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Joint angle estimation for floating base robots utilizing MEMS IMUs

Xiaolong Zhang, Eelis Peltola, Jouni Mattila

Year
2017
Citations
5

Abstract

This paper describes a novel motion estimation algorithm for floating base manipulators that utilizes low-cost inertial measurement units (IMUs) containing a three-axis gyroscope and a three-axis accelerometer. Four strap-down microelectromechanical system (MEMS) IMUs are mounted on each link to form a virtual IMU whose body's fixed frame is located at the center of the joint rotation. An extended Kalman filter (EKF) and a complementary filter are used to develop a virtual IMU by fusing together the output of four IMUs. The novelty of the proposed algorithm is that no forward kinematic model that requires data flow from previous joints is needed. The measured results obtained from the planar motion of a hydraulic arm show that the accuracy of the estimation of the joint angle is within ± 1 degree and that the root mean square error is less than 0.5 degree.

Keywords

Inertial measurement unitForward kinematicsKinematicsKalman filterExtended Kalman filterGyroscopeAccelerometerComputer scienceControl theory (sociology)Filter (signal processing)

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