DocumentCode :
2485635
Title :
A GMR based magnetic pretouch sensing system for a robot grasper
Author :
Schlegl, T. ; Mühlbacher-Karrer, S. ; Neumayer, M. ; Zangl, H.
Author_Institution :
Inst. of Electr. Meas. & Meas. Signal Process., Graz Univ. of Technol., Graz, Austria
fYear :
2012
fDate :
13-16 May 2012
Firstpage :
1506
Lastpage :
1510
Abstract :
Pretouch sensors are capable to classify objects and estimate their position prior to touching and thus close the gap between vision and contact based sensing. This will be particularly useful for robotics applications, not just for manipulation of objects but also with respect to safety. As robots will more and more operate in “open environments” where there is little prior knowledge it will be important to gather as much information on the environment as possible. However, although there are many measurement principles that might be applied, only a few can cope with the requirements, e.g., limitations with respect to spatial dimensions, weight and power consumption. In this paper we investigate a measurement system for ferromagnetic materials, which are common in many industrial applications. Inspired by magnetic field tomography we use a permanent magnet and apply GMR sensors to measure the field deformation caused by ferromagnetic objects. Based on the measurement results we solve an inverse problem with respect to the object position. We present experimental results for a prototype implementation and provide a description of the calibration method.
Keywords :
Gaussian processes; ferromagnetic materials; inverse problems; magnetic sensors; manipulators; maximum likelihood estimation; regression analysis; GMR based magnetic pretouch sensing system; Gaussian regression method; calibration method; contact based sensing; ferromagnetic materials; giant magnetic resistor sensors; inverse problem; magnetic field tomography; maximum likelihood estimator; measurement system; object classification; permanent magnet; position estimation; robot grasper; Calibration; Magnetic domains; Magnetic sensors; Maximum likelihood estimation; Robot sensing systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International
Conference_Location :
Graz
ISSN :
1091-5281
Print_ISBN :
978-1-4577-1773-4
Type :
conf
DOI :
10.1109/I2MTC.2012.6229681
Filename :
6229681
Link To Document :
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