Robot depth estimation inspired by fixational movements
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comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
comunitat-uji-handle4:
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Title
Robot depth estimation inspired by fixational movementsDate
2020-09-18Publisher
Institute of Electrical and Electronics EngineersISSN
2379-8920Bibliographic citation
DURAN, Angel J.; DEL POBIL, Angel P. Robot depth estimation inspired by fixational movements. IEEE Transactions on Cognitive and Developmental Systems, 2020.Type
info:eu-repo/semantics/articlePublisher version
https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7274989Version
info:eu-repo/semantics/acceptedVersionSubject
Abstract
Distance estimation is a challenge for robots, human
beings and other animals in their adaptation to changing environments. Different approaches have been proposed to tackle
this problem based on classical vision ... [+]
Distance estimation is a challenge for robots, human
beings and other animals in their adaptation to changing environments. Different approaches have been proposed to tackle
this problem based on classical vision algorithms or, more
recently, deep learning. We present a novel approach inspired
by mechanisms involved in fixational movements to estimate a
depth image with a monocular camera. An algorithm based
on microsaccades and head movements during visual fixation
is presented. It combines the images generated by these micromovements with the ego-motion signal, to compute the depth
map. Systematic experiments using the Baxter robot in the
Gazebo/ROS simulator are described to test the approach in two
different scenarios, and evaluate the influence of its parameters
and its robustness in the presence of noise. [-]
Investigation project
Ministerio de Economia y Competitividad/DPI2015- 69041-R, UJI-B2018-74Rights
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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