Identification methods for excavator arm parameters

Research output: Contribution to conferencePaperpeer-review

2 Scopus citations


This paper presents the results of a study on parameters identification of a full scale unmanned excavator vehicle. Two identification methods, the Generalized Newton method and the Least Square method are used and comparison between them in term of prediction accuracy, robustness to noise and computational speed are presented. The techniques are used to identify the link parameters (mass, inertia and length) and friction of a full-scale excavator arm. The identified parameters are compared with physical values. Further, the joint torques and positions computed by the proposed model using the identified parameters are validated against measured data. The comparison shows that the Generalized Newton method is better in term of prediction accuracy, robustness to noise and computational speed.

Original languageBritish English
Number of pages6
StatePublished - 2004
EventSICE Annual Conference 2004 - Sapporo, Japan
Duration: 4 Aug 20046 Aug 2004


ConferenceSICE Annual Conference 2004


  • Full-scale field experiment
  • Generalized Newton method
  • Least Square method
  • Parameters identification


Dive into the research topics of 'Identification methods for excavator arm parameters'. Together they form a unique fingerprint.

Cite this