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3D Shape and surface colour sensor fusion for robot vision

  • R. A. Jarvis (a1)


This paper argues the case for extracting as complete a set of sensory data as practicable from scenes consisting of complex assemblages of objects with the goal of completing the task of scene analysis, including placement, pose, identity and relationship amongst the components in a robust manner which supports goal directed robotic action, including collision-free trajectory planning, grip site location and manipulation of selected object classes.

The emphasis of the paper is that of sensor fusion of range and surface colour data including preliminary results in proximity, surface normal directionality and colour based scene segmentation through semantic-free clustering processes. The larger context is that of imbedding the results of such analysis in a graphics world containing an articulated robotic manipulator and of carrying out experiments in that world prior to replication of safe manipulation sequences in the real world.



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10.Alexander, B.F. and Ng, K.C., “3D Shape Measurement by Active Triangulation using an Array of Coded Light StripesSPIE 850, 199209 (11 1987).
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13.Jarvis, R.A., “A Laser time-of-Flight Range Scanner for Robotic VisionIEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-5, No. 5, 505512 (09 1983).
14.Jarvis, R.A. and Patrick, E.A., “Clustering Using a Similarity Measure Based on Shared Near NeighboursIEEE Transactions on Electronic Computers C-22, No. 11, 10251034 (11 1973).
15.Jarvis, R.A., “Region Based Image Segmentation Using Shared Near Neighbour Clustering” Proceedings International Conference on Cybernetics and Society,Washington, D.C.,19–21 September, 1977 (1977) pp. 641647.
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3D Shape and surface colour sensor fusion for robot vision

  • R. A. Jarvis (a1)


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