Distributed associative memory (DAM) for bin-picking
- 1 January 1989
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 11 (8) , 814-822
- https://doi.org/10.1109/34.31444
Abstract
The feasibility of using a distributed associative memory as the recognition component for a bin-picking system is established. The system displays invariance to metric distortions and a robust response in the presence of noise, occlusions, and faults. Although the system is primarily concerned with two-dimensional problems, eight extensions to the system allow the three-dimensional bin-picking problem to be addressed. It is noted that there are implicit weaknesses in the neural network model chosen for the heart of the recognition system. The distributed associative memory used is linear, and as a result there are certain desirable properties that cannot be exhibited by the computer vision system.Keywords
This publication has 16 references indexed in Scilit:
- 2-D invariant object recognition using distributed associative memoryPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1988
- Model-based recognition in robot visionACM Computing Surveys, 1986
- Perceptual Organization and Visual RecognitionPublished by Springer Nature ,1985
- Matched Filters for Bin PickingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1984
- The Mechanical Manipulation of Randomly Oriented PartsScientific American, 1984
- Cooperating processes for low-level vision: A surveyArtificial Intelligence, 1981
- Against direct perceptionBehavioral and Brain Sciences, 1980
- The internal representation of solid shape with respect to visionBiological Cybernetics, 1979
- Logarithmic spiral grids for image processing and displayComputer Graphics and Image Processing, 1979
- A Model-Based Vision System for Industrial PartsIEEE Transactions on Computers, 1978