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Objectives To analyze the curative effect of TiRobot surgical robotic navigation and location system‐assisted percutaneous sacroiliac screw fixation and percutaneous sacroiliac screw by traditional fluoroscopy, and to summarize the safety and benefits of TiRobot. Methods A total of 91 patients with pelvic posterior ring fractures from December 2015 to February 2018 were included in this study. According to the surgical methods selected by the patients, the patients were divided into a TiRobot surgical robotic navigation and location system group (TiRobot group) and a percutaneous sacroiliac screw fixation group (traditional group). Statistical indicators included the number of sacroiliac screws, the time of planning the sacroiliac screw path, fluoroscopy frequency, fluoroscopy time, operation time, length of incision, blood loss, anesthesia time, the healing process of skin incisions, and fracture healing time. Fracture reduction was evaluated according to the maximum displacement degree at the inlet and outlet view X‐ray or CT. Matta standard was used to evaluate fracture reduction. At the last follow‐up, the Majeed function system was used to evaluate the function. Results All patients were followed up for 8 to 32 months. A total of 66 sacroiliac screws were implanted in the TiRobot group. A total of 43 sacroiliac screws were implanted in the traditional group. There were statistically significant differences in terms of fluoroscopy frequency, fluoroscopy time, operation time, incision length, anesthesia time, and blood loss between the two groups; the TiRobot group was superior to the traditional group. The healing time of the TiRobot group and the traditional group was 4.61 ± 0.68 months (range, 3.5–6.3 months) and 4.56 ± 0.78 months (range, 3.4–6.2 months), respectively, and there was no statistical difference. Postoperatively, by Matta standard, the overall excellent and good rate of fracture reduction was 89.28% and 88.57%, respectively. At the last follow‐up, by Majeed function score, the overall excellent and good rate was 91.07% and 91.43%. There was no statistical difference between the two groups. Conclusion Sacroiliac screw implantation assisted by TiRobot to treat the posterior pelvic ring fractures has the characteristics of less trauma, shorter operation time, and less blood loss. TiRobot has the characteristics of high safety and accuracy and has great clinical application value.

Objective To compare the clinical efficacy of intramedullary nail fixation for intertrochanteric fractures assisted by orthopaedic robot navigation and the traditional intramedullary nail fixation in elderly patients, and to investigate the application advantages of intramedullary nail fixation for femoral intertrochanteric fractures assisted by orthopaedic robot navigation in the elderly. Methods Among the 51 patients with intertrochanteric fractures who were selected from April 2015 to September 2017 in the Affiliated Hospital of Chengdu University, 25 patients underwent the intramedullary nail fixation assisted by orthopaedic robot navigation (orthopaedic robot navigation surgery group) and 26 patients underwent the traditional intramedullary nail fixation (traditional surgery group). The operation time, the number of intraoperative fluoroscopy images taken, the frequency of guide pins inserted into the femoral marrow cavity, the amount of intraoperative bleeding, and the one‐time success rate of the guide pin inserted into the femoral marrow cavity were recorded. Fracture healing and internal fixation were observed. The Harris score was used to evaluate hip joint function 1 year after surgery. Results All patients were followed up for 12–24 months. The operation time was 65.44 ± 8.01 min in the orthopaedic robot navigation surgery group and 77.50 ± 16.64 min in the traditional surgery group. The number of intraoperative fluoroscopy images taken was 10.28 ± 0.61 in the orthopaedic robot navigation surgery group and 13.23 ± 1.75 in the traditional surgery group. The frequency of guide pins inserted into the femoral marrow cavity was 1.00 ± 0.00 times in the orthopaedic robot navigation surgery group and 2.46 ± 1.10 times in the traditional surgery group. The one‐time success rate of intramedullary pin puncture was 100% (25/25) in the orthopaedic surgical robot navigation surgery group and 19.23% (5/26) in the traditional surgery group. The amount of surgical bleeding was 90.80 ± 14.98 mL in the orthopaedic robot navigation surgery group and 118.46 ± 32.21 mL in the traditional surgery group. Compared with the traditional surgery group, the operation time of the orthopaedic surgical robot navigation surgery group was shorter (P < 0.05), the number of intraoperative fluoroscopy images taken was fewer (P < 0.05), the frequency of guide pins inserted into the femoral marrow cavity was lower (P < 0.05), the one‐time success rate of intramedullary pin puncture was higher (P < 0.05), and the amount of surgical bleeding was less (P < 0.05). One year after surgery, fracture healing occurred in both groups without failure of internal fixation or fracture displacement. The Harris score of hip function in the orthopaedic robot navigation surgery group was 86.68 ± 6.23 and that in the traditional surgery group was 82.69 ± 6.85. It was higher than that in the traditional surgery group (P < 0.05). The fine rate of hip joint function in the orthopaedic robot navigation surgery group was 84.00% (21/25) and that in the traditional surgery group was 73.07% (19/26). There was no significant difference between the two groups (P > 0.05). Conclusion Intramedullary nail fixation for intertrochanteric fractures assisted by orthopaedic robot navigation in elderly patients is an ideal method, offering a short operation time, minimal surgical trauma, less radiation, and good recovery of hip function.

In precision agriculture, identification of fruit in trees is important. Furthermore, it is also essential for estimating the yield, targeting the exact location for a harvesting robot and selectively harvesting the fruit. An elliptical boundary model-based machine vision algorithm was developed to identify immature and mature pomelo fruit in trees. In the proposed solution, the images were converted from RGB space to Y′CbCr space. Then, ordinary least-squares (OLS) was introduced in fitting implicit second order polynomials of elliptical boundary models in the Cr–Cb color space for segmenting immature green fruits, mature green, green partial white, green partial yellow and green partial red fruits. Those elliptical boundary models along with area opening mathematical morphology and diameter thresholding were applied in the identification procedure. The algorithm was tested on a set of 200 validation images acquired under natural illumination conditions. The results of the validation test showed that the total correct identification rate was 93.5%. The total false positive, missed rate, repeated rate and merged rate were equal to 8.2, 6.5, 10.2 and 10.6%, respectively. The proposed method performed better in detecting mature fruit, the color of which is different from green, than in detecting immature green fruit. On average, the segmenting time for 640 × 480 and 1280 × 960 images were 0.134 and 0.200 s, respectively and the total identification time for 640 × 480 and 1280 × 960 images were 0.240 and 0.362 s, respectively.

The detection and localization of pineapple fruit must be successfully conducted to realize intelligent picking. This paper proposed a method for detecting and localizing pineapples in natural environments based on binocular stereo vision and an improved YOLO (You Only Look Once) v3 model. In comparison with the original YOLOv3, the improved algorithm did the following two improvement: the DenseNet was added into the Darknet-53 backbone network to optimize the 13 × 13 and 26 × 26 feature layer, and the SPP-net was fused in the 52 × 52 dimension detection module to strengthen the information representation ability of feature map. A binocular camera acquired left and right images. The left image was then input to the improved YOLOv3 model to obtain the position information of pineapples in the image. Stereo matching and parallax calculation of the target pineapple region were completed via the stereo matching algorithm. Finally, the three-dimensional co-ordinates of pineapples were calculated based on the triangulation principle of binocular stereo vision. A series of experiments were run to compare the detection result of this method against YOLOv3, Faster-RCNN (Region Convolutional Neural Network) and Mobilenet-SSD (Single Shot MultiBox Detector) as per their respective F1 score (Balanced Score) and AP (Average Precision) values. On test set with slight occlusion, the F1 score and AP values of the improved YOLOv3 model were 93.18% and 97.55%, respectively. As the occlusion grew severe, the F1 score and AP values decreased to 89.15% and 91.47%, respectively. The improved YOLOv3 model developed in this study had the best detection effect among all models tested. The binocular stereo vision localization experiment showed an average absolute error of 24.414 mm and average relative error of 1.17% at a distance of 1.7–2.7 m. The proposed method may thus be suitable for picking robots detecting and localizing pineapple fruit in natural environments.

The goal of this article is to experimentally study how the vibrational acceleration spreads along the branch shaken by PVC tine, steel tine, and nylon tine for citrus canopy shaking harvesting and to compare the difference. PVC tine and steel tine have potential to be used as shaking rod for citrus canopy shaking harvesting. Nylon tine is a commonly used shaking rod. A tractor-mounted canopy shaker was developed to do the trial. The shaking frequency was set at 2.5 and 5 Hz. Experimental results showed that the vibrational acceleration at the shaking spot is not the highest. Spreading from shaking spot to the stem, it increases evidently. When spreading from stems of the outside subbranch to stems of the nearest inside subbranch, its average decrease percentage is 42%. The overall vibrational acceleration of shaking at 5 Hz is 1.85 times as high as shaking at 2.5 Hz. The overall vibrational acceleration exerted by straight PVC tine and steel tine is 1.77 and 1.97 times as high as that exerted by straight nylon tine, respectively. It is indicated that replacing nylon tine with steel tine or PVC tine helps remove the fruits inside the canopy. Replacing with steel tine is more effective than with PVC tine.

A nonautomatic bamboo-splitting machine must charge with material and change tools manually. However, manual charging is very dangerous. An intelligent bamboo-splitting machine can feed automatically and change tools intelligently and has broad application prospects. A charging manipulator is an important part of an intelligent bamboo-splitting machine. The size of the manipulator was optimized here using a genetic algorithm. The capture rate, centering rate, and dynamic characteristics of an intelligent bamboo-splitting machine charging manipulator, in which key factors were considered, were experimentally studied. First, three different manipulators, with arm lengths at 210, 220, and 230 mm, were developed. Then, the bamboo materials were divided into three gradients (60–85, 85–110, and 110–135 mm) according to diameter ranges. Accelerators were used to measure the manipulator arm dynamic characteristics, and a high-speed charge-coupled device was used to record the grasping process. Experimental results showed that the manipulator capture rate with an arm length of = 220 mm was as high as 100%, but that of manipulators with arm lengths of = 210 and 230 mm was 96 and 98.67%, respectively. Thus, the manipulator with a 220 mm arm length showed better performance than the other two manipulators. Trend curves of the influence of material diameter on capture time were similar to an exponential function.

The defect rate of initially produced block bamboo (Bambusoideae) parts is >20 percent. Sorting out these defective parts manually is a highly time-consuming and tedious process. An intelligent sorting system was developed based on machine vision using a Radial Basis Function (RBF) neural network learning algorithm in this study. First, a high-speed charge-coupled device camera was used to obtain a series of images of perfect and defective block bamboo parts. Next, the RBF neural-network learning algorithm was applied to obtain defect characteristics and to locate defective parts moving forward on a conveyor belt. An array of air jets was designed to force defective parts off the belt. Experimental results showed that the average defective part removal rate of the proposed system was 91.7 percent.

In order to analyze the role of air damping in synthesized damping of litchi tree vibration, the fruit tree was simplified into a cantilever firstly. Then, according to equations of equivalent stiffness, equivalent damping, and equivalent mass, the damping ratio of air resistance was analyzed. The results showed that such damping ratio increases with the height of canopy center and the canopy size, and decreases with canopy mass and trunk radius. Within normal trunk radius, trunk length, canopy size, and canopy mass range, the damping ratio of air resistance is much smaller than 1.

To improve the positioning accuracy of picking manipulator, research of stereo vision positioning for picking object in dynamic was studied. And system composition and positioning principle of stereo vision for vibratory object were introduced. Moreover, experimental platform, which simulated the vibration while picking, was designed for the stereo vision positioning experiment in static condition or vibratory condition. Therefore, influence of vibration condition on the depth information of vision positioning can be analyzed and the regression equation of depth error can be built. The results showed that when the object vibrating, the depth error increased. The vibratory frequency was the most important factor, and the depth error would increase with the frequency increased. The influence of vibratory direction and amplitude on depth error was also significant, but much less than frequency.