Haptic Perception with Self-Organizing ANNs and an Anthropomorphic Robot Hand
We have implemented and compared four biologically motivated self-organizing haptic systems based on proprioception. All systems employ a 12-d.o.f. anthropomorphic robot hand, the LUCS Haptic Hand 3. The four systems differ in the kind of self-organizing neural network used for clustering. For the m...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2010-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2010/860790 |
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| Summary: | We have implemented and compared four biologically motivated
self-organizing haptic systems based on proprioception. All systems
employ a 12-d.o.f. anthropomorphic robot hand, the LUCS Haptic
Hand 3. The four systems differ in the kind of self-organizing neural
network used for clustering. For the mapping of the explored objects,
one system uses a Self-Organizing Map (SOM), one uses a Growing Cell
Structure (GCS), one uses a Growing Cell Structure with Deletion of
Neurons (GCS-DN), and one uses a Growing Grid (GG). The systems
were trained and tested with 10 different objects of different sizes from
two different shape categories. The generalization abilities of the systems
were tested with 6 new objects. The systems showed good performance
with the objects from the training set as well as in the generalization
experiments. Thus the systems could discriminate individual objects,
and they clustered the activities into small cylinders, large cylinders,
small blocks, and large blocks. Moreover, the self-organizing ANNs were
also organized according to size. The GCS-DN system also evolved disconnected
networks representing the different clusters in the input space
(small cylinders, large cylinders, small blocks, large blocks), and the generalization
samples activated neurons in a proper subnetwork in all but
one case. |
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| ISSN: | 1687-9600 1687-9619 |