This paper presents a practical and effective approach to the calibration of instrumented spatial linkages for biomechanical applications. A 6-DOF mechanical linkage with rotational transducers is designed and in-house manufactured for this purpose. In order to assess the validity of the proposed calibration technique and to distinguish between geometrical and electrical parameters uncertainties, high-precision optical encoders are used and calibration is addressed from a kinematic point of view only. The proposed technique is based on a closed-loop method, in which the end segments of the linkage are connected to each other by revolute joints. A parametrical model of the system is formulated using a standard link-to-link transformation matrices approach. Continuous data collection is carried out and a recursive identification of kinematic parameters is implemented by the use of an extended Kalman filter algorithm. Results shows that the proposed technique, despites its simplicity, is effective in improving the accuracy of the system up to its theoretically computed resolution, which limits the performance of the real system. (C) 2006 Elsevier Ltd. All rights reserved.

Validation of a calibration technique for 6-DOF instrumented spatial linkages

GATTI, Gianluca;
2007-01-01

Abstract

This paper presents a practical and effective approach to the calibration of instrumented spatial linkages for biomechanical applications. A 6-DOF mechanical linkage with rotational transducers is designed and in-house manufactured for this purpose. In order to assess the validity of the proposed calibration technique and to distinguish between geometrical and electrical parameters uncertainties, high-precision optical encoders are used and calibration is addressed from a kinematic point of view only. The proposed technique is based on a closed-loop method, in which the end segments of the linkage are connected to each other by revolute joints. A parametrical model of the system is formulated using a standard link-to-link transformation matrices approach. Continuous data collection is carried out and a recursive identification of kinematic parameters is implemented by the use of an extended Kalman filter algorithm. Results shows that the proposed technique, despites its simplicity, is effective in improving the accuracy of the system up to its theoretically computed resolution, which limits the performance of the real system. (C) 2006 Elsevier Ltd. All rights reserved.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/138081
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