DocumentCode :
2544317
Title :
Non-drifting limb angle measurement relative to the gravitational vector during dynamic motions using accelerometers and rate gyros
Author :
Petruska, Andrew J. ; Meek, Sanford G.
Author_Institution :
Dept. of Mech. Eng., Univ. of Utah, Salt Lake City, UT, USA
fYear :
2011
fDate :
25-30 Sept. 2011
Firstpage :
3632
Lastpage :
3637
Abstract :
A method for estimating limb orientation, during static, quasi-static, and dynamic motions, by using a combination of gyroscopes and accelerometers is presented. The method uses two tri-axis accelerometers and one single axis rate gyro to calculate an estimate of angle relative to the gravitational vector independently from the rotational accelerations. This unbiased inclination estimate is blended with the angular velocity and acceleration measurements using a Kalman filter to obtain the final estimated orientation. Initially developed for implementation in a feedback control loop for control of sit-to-stand transitions in felines during direct electrical stimulation of the sciatic nerve, the method can be directly applied to other limb angle measurement tasks such as human gait analysis. The algorithm and sensor is tested on a rotational linkage with a predefined trajectory and compared to an encoder measurement with good agreement.
Keywords :
Kalman filters; acceleration control; acceleration measurement; accelerometers; angular measurement; angular velocity control; angular velocity measurement; feedback; gyroscopes; manipulator dynamics; manipulator kinematics; motion control; Kalman filter; acceleration measurement; accelerometer; angular velocity measurement; dynamic motion; encoder measurement; feedback control loop; feline; gravitational vector; human gait analysis; inclination estimation; limb orientation; nondrifting limb angle measurement; quasistatic motion; rate gyroscope; robotic manipulators; rotational acceleration; rotational linkage; sit-to-stand transition control; static motion; Acceleration; Accelerometers; Dynamics; Joints; Kalman filters; Noise; Noise measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on
Conference_Location :
San Francisco, CA
ISSN :
2153-0858
Print_ISBN :
978-1-61284-454-1
Type :
conf
DOI :
10.1109/IROS.2011.6094612
Filename :
6094612
Link To Document :
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