The paper focuses on the development and performance assessment of the PAUL robot, emphasizing the importance of precise kinematic modeling in pneumatic systems. A novel data acquisition strategy was implemented to manage the variability in experimental conditions, such as ambient temperature and potential pneumatic leaks. Results indicate that the automated data collection significantly enhanced the reliability and accuracy of the robot’s control. The findings stress the necessity of iterative testing in developing effective pneumatic actuation systems.
The experimentation process revealed that the size of the table for achieving accurate kinematic modeling was pivotal, requiring precise adjustments due to variability in prior literature.
The automated data collection system mitigated concerns regarding potential errors in the pneumatic actuation, allowing for consistent results despite variable factors like ambient temperature.
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