Tactile image based contact shape recognition using neural network
2012 (English)In: Multisensor Fusion and Integration for Intelligent Systems (MFI), 2012 IEEE Conference on, IEEE , 2012, 138-143 p.Conference paper (Refereed)
This paper proposes a novel algorithm for recognizing the shape of object which in contact with a robotic finger through the tactile pressure sensing. The developed algorithm is capable of distinguishing the contact shapes between a set of low-resolution pressure map. Within this algorithm, a novel feature extraction technique is developed which transforms a pressure map into a 512-feature vector. The extracted feature of the pressure map is invariant to scale, positioning and partial occlusion, and is independent of the sensor's resolution or image size. To recognize different contact shape from a pressure map, a neural network classifier is developed and uses the feature vector as inputs. It has proven from tests of using four different contact shapes that, the trained neural network can achieve a high success rate of over 90%. Contact sensory information plays a crucial role in robotic hand gestures. The algorithm introduced in this paper has the potential to provide valuable feedback information to automate and improve robotic hand grasping and manipulation.
Place, publisher, year, edition, pages
IEEE , 2012. 138-143 p.
Feature extraction techniques, Feature vectors, Feed back information, Hand gesture, Hand grasping, Neural network classifier, Novel algorithm, Partial occlusions, Robotic finger, Sensory information, Shape recognition, Tactile images, Tactile pressure, Trained neural networks
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-111805DOI: 10.1109/MFI.2012.6343036ScopusID: 2-s2.0-84870624417ISBN: 978-146732511-0OAI: oai:DiVA.org:kth-111805DiVA: diva2:587486
2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2012, 13 September 2012 through 15 September 2012, Hamburg
QC 201301142013-01-142013-01-142013-09-03Bibliographically approved