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The aim of this meta-analysis was to evaluate whether robotic pancreaticoduodenectomy (PD) may provide better clinical and pathologic outcomes compared to its open counterpart. The Pubmed, EMBASE, and Cochrane Library were systematically searched. Overall postoperative morbidity and resection margin involvement rate were the primary endpoints. Secondary endpoints included operating time, estimated blood loss (EBL), incisional surgical site infection (SSI) rate, length of hospital stay (LOS), and number of lymph nodes harvested. Twenty-four studies totaling 12,579 patients (2,175 robotic PD and 10,404 open PD were included. Overall postoperative mortality did not significantly differ [OR (95%CI) = 0.86 (0.74, 1.01); p = 0.06]. Resection margin involvement rate was significantly lower in robotic PD [15.6% vs. 19.9%; OR (95%CI) = 0.64 (0.41, 1.00); p = 0.05; NNT = 23]. Operating time was significantly longer in robotic PD [MD (95%CI) = 75.17 (48.05, 102.28); p < 0.00001]. EBL was significantly decreased in robotic PD [MD (95%CI) = − 191.35 (− 238.12, − 144.59); p < 0.00001]. Number of lymph nodes harvested was significantly higher in robotic PD [MD (95%CI) = 2.88 (1.12, 4.65); p = 0.001]. This meta-analysis found that robotic PD provides better histopathological outcomes as compared to open PD at the cost of longer operating time. Furthermore, robotic PD did not have any detrimental impact on clinical outcomes, with lower wound infection rates.

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We present a fractional order PI controller (FOPI) with SLAM method, and the proposed method is used in the simulation of navigation of NAO humanoid robot from Aldebaran. We can discretize the transfer function by the Al-Alaoui generating function and then get the FOPI controller by Power Series Expansion (PSE). FOPI can be used as a correction part to reduce the accumulated error of SLAM. In the FOPI controller, the parameters (Kp,Ki,  and  α) need to be tuned to obtain the best performance. Finally, we compare the results of position without controller and with PI controller, FOPI controller. The simulations show that the FOPI controller can reduce the error between the real position and estimated position. The proposed method is efficient and reliable for NAO navigation.

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