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Si-Lu Chen
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Thu, 01/16/2020 - 00:06
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The data is used to identify the deviation of kinematic parameters,train GPR model,record the geometric error and non-geometric error compensation result.


BD+GPR_training file:By using these data,we can get 320 residual error data after HCT+BD method is compensated. And they are used to train GPR model. 10-fold cross validation result of GPR model about x and z is obtained by using the data. we can see Figure13 and Figure14 in this paper.

Compensation results file:It expresses the compensation results in 8 test points when using four different calibration method. We can see Figure15 in this paper.

GPR_training file:By using these datas,we can get 320 error data after HCT method is compensated.

Identify_kinematic_parameter_deviation file:Using nonlinear least square method to minimize the difference  between modified position and actual position. We can get the deviation of kinematic parameters. And we can see Table 2 in this paper.


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[1] Silu Chen, "Robot_calibration_experiment_data", IEEE Dataport, 2020. [Online]. Available: Accessed: Feb. 28, 2020.
doi = {10.21227/yxdw-jp45},
url = {},
author = {Silu Chen },
publisher = {IEEE Dataport},
title = {Robot_calibration_experiment_data},
year = {2020} }
T1 - Robot_calibration_experiment_data
AU - Silu Chen
PY - 2020
PB - IEEE Dataport
UR - 10.21227/yxdw-jp45
ER -
Silu Chen. (2020). Robot_calibration_experiment_data. IEEE Dataport.
Silu Chen, 2020. Robot_calibration_experiment_data. Available at:
Silu Chen. (2020). "Robot_calibration_experiment_data." Web.
1. Silu Chen. Robot_calibration_experiment_data [Internet]. IEEE Dataport; 2020. Available from :
Silu Chen. "Robot_calibration_experiment_data." doi: 10.21227/yxdw-jp45