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Record 1 of 7656
Learning for autonomous navigation
External Online Source: hdl:2014/38551
Author and Affiliation:
Angelova, Anelia
Howard, Andrew
Matthies, Larry
Tang, Benyang
Turmon, Michael
Mjolsness, Eric
Abstract: Autonomous off-road navigation of robotic ground vehicles has important applications on Earth and in space exploration. Progress in this domain has been retarded by the limited lookahead range of 3-D sensors and by the difficulty of preprogramming systems to understand the traversability of the wide variety of terrain they can encounter.
Publication Date: Dec 01, 2005
Document ID:
20060043514
(Acquired Sep 15, 2006)
Document Type: Conference Paper
Meeting Information: Neural Information Processing Systems; December 8-12, 2005; Vancouver, British Columbia; Canada
Financial Sponsor: Jet Propulsion Lab., California Inst. of Tech.; Pasadena, CA, United States
Description: In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright
NASA Terms: AUTONOMOUS NAVIGATION; PROGRESS; ROADS; ROBOTICS; SPACE EXPLORATION; TERRAIN
Other Descriptors: LEARNING; ROBOTICS; NAVIGATION
Availability Source: Other Sources
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