Paper Info
Title
A quaternion-based Attitude Estimate System Based on a Low Power Consumption Inertial Measurement Unit.
Abstract
Accurate and real-time tracking of the orientation or attitude of rigid bodies has traditional applications in robotics, aerospace, underwater vehicles, human body motion capture, etc. Towards human body motion capture, especially wearable devices, the use of a longer time has always been a challenge for several weeks or several months continuously, so a low-cost chip and a low computational cost algorithm are necessary .The paper presented a quaternion-based algorithm that integrated the sensor output with the Kalman filtering algorithm, and a low power consumption Inertial Measurement Unit (IMU) for the attitude estimation. The low power consumption IMU with an inner Digital Motion Processor(DMP) from InvenSense Inc. called MPU9150, which contains triaxial accelerometers, triaxial gyroscopes, triaxial magnetometers and inner DMP. Firstly, we got attitude quaternion from DMP, and used the factored quaternion algorithm (FQA) to calculate course angle quaternion component. Then the Kalman Filtering algorithm was used to mix them together to acquire the accurate and good real-time performance attitude .The experimental results showed that Kalman filtering algorithm to mix DMP output and magnetometers data have better performance than gradient descent algorithm and complementary filter algorithm even in static performance and dynamic performance and power consumption.
Year
DOI
Venue
2016
10.4108/eai.14-10-2015.2261661
EAI Endorsed Trans. Energy Web
Field
DocType
Volume
Computer vision,Motion capture,Gradient descent,Gyroscope,Accelerometer,Computer science,Quaternion,Kalman filter,Inertial measurement unit,Artificial intelligence,Robotics
Journal
3
Issue
Citations 
PageRank 
9
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Yunkun Ning142.27
Liangju Li200.34
Guoru Zhao3206.50
Ying-Nan Ma442.06
Xing Gao511.45
Zongzhen Jin600.34