Abstract
A force-feedback Phantom device, a custom-built vibrotactile dataglove, and embossed paper sheets are compared to detect different textures. Two types of patterns are used, one formed by different geometrical shapes, and the other with different grooves width. Evaluation shows that the vibrotactile dataglove performs better in the detection of textures where the frequency of tactile stimuli varies, and it is even useful to detect more complex textures. © 2011 IFIP International Federation for Information Processing.
Author supplied keywords
Cite
CITATION STYLE
Martínez, J., García, A. S., Martínez, D., Molina, J. P., & González, P. (2011). Texture recognition: Evaluating force, vibrotactile and real feedback. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6949 LNCS, pp. 612–615). https://doi.org/10.1007/978-3-642-23768-3_95
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
