DocumentCode :
1546683
Title :
Perception and characterization of materials using signal processing techniques
Author :
Femmam, S. ; M´Sirdi, N.K. ; Ouahabi, A.
Author_Institution :
Laboratorie de Robotique de Paris, Velizy, France
Volume :
50
Issue :
5
fYear :
2001
fDate :
10/1/2001 12:00:00 AM
Firstpage :
1203
Lastpage :
1211
Abstract :
In this paper, we develop a methodology and a conceptual framework in which manipulations are undertaken for perceiving and characterizing materials. Within this framework, we distinguish different materials (unknown environments) by actively contacting and testing them, and by analyzing the resulting sounds using a microphone. For this implementation, we identify sensor-derived measures that are diagnostic of a material´s properties, and use these measures to categorize the objects (or unknown environments) in their different material class. The parameter of characterization is the internal angle of friction of the materials. This parameter is determined by the relation of strain and stress properties. Using this theoretical approach and the experimental results, we conclude that the statement of shape-invariance of materials is critical and invalid in real cases
Keywords :
acoustic signal processing; anelasticity; dexterous manipulators; internal friction; legged locomotion; robot vision; stress-strain relations; time-frequency analysis; transient analysis; ultrasonic applications; DSP card; abrupt changes detection; anelastic spring; carpet; complex modulus; discrete signal; duralumin; energy bands; first-order linear system; grasping; intelligent robot; internal angle of friction; legged robot; materials characterization; materials perception; microphone sensor; peak vibration; plastic; plexiglass; robotic approach; robotic perception; sand; sensor-derived measures; sensory modality of audition; shape-invariance; signal segmentation; soil; standard linear model; stress/strain properties; time-frequency representation; transient analysis; transient contact; ultrasonic signal analysis; unknown environments; wood; Acoustic materials; Acoustic testing; Capacitive sensors; Friction; Material properties; Materials testing; Microphones; Robots; Signal processing; Stress;
fLanguage :
English
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9456
Type :
jour
DOI :
10.1109/19.963184
Filename :
963184
Link To Document :
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