Segmentation via manipulation

Segmentation via manipulation

A paradigm of iterative, interactive scene segmentation and simplification of random heaps of unknown objects via vision and manipulation is introduced. The scene simplification is based on the graph operations of vertex and edge removal. These operations are defined isomorphic to the pick and push...

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Bibliographic Details
Published in:IEEE transactions on robotics and automation Vol. 7; no. 3; pp. 306 - 319
Main Authors: Tsikos, C.J., Bajcsy, R.K.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01-06-1991
Institute of Electrical and Electronics Engineers
Subjects:
Applied sciences
Computer science; control theory; systems
Control theory. Systems
Convergence
Exact sciences and technology
Force sensors
Layout
Machine vision
Manipulators
Robot sensing systems
Robot vision systems
Robotics
Testing
Torque
Turing machines
Computer vision
Graph
Segmentation
Manipulation
Robotics
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Summary:A paradigm of iterative, interactive scene segmentation and simplification of random heaps of unknown objects via vision and manipulation is introduced. The scene simplification is based on the graph operations of vertex and edge removal. These operations are defined isomorphic to the pick and push manipulation actions. Sensors are used as graph generators and the manipulator is used as the decomposing mechanism of the graphs. The model is a nondeterministic finite-state Turing machine. A vision system, a manipulator, and force/torque and other sensory input are integrated into a robot work cell. Experiments conducted to test convergence and error recovery of four different strategies are discussed. It is found that under certain conditions the strategies can tolerate errors in the sensory data, recover from pathological states, and converge.< >
ISSN:1042-296X
2374-958X
DOI:10.1109/70.88140