Abstract
Traditional manual dispensing of intravenous drugs needs the pharmacist to work in a pharmacy intravenous admixture services (PIVAS), leading to low efficiency, heavy physical labor, and the potential toxic drug exposure risk. There exist some automatic systems for drug dispensing. However, they may lead to inaccurate positioning and mass control due to various vial sizes and assembly errors. To solve this, this paper develops a compact dispensing platform with a six-DOF parallel robot, force sensing module, and visual servoing module for routine work in the biosafety cabinet. First, a customized robot to work inside the biosafety cabinet is developed using the configuration of 6-PSS parallel robot with three single-axis force sensors, enabling accurate needle positioning and mass control. Then, the forward and inverse kinematics are built to analyze and optimize its operational workspace and performance. Second, a visual servoing algorithm using a binocular camera is used to align the injection needle and the vial hole and a force-sensing module is incorporated onto the parallel robot to achieve real-time onsite measurement and evaluation of mass changes in the aspirated liquid. Finally, experiments are carried out to validate the effectiveness of the proposed robotic dispensing platform, and results indicate that the average positioning error is 0.41 mm, and the average mass error is 0.3 g. The developed robotic dispensing platform shows the merits of unmanned working inside the biosafety cabinet without occupying additional space, also makes accurate robotic positioning be adapted to the various sizes of commercial vials.
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Acknowledgement
This work was supported in part by the Science and Technology Commission of Shanghai Municipality (22511101602); the National Natural Science Foundation of China (62003209); the Natural Science Foundation of Shanghai (21ZR1429500); the Shanghai Rising-Star Program (22QC1401400).
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Xia, J., Lin, Z., Liu, H., Gao, A. (2023). A Six-Dof Parallel Robot-Assisted Dispensing Platform with Visual Servoing and Force Sensing for Accurate Needle Positioning and Mass Control. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14267. Springer, Singapore. https://doi.org/10.1007/978-981-99-6483-3_22
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DOI: https://doi.org/10.1007/978-981-99-6483-3_22
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