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Titolo:
A new approach to vision-based unsupervised learning of unexplored indoor environment for autonomous land vehicle navigation
Autore:
Chen, GY; Tsai, WH;
Indirizzi:
Natl Tsing Hua Univ, Dept Comp & Informat Sci, Hsinchu 300, Taiwan Natl Tsing Hua Univ Hsinchu Taiwan 300 Informat Sci, Hsinchu 300, Taiwan
Titolo Testata:
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
fascicolo: 5, volume: 15, anno: 1999,
pagine: 353 - 364
SICI:
0736-5845(199910)15:5<353:ANATVU>2.0.ZU;2-V
Fonte:
ISI
Lingua:
ENG
Keywords:
unsupervised learning; autonomous land vehicle navigation; computer vision; model matching; pushdown transducer; environment exploration;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
18
Recensione:
Indirizzi per estratti:
Indirizzo: Tsai, WH Natl Tsing Hua Univ, Dept Comp & Informat Sci, 1001 Ta Hsuch Rd, Hsinchu 300, Taiwan Natl Tsing Hua Univ 1001 Ta Hsuch Rd Hsinchu Taiwan 300 , Taiwan
Citazione:
G.Y. Chen e W.H. Tsai, "A new approach to vision-based unsupervised learning of unexplored indoor environment for autonomous land vehicle navigation", ROBOT CIM, 15(5), 1999, pp. 353-364

Abstract

A vision-based approach to unsupervised learning of the indoor environmentfor autonomous land vehicle (ALV) navigation is proposed. The ALV may, without human's involvement, self-navigate systematically in an unexplored closed environment, collect the information of the environment features, and then build a top-view map of the environment for later planned navigation orother applications. The learning system consists of three subsystems: a feature location subsystem, a model management subsystem, and an environment exploration subsystem. The feature location subsystem processes input images, and calculates the locations of the local features and the ALV by model matching techniques. To facilitate feature collection, two laser markers are mounted on the vehicle which project laser light on the corridor walls toform easily detectable line and corner features. The model management subsystem attaches the local model into a global one by merging matched corner pairs as well as line segment pairs, The environment exploration subsystem guides the ALV to explore the entire navigation environment by using the information of the learned model and the current ALV location. The guidance scheme is based on the use of a pushdown transducer derived from automata theory. A prototype learning system was implemented on a real vehicle, and simulations and experimental results in real environments show the feasibility of the proposed approach. (C) 1999 Elsevier Science Ltd. All rights reserved.

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Documento generato il 22/09/20 alle ore 06:22:43