Abstract
In the applications of parallel robots, kinematic calibration is required to eliminate the errors resulting from the manufacturing and assembly. In this paper, a new method for calibrating a parallel robot is proposed. An error model for kinematic calibration is constructed using differential geometry method. All leg length information and pose error are obtained based on measurement results coordinate measuring machine. A nonlinear least squares procedure is employed to determine the kinematic parameters. The parameters of the measurement error in the leg sensors are considered during kinematic modeling and parameter identification program. Experimental results presented demonstrate that the root mean square pose error can be improved at 80% with the 48 identified parameters. Key words: Parallel robot, error modeling, kinematic calibration, parameter identification, nonlinear least squares.
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