A Biologically Inspired Approach for Robot Depth Estimation

TitleA Biologically Inspired Approach for Robot Depth Estimation
Publication TypeJournal Article
Year of Publication2018
AuthorsMartinez-Martin, E, del Pobil, AP
JournalComputational Intelligence and Neuroscience
Date Published2018/08/23
ISBN Number1687-5265

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.