DocumentCode :
565467
Title :
Hybrid tracking of human operators using IMU/UWB data fusion by a Kalman filter
Author :
Corrales, J.A. ; Candelas, F.A. ; Torres, F.
Author_Institution :
Phys., Syst. Eng. & Signal Theor. Dept, Univ. of Alicante., Alicante, Spain
fYear :
2008
fDate :
12-15 March 2008
Firstpage :
193
Lastpage :
200
Abstract :
The precise localization of human operators in robotic workplaces is an important requirement to be satisfied in order to develop human-robot interaction tasks. Human tracking provides not only safety for human operators, but also context information for intelligent human-robot collaboration. This paper evaluates an inertial motion capture system which registers full-body movements of an user in a robotic manipulator workplace. However, the presence of errors in the global translational measurements returned by this system has led to the need of using another localization system, based on Ultra-WideBand (UWB) technology. A Kalman filter fusion algorithm which combines the measurements of these systems is developed. This algorithm unifies the advantages of both technologies: high data rates from the motion capture system and global translational precision from the UWB localization system. The developed hybrid system not only tracks the movements of all limbs of the user as previous motion capture systems, but is also able to position precisely the user in the environment.
Keywords :
Kalman filters; control engineering computing; human-robot interaction; manipulators; sensor fusion; tracking; ultra wideband technology; IMU data fusion; Kalman filter fusion algorithm; UWB data fusion; UWB localization system; full-body movement; global translational measurement; global translational precision; human operator localization; human tracking; human-robot interaction task; hybrid tracking; inertial motion capture system; intelligent human-robot collaboration; limb movement tracking; robotic manipulator workplace; robotic workplace; ultra-wideband technology; Humans; Kalman filters; Mathematical model; Position measurement; Robots; Sensors; Tracking; Kalman filter; Motion capture; UWB; data fusion; human tracking and monitoring; indoor location; inertial sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Human-Robot Interaction (HRI), 2008 3rd ACM/IEEE International Conference on
Conference_Location :
Amsterdam
ISSN :
2167-2121
Print_ISBN :
978-1-60558-017-3
Type :
conf
Filename :
6249434
Link To Document :
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