Robot Geometric Parameter Identification with Extended Kalman Filtering Algorithm

  • Hoai-Nhan Nguyen
  • Jian Zhou
  • Hee-Jun Kang
  • Young-Shick Ro
Part of the Communications in Computer and Information Science book series (CCIS, volume 375)


This paper proposes a calibration method for enhancing position accuracy of robotic manipulators. In order to increase the robot accuracy, the method first develops a robot kinematic model and then identifies the robot geometric parameters by using an extended Kalman filtering (EFK) algorithm. The Kalman filter has advantages in identifying geometric parameters from the noisy measurements. Therefore, the obtained kinematic parameters are more precise. A simulation study of this calibration is performed for a PUMA 560 robot to prove the effectiveness of the method in increasing robot position accuracy.


robot calibration extended Kalman filter parameter identification 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hoai-Nhan Nguyen
    • 1
  • Jian Zhou
    • 1
  • Hee-Jun Kang
    • 2
  • Young-Shick Ro
    • 2
  1. 1.Graduate School of Electrical EngineeringUniversity of UlsanUlsanKorea
  2. 2.School of Electrical EngineeringUniversity of UlsanUlsanKorea

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