DocumentCode :
1583680
Title :
Biologically inspired posture recognition and posture change detection for humanoid robots
Author :
Spranger, Michael ; Höfer, Sebastian ; Hild, Manfred
Author_Institution :
Sony CSL Paris, Paris, France
fYear :
2009
Firstpage :
562
Lastpage :
567
Abstract :
This paper presents a biologically inspired approach to posture recognition and posture change detection for a biped robot. Slow Feature Analysis, an algorithm developed by theoretical biologists for extracting slowly changing signals from signals varying on a fast time scale, is applied to the problem of recognizing the posture of biped humanoid robots over time and successively on the recognition of the change of posture. Both the recognition of basic static postures, like lying and standing, of peer robots via visual sensory information and the recognition of the same postures via internal proprioceptive sensors are considered. Given promising results in this domain we extend the application of the method onto the dynamic domain of detecting the change of posture, specifically we show the utility of the algorithm for detecting when a robot falls.
Keywords :
humanoid robots; legged locomotion; medical robotics; biologically inspired posture recognition; biped robot; humanoid robots; posture change detection; slow feature analysis; Algorithm design and analysis; Biomimetics; Change detection algorithms; Cognitive robotics; Data mining; Human robot interaction; Humanoid robots; Legged locomotion; Robot sensing systems; Signal analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-4774-9
Electronic_ISBN :
978-1-4244-4775-6
Type :
conf
DOI :
10.1109/ROBIO.2009.5420708
Filename :
5420708
Link To Document :
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