Online Direction Classification and Recognition Using an Intuitive Tactile Communication
2014 ◽
Vol 543-547
◽
pp. 1542-1545
Keyword(s):
This paper proposed an online direction classifying method for constructing an intuitive tactile communication during human-robot cooperation. The proposed approach abstracts a suitable feature set from a tactile array sensor equipped on a hand-bar. This lower computation feature extraction method analyze the weighting values concerned with oriental information from principle component analysis (PCA), together with support vector machines (SVM) classifier for direction classification and recognition. Experimental results showed an average accuracy of 96.3% and a low costs of 512μs with respect to different handle gestures of the 6 touch directions, which is practicable utilized for human-robot cooperation based on tactile recognition.
2012 ◽
Vol 2
(1)
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pp. 16-41
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2017 ◽
Vol 7
(5)
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pp. 2547
2016 ◽
Vol 6
(6)
◽
pp. 2797
2021 ◽
Vol 11
(10)
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pp. 2558-2565
2016 ◽
Vol 6
(6)
◽
pp. 2797
2014 ◽
Vol 85
(8)
◽
pp. 34-42
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Keyword(s):