Many of the systems used in industry can be considered real-time systems, meaning that the validity of their outputs is related to the instant in time at which they are produced. Since the appearance of computers, real-time systems often make use of computer-assisted decision making algorithms. In this category, scheduling is one of the most extended computer-assisted decision making solutions to manage and organize the tasks they must execute and ensure real-time compliance, but it is not necessary in all cases. There are few examples of schedulers applied in biomedical robotics, usually designed for a specific machine and relying on pre-existing code libraries. We studied the different needs of a biomedical analysis robot, and we defined and modeled test protocols which mimic real processes carried out during real operation. Then, we propose the implementation of a simple scheduler for this robot and these test protocols which uses custom libraries designed to be easily ported to other similar machinery. Timing comparisons were made between an unplanned system and a planned system, concluding that the time can be reduced up to 80% by using our scheduler.

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Generic Planning Algorithm Adaptable for Order Decision to Automated Clinical Analysis Equipment

  • Plácido Fernández-Cuevas,
  • Saturnino Vicente-Diaz,
  • Antón Civit-Balcels

摘要

Many of the systems used in industry can be considered real-time systems, meaning that the validity of their outputs is related to the instant in time at which they are produced. Since the appearance of computers, real-time systems often make use of computer-assisted decision making algorithms. In this category, scheduling is one of the most extended computer-assisted decision making solutions to manage and organize the tasks they must execute and ensure real-time compliance, but it is not necessary in all cases. There are few examples of schedulers applied in biomedical robotics, usually designed for a specific machine and relying on pre-existing code libraries. We studied the different needs of a biomedical analysis robot, and we defined and modeled test protocols which mimic real processes carried out during real operation. Then, we propose the implementation of a simple scheduler for this robot and these test protocols which uses custom libraries designed to be easily ported to other similar machinery. Timing comparisons were made between an unplanned system and a planned system, concluding that the time can be reduced up to 80% by using our scheduler.