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Neural network structure for navigation using potential fieldsA hybrid-network method for obstacle avoidance in the truck-backing system of D. Nguyen and B. Widrow (1989) is presented. A neural network technique for vehicle navigation and control in the presence of obstacles has been developed. A potential function which peaks at the surface of obstacles and has its minimum at the proper vehicle destination is computed using a network structure. The field is guaranteed not to have spurious local minima and does not have the property of flattening-out far from the goal. A feedforward neural network is used to control the steering of the vehicle using local field information. The network is trained in an obstacle-free space to follow the negative gradient of the field, after which the network is able to control and navigate the truck to its target destination in a space of obstacles which may be stationary or movable.
Document ID
19930053009
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Plumer, Edward S.
(Stanford Univ. CA, United States)
Date Acquired
August 16, 2013
Publication Date
January 1, 1992
Publication Information
Publication: In: IJCNN - International Joint Conference on Neural Networks, Baltimore, MD, June 7-11, 1992, Proceedings. Vol. 1 (A93-37001 14-63)
Publisher: Institute of Electrical and Electronics Engineers, Inc.
Subject Category
Cybernetics
Accession Number
93A37006
Funding Number(s)
CONTRACT_GRANT: NGT-50642
Distribution Limits
Public
Copyright
Other

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