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Proceedings Paper

Biologically inspired obstacle avoidance: a technology-independent paradigm
Author(s): Derek Abbott; Andre Yakovleff; Alireza Moini; X. Thong Nguyen; Andrew Blanksby; R. Beare; Andrew J. Beaumont-Smith; Gyudong Kim; Abdesselam Bouzerdoum; Robert E. Bogner; Kamran Eshraghian
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Paper Abstract

With regard to obstacle avoidance, a paradigm shift from technology centered solutions to technology independent solutions is taking place. This trend also gives rise to a shift from function specific solutions to multifunctional solutions. A number of existing approaches are reviewed and a case study of a biologically inspired insect vision model is used to illustrate the new paradigm. The insect vision model leads to the realization of a sensor that is low in complexity, high in compactness, multifunctional and technology independent. Technology independence means that any front end technology, resulting in either optical, infrared or mm wave detection, for example, can be used with the model. Each technology option can be used separately or together with simple data fusion. Multifunctionality implies that the same system can detect obstacles, perform tracking, estimate time-to-impact, estimate bearing, etc. and is thus non-function specific. Progress with the latest VLSI realization of the insect vision sensor is reviewed and gallium arsenide is proposed as the future medium that will support a multifunctional and multitechnology fusion of optical, infrared, millimeter wave, etc. approaches. Applications are far reaching and include autonomous robot guidance, automobile anti-collision warning, IVHS, driver alertness warning, aids for the blind, continuous process monitoring/web inspection and automated welding, for example.

Paper Details

Date Published: 27 December 1995
PDF: 11 pages
Proc. SPIE 2591, Mobile Robots X, (27 December 1995); doi: 10.1117/12.228964
Show Author Affiliations
Derek Abbott, Univ. of Adelaide (Australia)
Andre Yakovleff, Univ. of Adelaide and Defence Science and Technology Organisation (Australia)
Alireza Moini, Univ. of Adelaide (Australia)
X. Thong Nguyen, Univ. of Adelaide (Australia)
Andrew Blanksby, Univ. of Adelaide (Australia)
R. Beare, Univ. of Adelaide (Australia)
Andrew J. Beaumont-Smith, Univ. of Adelaide (Australia)
Gyudong Kim, Univ. of Adelaide (Australia)and Seoul National Univ. (South Korea)
Abdesselam Bouzerdoum, Univ. of Adelaide (Australia)
Robert E. Bogner, Univ. of Adelaide (Australia)
Kamran Eshraghian, Univ. of Adelaide and Edith Cowan Univ. (Australia)


Published in SPIE Proceedings Vol. 2591:
Mobile Robots X
William J. Wolfe; Chase H. Kenyon, Editor(s)

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