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71 to 80 of 2,423 Results
regression_identified_parameters_IC.tab
May 28, 2025 - Replication Data for: A Nonlinear Elasticity Model and Feedforward Compensation Method to Increase Positioning Accuracy of Industrial Robots
Tabular Data - 3.6 KB - 8 Variables, 37 Observations - UNF:6:5/4ZOEzZ83GUpVNorbB0nA==
Nominal values, IC's and identifeid parameters
regression_set.tab
May 28, 2025 - Replication Data for: A Nonlinear Elasticity Model and Feedforward Compensation Method to Increase Positioning Accuracy of Industrial Robots
Tabular Data - 314.8 KB - 18 Variables, 999 Observations - UNF:6:NyhOBCwJV9EwEavFylCpAA==
Figure 3. Regression data set. Lasertracker data: cartesian position of the Target (T) in the lasertracker's coordinate system (LT) x_LT_T: x value [m] y_LT_T: y value [m] z_LT_T: z value [m] Transformation in the robot's coordinate system (0): x_0_T: x value [m] y_0_T: y value [m] z_0_T: z value [m] Disclaimer: x_0_T, y_0_T, and z_0_T were calc...
validation_set.tab
May 28, 2025 - Replication Data for: A Nonlinear Elasticity Model and Feedforward Compensation Method to Increase Positioning Accuracy of Industrial Robots
Tabular Data - 123.3 KB - 18 Variables, 391 Observations - UNF:6:0XBMsErN972oRRSt9ehQpg==
Figure 11.. Validation data set. Lasertracker data: cartesian position of the Target (T) in the lasertracker's coordinate system (LT) x_LT_T: x value [m] y_LT_T: y value [m] z_LT_T: z value [m] Transformation in the robot's coordinate system (0): x_0_T: x value [m] y_0_T: y value [m] z_0_T: z value [m] Disclaimer: x_0_T, y_0_T, and z_0_T were ca...
analyze.py
May 27, 2025 - Replication Data for: Adaptive Preload Control of Cable-Driven Parallel Robots for Handling Task
Python Source Code - 1.5 KB - MD5: e45f9fb29e57021570e898478b4495be
python functions to import csv files
apc.py
May 27, 2025 - Replication Data for: Adaptive Preload Control of Cable-Driven Parallel Robots for Handling Task
Python Source Code - 1.7 KB - MD5: a56b742555a89c56f080b3ca83076db9
python class for simulation study of adaptive preload control (apc)
COPacabana.xml
May 27, 2025 - Replication Data for: Adaptive Preload Control of Cable-Driven Parallel Robots for Handling Task
XML - 11.6 KB - MD5: 65ef377004e7c8270a6cbdf1ad1be155
geometry, control, and platform parameters of the cable robot COPacabana at ISW
experiment_apc.csv
May 27, 2025 - Replication Data for: Adaptive Preload Control of Cable-Driven Parallel Robots for Handling Task
Comma Separated Values - 654.8 KB - MD5: fbee282713e58d9a336e35ce10ff0eec
measurement data of the apc experiment
experiment_APC.mp4
May 27, 2025 - Replication Data for: Adaptive Preload Control of Cable-Driven Parallel Robots for Handling Task
MPEG-4 Video - 198.1 MB - MD5: 68fc16f1e367b5d47d5a67294cf32168
video of the experiment with adaptive preload control approach (APC)
experiment.nc
May 27, 2025 - Replication Data for: Adaptive Preload Control of Cable-Driven Parallel Robots for Handling Task
Network Common Data Form - 1.9 KB - MD5: 8fa9666131c4eae07c2796aa678d35c9
NC motion file of the experiment
experiment.pdf
experiment.pdf
May 27, 2025 - Replication Data for: Adaptive Preload Control of Cable-Driven Parallel Robots for Handling Task
Adobe PDF - 104.4 KB - MD5: 76c51dff957b150ec8611c5d22973d76
plot of experimental results
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