A Biologically Inspired Approach for Robot Depth Estimation
Joint Authors
Martinez-Martin, Ester
del Pobil, Angel P.
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-08-23
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Aimed at building autonomous service robots, reasoning, perception, and action should be properly integrated.
In this paper, the depth cue has been analysed as an early stage given its importance for robotic tasks.
So, from neuroscience findings, a hierarchical four-level dorsal architecture has been designed and implemented.
Mainly, from a stereo image pair, a set of complex Gabor filters is applied for estimating an egocentric quantitative disparity map.
This map leads to a quantitative depth scene representation that provides the raw input for a qualitative approach.
So, the reasoning method infers the data required to make the right decision at any time.
As it will be shown, the experimental results highlight the robust performance of the biologically inspired approach presented in this paper.
American Psychological Association (APA)
Martinez-Martin, Ester& del Pobil, Angel P.. 2018. A Biologically Inspired Approach for Robot Depth Estimation. Computational Intelligence and Neuroscience،Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1130850
Modern Language Association (MLA)
Martinez-Martin, Ester& del Pobil, Angel P.. A Biologically Inspired Approach for Robot Depth Estimation. Computational Intelligence and Neuroscience No. 2018 (2018), pp.1-16.
https://search.emarefa.net/detail/BIM-1130850
American Medical Association (AMA)
Martinez-Martin, Ester& del Pobil, Angel P.. A Biologically Inspired Approach for Robot Depth Estimation. Computational Intelligence and Neuroscience. 2018. Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1130850
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1130850