Angle Estimation for Robotic Arms on Floating Base Using Low-Cost IMUS
Xiaolong Zhang, Eelis Peltola, Jouni Mattila
- Year
- 2018
- Citations
- 4
Abstract
An algorithm that uses low-cost inertial measurement units (IMUs) for estimating link angles for floating base robotic platforms is proposed. Each link has four IMUs attached on its surfaces, and an Extended Kalman Filter (EKF) and a Complementary Filter (CF) are used for fusing the sensors' data. The algorithm is validated with a commercial mobile working machine, which consist of six degrees-of-freedom (DOF) wheeled base platform, and a 3-DOF hydraulic anthropomorphic arm. Although there are vibrational disturbances from the machine's diesel engine and deformation of the links themselves, the measured results from the planar motion of a floating base hydraulic arm show that the accuracy of the angle estimation is impressively less than 1 degree in the root mean square (RMS) error.
Keywords
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