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Titolo:
AN INCREMENTAL-LEARNING-BY-NAVIGATION APPROACH TO VISION-BASED AUTONOMOUS LAND VEHICLE GUIDANCE IN INDOOR ENVIRONMENTS USING VERTICAL LINE INFORMATION AND MULTIWEIGHTED GENERALIZED HOUGH TRANSFORM TECHNIQUE
Autore:
CHEN GY; TSAI WH;
Indirizzi:
NATL CHIAO TUNG UNIV,DEPT COMP & INFORMAT SCI HSINCHU 300 TAIWAN
Titolo Testata:
IEEE transactions on systems, man and cybernetics. Part B. Cybernetics
fascicolo: 5, volume: 28, anno: 1998,
pagine: 740 - 748
SICI:
1083-4419(1998)28:5<740:AIATVA>2.0.ZU;2-V
Fonte:
ISI
Lingua:
ENG
Keywords:
AUTONOMOUS LAND VEHICLE; GUIDANCE; INCREMENTAL LEARNING; MODEL MATCHING; NAVIGATION; WEIGHTED GENERALIZED HOUGH TRANSFORM;
Tipo documento:
Letter
Natura:
Periodico
Settore Disciplinare:
CompuMath Citation Index
CompuMath Citation Index
CompuMath Citation Index
Science Citation Index Expanded
Science Citation Index Expanded
Science Citation Index Expanded
Citazioni:
17
Recensione:
Indirizzi per estratti:
Citazione:
G.Y. Chen e W.H. Tsai, "AN INCREMENTAL-LEARNING-BY-NAVIGATION APPROACH TO VISION-BASED AUTONOMOUS LAND VEHICLE GUIDANCE IN INDOOR ENVIRONMENTS USING VERTICAL LINE INFORMATION AND MULTIWEIGHTED GENERALIZED HOUGH TRANSFORM TECHNIQUE", IEEE transactions on systems, man and cybernetics. Part B. Cybernetics, 28(5), 1998, pp. 740-748

Abstract

An incremental-learning-by-navigation approach to vision-based autonomous land vehicle (ALV) guidance in indoor environments is proposed. The approach consists of three stages: initial learning, navigation, and model updating. In the initial learning stage, the ALV is driven manually, and environment images and other status data are recorded automatically, Then, an off-line procedure is performed to build an initialenvironment model. In the navigation stage, the ALV moves along the learned environment automatically, locates itself by model matching, and records necessary information for model updating. In the model updating stage, an off-line procedure is performed to refine the learned model. A more precise model is obtained after each navigation-and-updateiteration. Used environment features are vertical straight lines in camera views. A multiweighted generalized Hough transform is proposed for model matching. A real ALV was used as the testbed, and successful navigation experiments show the feasibility of the proposed approach.

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Documento generato il 18/09/20 alle ore 17:06:34