or central connections. Thus, a complex interplay between central neural elements and sensor inputs is responsible for the robustness of the controller and its ability to generate a continuous range of gaits. These results suggest that biologically inspired neural-network controllers may be a robust method for robotic control.
Document ID
19920068513
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Chiel, Hillel J.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Beer, Randall D.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Quinn, Roger D.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Espenschied, Kenneth S.
(Case Western Reserve University Cleveland, OH, United States)
Date Acquired
August 15, 2013
Publication Date
June 1, 1992
Publication Information
Publication: IEEE Transactions on Robotics and Automation
Volume: 8
Issue: 3 Ju
ISSN: 1042-296X
Subject Category
Cybernetics
Accession Number
92A51137
Funding Number(s)
CONTRACT_GRANT: N00014-90-J-1545
CONTRACT_GRANT: NGT-50588
CONTRACT_GRANT: NSF BNS-88-10757
Distribution Limits
Public
Copyright
Other

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