Biologically inspired automatic construction of cross-modal mapping in robotic eye/hand systems

Authors Organisations
Type Conference Proceeding (Non-Journal item)
Original languageEnglish
Title of host publication2006 IEEE/RSJ International Conference on Intelligent Robots and Systems
Pages4742-4749
Number of pages8
ISBN (Electronic) 1-4244-0259-X
DOI
Publication statusPublished - 2006
EventProceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems - Beijiing, China
Duration: 09 Oct 200615 Oct 2006

Conference

ConferenceProceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems
Country/TerritoryChina
CityBeijiing
Period09 Oct 200615 Oct 2006
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Abstract

Advanced autonomous artificial systems will need incremental learning and adaptive abilities similar to those seen in humans. Knowledge from biology, psychology and neuro-science is now inspiring new approaches for systems that have sensory-motor capabilities and operate in complex environments. Eye/hand coordination is an important cross-modal cognitive function, and is also typical of many of the other coordinations that must be involved in the control and operation of embodied intelligent systems. This paper examines a biologically inspired approach for incrementally constructing compact mapping networks for eye/hand coordination. We present a simplified node-decoupled extended Kalman filter for radial basis function networks, and compare this with other learning algorithms. An experimental system consisting of a robot arm and a pan-and-tilt head with a color camera is used to produce results and test the algorithms in this paper. We also present three approaches for adapting to structural changes during eye/hand coordination tasks, and the robustness of the algorithms under noise are investigated. The learning and adaptation approaches in this paper have similarities with current ideas about neural growth in the brains of infants during early cognitive development.