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Asian Conference on Computer Vision

ACCV 1995: Recent Developments in Computer Vision pp 111–128Cite as

Modeling structured environments using robot vision

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1035))

Abstract

In this paper, we review the various methods for robust autonomous mobile robot navigation and scene modeling in structured environments. The techniques vary with availibility of a priori knowledge of the environment and the number of sensors with which the robot is equipped. The methods may be broadly classified into three categories: model based approaches, landmark based methods, and methods using information provided by the robot trajectory and its integration with sensor information for navigation and estimation of three dimensional (3D) position in the environment. Also, we describe the mobile robot ROBO-TEX, an autonomous mobile robot constructed in our laboratory. A successful implementation for constructing computer aided design (CAD) models of a structured scene as imaged by a single wide angle lens CCD camera while navigating is considered and evaluated. Finally, we discuss another navigation system that uses a stereo pair of fish-eye lenses, and discuss the merits of such a system over some of the other implementations for navigation and modeling of the scene.

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Authors and Affiliations

  1. Computer and Vision Research Center Department of Electrical and Computer Engineering, The University of Texas at Austin, 78712-1084, Austin, Texas, USA

    Shishir Shah & J. K. Aggarwal

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  1. Shishir Shah
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  2. J. K. Aggarwal
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Stan Z. Li Dinesh P. Mital Eam Khwang Teoh Han Wang

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© 1996 Springer-Verlag Berlin Heidelberg

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Shah, S., Aggarwal, J.K. (1996). Modeling structured environments using robot vision. In: Li, S.Z., Mital, D.P., Teoh, E.K., Wang, H. (eds) Recent Developments in Computer Vision. ACCV 1995. Lecture Notes in Computer Science, vol 1035. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60793-5_67

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  • DOI: https://doi.org/10.1007/3-540-60793-5_67

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  • Online ISBN: 978-3-540-49448-5

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