Jörgen Eriksson
Kristoffer Holmqvist
Mikael Graffner
Email: publicera@lub.lu.se
+46 (0)46 222 0326
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Theses, dissertations and research publications (including journal articles, conference abstracts and books) from Lund University are collected in this database. Where possible, the option to download a full text document is available. It is also possible to search for Lund University student theses in the student theses database.
| Title | Recognizing Texture and Hardness by Touch |
| Author/s | Magnus Johnsson, Christian Balkenius |
| Department/s |
Cognitive Science
|
| Full-text | Full text is not available in this archive |
| Publication/Series | 2008 IEEE/RSJ INTERNATIONAL CONFERENCE ON ROBOTS AND INTELLIGENT SYSTEMS, VOLS 1-3, CONFERENCE PROCEEDINGS |
| Publishing year | 2008 |
| Pages | 482 - 487 |
| Document type | Conference |
| Conference name | IEEE/RSJ International Conference on Intelligent Robots and Systems |
| Conference date | SEP 22-26, 2008 |
| Conference location | Nice, FRANCE |
| Status | published |
| Quality controlled | yes |
| Language | English |
| Publisher | IEEE Press |
| Abstract English | We have experimented with different neural network based architectures for bio-inspired self-organizing texture and hardness perception systems. To this end we have developed a microphone based texture sensor and a hardness sensor that measures the compression of the material at a constant pressure. We have implemented and successfully tested both monomodal systems for texture and hardness perception and multimodal systems that merge texture and hardness data into one representation. All systems were trained and tested with multiple samples gained from the exploration of a set of 4 soft and 4 hard objects of different materials. The monomodal texture system was good at mapping individual objects in a sensible way, the hardness systems was good at mapping individual objects and in addition dividing the objects into categories of hard and soft objects. The multimodal system was successful in merging the two modalities into a representation that performed at least as good as the best recognizer of individual objects, i.e. the texture system, and at the same time categorizing the objects into hard and soft. |
| Subject |
Technology and Engineering Medicine and Health Sciences Social Sciences |
Jörgen Eriksson
Kristoffer Holmqvist
Mikael Graffner
Email: publicera@lub.lu.se
+46 (0)46 222 0326
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