RESUMEN
In the field of robotic automation, achieving high position accuracy in robotic vision systems (RVSs) is a pivotal challenge that directly impacts the efficiency and effectiveness of industrial applications. This study introduces a comprehensive modeling approach that integrates kinematic and joint compliance factors to significantly enhance the position accuracy of a system. In the first place, we develop a unified kinematic model that effectively reduces the complexity and error accumulation associated with the calibration of robotic systems. At the heart of our approach is the formulation of a joint compliance model that meticulously accounts for the intricacies of the joint connector, the external load, and the self-weight of robotic links. By employing a novel 3D rotary laser sensor for precise error measurement and model calibration, our method offers a streamlined and efficient solution for the accurate integration of vision systems into robotic operations. The efficacy of our proposed models is validated through experiments conducted on a FANUC LR Mate 200iD robot, showcasing notable improvements in the position accuracy of robotic vision system. Our findings contribute a framework for the calibration and error compensation of RVS, holding significant potential for advancements in automated tasks requiring high precision.
RESUMEN
PURPOSE: To investigate the efficacy and accuracy of the Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) and Portsmouth-POSSUM (P-POSSUM) scoring systems in the risk assessment of postoperative complications and death in elderly patients undergoing hepatobiliary and pancreatic surgery. PATIENTS AND METHODS: Using POSSUM and P-POSSUM, 274 elderly patients undergoing hepatobiliary and pancreatic surgery were evaluated, and the complications and deaths predicted by the systems were compared with the actual situation. The accuracy and predictive ability of POSSUM and P-POSSUM were evaluated using chi-squared and t-tests, consistency of predicted and actual complication rates (observed/expected, OE ratio), and receiver operating characteristic (ROC) curve. RESULTS: The complication rate predicted by POSSUM (R1) was 22.57%, while the actual postoperative complication rate was 17.88% (P>0.05). The mortality rate predicted by POSSUM (R2) was 4.61%, while the actual rate was 1.09% (P<0.05). The mortality rate predicted by P-POSSUM (R) was 1.42%, while the actual rate was 1.09% (P>0.05). Patients with complications had higher physiology scores (PS), operative severity scores (OS), and POSSUM scores than those without complications (P<0.05). Furthermore, PS, OS, and POSSUM scores were higher in the mortality group than in the survival group. However, the number of individuals in the mortality group was too small to accurately reflect the overall situation. Stratified analysis showed that consistency of the OE ratio in different subgroups was close to 1. The ROC curve showed that the area under the curve for the complication rate predicted by POSSUM was 0.76. CONCLUSION: Although the postoperative mortality rate was higher than the actual value, POSSUM could accurately predict the postoperative complication rate in elderly patients undergoing hepatobiliary and pancreatic surgery. The P-POSSUM accurately predicted the postoperative mortality rate in this population. Patients with complications had higher POSSUM scores.