Robotic System Research Articles

DOE Robot Perspective: Past, Present, and Future

The master-slave robotics system was invented at Argonne National Laboratory in 1948 to protect an operator from the harmful effects of radiation. Worker safety has been the highest priority at the U.S. Department of Energy (DOE) as it continues its cleanup mission. Safety is achieved by separating the human from the nuclear source and shielding that source to a manageable level. Robotics with remote control is a natural solution for many of DOE’s cleanup tasks. Unlike conventional robotics, a remote-handling system always involves a human being within the control process. The main handling device is a manipulator because the majority of remote-handling tasks need the intuition and intelligence of a human operator. In this paper, we take a historical perspective to the technology when exploring robotic systems from the past, on what we are currently doing, and what technologies would enable new capabilities for the future. We look at past successes and failures, and we glean lessons learned that can be applied to current and upcoming robotic activities within DOE. We also take a look at some new and emerging technologies that when matured could have a positive impact on where robotics within DOE will be needed.

The Application of an Intelligent Agaricus bisporus-Harvesting Device Based on FES-YOLOv5s

To address several challenges, including low efficiency, significant damage, and high costs, associated with the manual harvesting of Agaricus bisporus, in this study, a machine vision-based intelligent harvesting device was designed according to its agronomic characteristics and morphological features. This device mainly comprised a frame, camera, truss-type robotic arm, flexible manipulator, and control system. The FES-YOLOv5s deep learning target detection model was used to accurately identify and locate Agaricus bisporus. The harvesting control system, using a Jetson Orin Nano as the main controller, adopted an S-curve acceleration and deceleration motor control algorithm. This algorithm controlled the robotic arm and the flexible manipulator to harvest Agaricus bisporus based on the identification and positioning results. To confirm the impact of vibration on the harvesting process, a stepper motor drive test was conducted using both trapezoidal and S-curve acceleration and deceleration motor control algorithms. The test results showed that the S-curve acceleration and deceleration motor control algorithm exhibited excellent performance in vibration reduction and repeat positioning accuracy. The recognition efficiency and harvesting effectiveness of the intelligent harvesting device were tested using recognition accuracy, harvesting success rate, and damage rate as evaluation metrics. The results showed that the Agaricus bisporus recognition algorithm achieved an average recognition accuracy of 96.72%, with an average missed detection rate of 2.13% and a false detection rate of 1.72%. The harvesting success rate of the intelligent harvesting device was 94.95%, with an average damage rate of 2.67% and an average harvesting yield rate of 87.38%. These results meet the requirements for the intelligent harvesting of Agaricus bisporus and provide insight into the development of intelligent harvesting robots in the industrial production of Agaricus bisporus.

Democratization in abdominal ablation therapies: The impact of percutaneous robotic assistance on accuracy-A systematic review.

Advances in medical technology have revolutionized minimally invasive procedures. This study aims to determine the status of intra-abdominal ablation therapies, focusing on outcomes regarding technique improvement and benefits related to the learning curve. A systematic search in four databases was performed in March 2024 to identify relevant studies. Endpoints included targeting accuracy, organ efficacy, safety, outcomes and technical advantages regardless of physician experience. A total of 40 studies were included. The robotic technique demonstrated significantly higher accuracy (median 1.75mm) compared to the freehand technique (median 4.50mm) (p < 0.05). RFA and MWA were the most frequently used ablation techniques, reaching a rate of 52.5% and liver was the main target organ in 77.5% of the studies. Subgroup analysis showed a median tumor size of 2.30cm, 1.40mm for the readjustments and 3.30mm for accuracy in the freehand technique. For robotic approach, the median tumor size was 1.95cm, readjustments were 0.55mm, and accuracy was 1.85mm, and no statistical difference was identified. Severe adverse events were lower with the robotic approach, and improvement in the learning curve was observed among novice physicians. Robotic-assisted ablation techniques improve accuracy and efficacy compared to freehand techniques and are easier for novices to use. This technology allows novices to achieve similar outcomes to experts, contributing to the democratization of ablation techniques. Nevertheless, more clinical trials and standardized studies are necessary to validate these findings and enable the integration of robotic systems into routine practice.

A compliant metastructure design with reconfigurability up to six degrees of freedom

Compliant mechanisms with reconfigurable degrees of freedom are gaining attention in the development of kinesthetic haptic devices, robotic systems, and mechanical metamaterials. However, available devices exhibit limited programmability and form-customizability, restricting their versatility. To address this gap, we propose a metastructure concept featuring reconfigurable motional freedom and tunable stiffness, adaptable to various form factors and applications. These devices incorporate passive flexures and actively stiffness-changing rods to modify kinematic freedom. A rational design pipeline informs the flexures’ topological arrangements, geometric parameters, and control signals based on targeted mobilities, enabling the creation of unitary joints with up to six degrees of freedom. Our demonstrative application examples include a wrist device that has an effective stiffness of 0.370 Nm/deg (unlocked state, 5% displacement) to 2.278 Nm/deg (locked state, 1% displacement) to enable dynamic joint mobility control, a haptic thimble device (2.27-52.815 Nmm−1 at 1% displacement) that mimics the sensation of touching physical materials ranging from soft gel to metal surfaces, and a wearable device composed of multiple joints tailored for the arm and hand to augment haptic experiences or facilitate muscle training. We believe the presented method can help democratize compliant metastructures development and expand their versatility for broader contexts.

Rundherddiagnostik: Fortschritt durch integrierte Tool-in-Lesion-Tomosynthese in der Roboter-Navigationsbronchoskopie

Background and Objective: As the presentation of pulmonary nodules increases, the importance of a safe and accurate method of sampling peripheral pulmonary nodules is highlighted. First-generation robotic bronchoscopy has successfully assisted navigation and improved peripheral reach during bronchoscopy. Integrating tool-in-lesion tomosynthesis (TiLT) may further improve yield. Methods: We performed a first-in-human clinical trial of a new robotic electromagnetic navigation bronchoscopy system with integrated digital tomosynthesis technology (Galaxy System, Noah Medical). Patients with moderate-risk peripheral pulmonary nodules were enrolled in the study. Robotic bronchoscopy was performed using electromagnetic navigation with TiLT-assisted lesion guidance. Non-specific results were followed up until either a clear diagnosis was achieved or repeat radiology at 6 months demonstrated stability. Results: Eighteen patients (19 nodules) were enrolled. The average lesion size was 20 mm, and the average distance from the pleura was 11.6 mm. The target was successfully reached in 100% of nodules, and the biopsy tool was visualized inside the target lesion in all cases. A confirmed specific diagnosis was achieved in 17 nodules, 13 of which were malignant. In one patient, radiological monitoring confirmed a true non-malignant result. This translates to a yield of 89.5% (strict) to 94.7% (intermediate). Complications included one pneumothorax requiring observation only and another requiring an overnight chest drain. There was one case of severe pneumonia following the procedure.

Robotic Systems for Hand Rehabilitation—Past, Present and Future

Robotic Systems for Hand Rehabilitation—Past, Present and Future

A robot in-place geometric model reconstruction method for additive manufacturing parts by fusing 3D scanner measuring data

Abstract Geometric model reconstruction of additive manufacturing (AM) parts based on in-place measurement (IPM) is meaningful in realizing the robotic post-processing of AM parts. However, the low motion accuracy of the robot and the low efficiency of the IPM system restrict the development of the in-place model reconstruction. This paper presents a reconstruction method that integrates the 3D scanner and the robotic IPM system to improve the accuracy and efficiency of the model reconstruction. First, considering the measurement errors in the robotic IPM system, an error correction model is developed by measuring the calibration ball (CB) at the boundary of the measurement space. For each CB, a modified correction matrix (MCM) is constructed based on measurement data and geometric parameters of the CB to compensate for measurement errors. Second, a CB in the measurement space is measured, and the MCMs of each CB at the boundary are combined using the neural network model. Based on the measurement data of the CB, a geometric error correction model for the entire measurement space is developed, which corrects the spatial distribution of geometric errors in the robotic IPM system and enhances its accuracy within the measurement space. Finally, a local motion algorithm based on IPM data is proposed to calibrate the large volume of point cloud data from a 3D scanner. A high-precision model of AM parts is quickly reconstructed by fusing the few high-accuracy robotic IPM data with the large volume of low-accuracy point cloud data obtained by the 3D scanner. In order to verify the effectiveness of the method proposed in this paper, the measurement experiments on the CB are conducted. The results show that the model reconstruction accuracy can reach 0.06 mm compared with point cloud data obtained by the 3D scanner. The AM concave and convex parts are measured and the manufacturing geometric accuracy is analyzed by the proposed method. Compared to the digital model, the maximum deviation of the AM concave part is 1.3864 mm, and the maximum deviation of the AM convex part is 1.6802 mm.

Application Research of Vision-Guided Grinding Robot for Wheel Hub Castings

The combination of vision and robotic grinding technology provides robots with “visual perception” capabilities that enable them to accurately locate the area to be ground and perform the grinding tasks efficiently. Based on the rough grinding requirements for wheel hub burrs proposed by a casting company, this paper investigates the application of a vision-guided grinding robot in treating burrs on wheel hub castings. First, through vision system calibration, the conversion from pixel coordinate system to robot base coordinate system is implemented, thus ensuring that the subsequently extracted burr point coordinates can be correctly mapped to the robot’s operational coordinate system. Next, the images of the burrs on wheel hub castings are collected and processed. All the burr points are extracted by applying image algorithms. In order to improve grinding accuracy, a height error compensation model is established to adjust the coordinates of the 2D-pixel points; the coordinate error after compensation was reduced by 58.33%. Subsequently, the compensated burr point trajectories are optimized by utilizing an intelligent optimization algorithm to generate the shortest grinding path. Through experimental analysis of the relationship between spindle speed and surface roughness, a grinding trajectory simulation model is constructed, and the simulation results are integrated into the robot system. Finally, actual wheel hub burr grinding experiments are performed to validate the effectiveness and practicality of the proposed solution.

Direct assessment of the influence of pose repeatability on the accuracy of dimensional measurements for computed tomography systems with high degrees of freedom

Abstract Industrial x-ray computed tomography (CT) systems with high geometric flexibility are increasingly utilized for large-scale measurement objects or challenging measurement tasks. To maintain high accuracy when deviating from the established circular scan trajectory, trajectory calibration methods using multi-sphere reference objects with known marker positions are commonly employed. These multi-sphere objects can either be scanned together with the measurement object (online trajectory calibration) or in a separate scan (offline trajectory calibration). While offline calibration increases machine time, it generally results in higher scan quality. However, a sufficient pose repeatability is necessary to ensure comparable or even superior accuracy to online calibration. In this contribution, we present a straightforward procedure to compare both types of trajectory calibration in a way that the differences of the results can directly be traced back to the influence of the pose repeatability. The multi-sphere reference object is not only used for trajectory calibration, but simultaneously as a measurement object for repeated measurements. The methodology is tested on both a twin robotic CT system and a conventional CT system that is additionally equipped with a hexapod manipulator for adaptive object tilting. Results showed, independent from the type of trajectory calibration, systematic measurement errors in the order of 10−5–10−4 of measured sphere distances and sphericity values below 50 μ m . For sphere distances, random errors were increased by a factor of 5 due to the offline trajectory calibration, but were still low ( &lt; 1 μ m ) in comparison to systematic errors and the spread of different measurement features. Overall, both investigated systems demonstrated sufficient positioning repeatability for offline trajectory calibration. The method is in general also applicable to any other types of manipulator systems used for CT devices. It provides a workflow for the decision which type of trajectory calibration is preferable for a given CT system.

Development of an Innovative Magnetorheological Gearbox for Positioning Control and Anti-Disturbance of a Robotic Arm

The robotic arm is a critical component of modern industrial manufacturing. However, its positioning performance can be hindered by overshooting and oscillation. External disturbances, including collisions or impacts with other objects, can also affect its accuracy and precision. To resolve this problem, this work integrates a compact magnetorheological (MR) bearing, which is capable of switching between locking and unlocking states utilizing the MR effect, into the gearbox of the actuation system of the robotic arm. This integration enables the gearbox (referred to as the MR gearbox) to exhibit variable damping characteristics. This controllable damping property will play an important role in improving the positioning accuracy by offering additional damping. In this study, the MR gearbox was first designed and prototyped. A characterization test was then conducted to verify its variable damping property. The classic Bouc–Wen model was used to describe the MR gearbox and then a mathematical model was established for the whole robotic arm. Additionally, a new variable damping control method was proposed for further improving the positioning precision and reducing energy consumption. As follows, the positioning and the anti-disturbance performances of the robotic arm system installed with the MR gearbox were assessed through numerical simulations and experimental tests. The result shows that the robotic arm under the new control method achieves reductions of 11.76% in overshoot, 14.73% in settling time, and 26.1% in energy consumption compared to the uncontrolled case under the step trajectory, indicating improved positioning performance.

Design of a Cost-Effective Ultrasound Force Sensor and Force Control System for Robotic Extra-Body Ultrasound Imaging

Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but is often limited by operator variability, affecting image quality and reproducibility. Robot-assisted ultrasound may provide a solution by delivering more consistent, precise, and faster scans, potentially reducing human error and healthcare costs. Effective force control is crucial in robotic ultrasound scanning to ensure consistent image quality and patient safety. However, existing robotic ultrasound systems rely heavily on expensive commercial force sensors or the integrated sensors of commercial robotic arms, limiting their accessibility. To address these challenges, we developed a cost-effective, lightweight, 3D-printed force sensor and a hybrid position–force control strategy tailored for robotic ultrasound scanning. The system integrates patient-to-robot registration, automated scanning path planning, and multi-sensor data fusion, allowing the robot to autonomously locate the patient, target the region of interest, and maintain optimal contact force during scanning. Validation was conducted using an ultrasound-compatible abdominal aortic aneurysm (AAA) phantom created from patient CT data and healthy volunteer testing. For the volunteer testing, during a 1-min scan, 65% of the forces were within the good image range. Both volunteers reported no discomfort or pain during the whole procedure. These results demonstrate the potential of the system to provide safe, precise, and autonomous robotic ultrasound imaging in real-world conditions.

Robotics in Elderly Healthcare: A Qualitative Analysis of 20 Recent European Research Projects

Studies foresee a dramatic increase in the elderly population of Western Europe over the next decades, putting pressure on healthcare systems. Healthcare robots are developed to facilitate independent living for elderly people. This paper aims to provide a qualitative analysis of recent projects in healthcare robotics (2008-2024) and proposes new research directions for healthcare robots for older adults. We provide an overview of current research and a roadmap for upcoming research. Our study began with a literature search using four databases. Searches were performed for articles from research projects containing the words “elderly care”, “assisted aging”, “health monitoring”, or “elderly health”. Additional exclusion criteria were used to focus on elderly healthcare and utilization of commercial robotic systems. Resulting from this endeavor, 20 recent research projects are described and categorized in this paper. Then, these projects were analyzed using thematic analysis. Our findings are summarized in common themes: most projects have a strong bias towards care robots’ functionalities; robots are often seen as outsiders in care settings; there is an emphasis on robots as commercial products; and there is some limited attention to the design and ethical aspects of care robots, but very little attention to their legal aspects. The paper concludes with key points representing a roadmap for future research addressing robotics for the elderly.

Design and Evaluation of a Leader–Follower Isomorphic Vascular Interventional Surgical Robot

Vascular interventional surgical robots (VISRs) can help doctors to avoid X-ray radiation. This paper proposes a leader–follower isomorphic robot where the structural form and operational logic are completely identical. The doctor’s operation on the leader robot is precisely replicated on the follower robot, enabling delivery and rotation capabilities. It can further achieve collaborative operation. This control system adopts a four-channel scheme based on acceleration and can achieve approximately ideal transparency. The leader–follower delivery error of the catheter/guidewire is less than 1 mm, and the leader–follower rotation error of the guidewire is less than 0.3° in an actual intervention task based on a human vascular model. Subsequently, the cumulative sum (CUSUM) method was used to evaluate the learning curve of the robot system, demonstrating that both operators could master the operation method within 10 trials. We classified operators with different operational experience using machine learning methods. The classification process includes time-frequency domain feature extraction, feature selection based on the Relief method and random forest (RF) method, and a BP neural network (NN) classifier. The results indicate that this method can achieve accuracy of 94%. This paper comprehensively discusses the robot system from the perspectives of the mechanism design, control methods, and evaluation methods, providing valuable insights for the design of related robotic systems.

Development of a Cable-Driven Bionic Spherical Joint for a Robot Wrist

Wrist movements play a crucial role in upper-limb motor tasks. As prosthetic and robotic hand technologies have evolved, increasing attention has been focused on replicating the anatomy and functionality of the wrist. Closely imitating the biomechanics and movement mechanisms of human limbs is expected to enhance the overall performance of bionic robotic hands. This study presents the design of a tendon-driven bionic spherical robot wrist, utilizing two pairs of cables that mimic antagonist muscle pairs. The cables are actuated by pulleys driven by servo motors, allowing for two primary wrist motions: flexion–extension and ulnar–radial deviation. The performance Please confirm if the “1583 Iiyama” is necessary. Same as belowof the proposed robot wrist is validated through manipulation experiments using a prototype, demonstrating its capability to achieve a full range of motion for both ulnar and radial deviation. This wrist mechanism is expected to be integrated into robotic systems, enabling greater flexibility and more human-like movement capabilities.

Research on Automatic Grasping System of Industrial Robot Based on Computer Vision

The first paper focuses on YOLOv5 model optimization for advanced image processing, cu. The second paper explores low-cost machine vision cameras, achieving 97% accuracy in grasp verification. The third paper implements SVM algorithm with ArUco markers for hand-eye calibration. The adjustments made to the connection of sensing and motion system significantly expanded the scope of the detection while maintain the accuracy of grasping.. The fourth and fifth experiments improved the existing models by adding coordinate systems and wrist-mounted cameras separately. By doing so, it is possible to catch clearer and more precise pictures of the target objects. The final two research focus on promoting the automatic aspect of the system. Utilizing two networks and corresponding datasets, for one; employing multiple innovative vision-based techniques, for another. These studies collectively demonstrate the advancement in machine vision-based robotic grasping through various technical approaches, including model optimization, hardware evaluation, and algorithm implementation for improved accuracy and efficiency.

The feasibility and short-term safety of single-site hysterectomy: a retrospective cohort study of a novel robotic platform.

Robotic-assisted laparoscopic single-site hysterectomy is popular among patients and surgeons due to good cosmetic outcomes and fast recovery. However, questions remain such as loss of triangulation and instrument collision. Our aim is to test the feasibility and safety of a purpose-designed single-site robotic surgical platform mainly in hysterectomies. We retrospectively collected patients who had undergone hysterectomy by SHURUI (SR-ENS-600) robotic surgical system in the First Affiliated Hospital of Xi'an Jiaotong University. Initial cases as control were also collected including da Vinci single-site (IS4000) and multi-port (IS3000 and IS4000) hysterectomies performed by the same surgical team. The main outcome was surgical feasibility rate (valid surgeries/total cases × 100%). Short-term post-operative outcomes and complications were recorded and compared between three groups. From Dec, 2nd, 2023 to Mar, 1st, 2024, 19 cases of hysterectomies were enrolled, including 6 myomas, 2 adenomyosis, 9 cervical high-grade squamous intraepithelial lesion/stage Ia1 cancers, and 2 stage Ia endometrial cancers. Seventeen cases of da Vinci single-site surgeries and 20 cases of multi-ports surgeries were also included for comparation. Intra-operative bleeding volume was significantly lower in SHURUI group compared with da Vinci single-site and multi-ports groups (40.5mL vs 47.4mL vs 58.5mL, P = 0.046 and 0.028). Post-operative time to flatus was also shorter in SHURUI group compared with da Vinci single-site and multi-port surgeries (22.9h vs. 33.5h vs. 28.6h, P = 0.054 and 0.001). Follow-up for SHURUI group lasted for 3months with no complications. SHURUI robotic surgery was feasible and safe in hysterectomies. It also had comparable outcomes with da Vinci robotic platform and approaches.

Study of Bionic Tactile Sensors in Flexible Robots

This research investigates the advancement and implementation of bio-inspired tactile and mechanosensory systems, drawing inspiration from sophisticated biological mechanisms found in nature, particularly human sensory networks and the Venus flytrap's rapid response system. The study demonstrates significant progress in developing highly sensitive and precise sensor technologies that effectively mimic natural sensing capabilities. Through innovative material combinations and structural designs, including hybrid graphene-based platforms and advanced piezoelectric tactile arrays, these sensing systems achieve enhanced detection of mechanical forces, subtle vibrations, and environmental fluctuations. The research findings indicate substantial improvements in sensor performance metrics, including response time, sensitivity threshold, and signal-to-noise ratio. Current challenges in manufacturing scalability and cost-effectiveness are addressed, with proposed solutions for large-scale production and seamless system integration. The study outlines promising applications across multiple fields, from advanced prosthetic limbs with enhanced tactile feedback to sophisticated robotic systems capable of precise environmental interaction. Future research directions emphasize the development of more robust and adaptable sensing platforms, focusing on improved durability, reduced power consumption, and enhanced integration capabilities for next-generation biosensing applications.

Collision avoidance and routing based on location access (CARLA) of mobile robots

Abstract The paper introduces a new path-planning robotic system methodology called Collision Avoidance and Routing based on Location Access (CARLA) for use in critical environments such as hospitals and crises where quick action and saving human lives are vital. The main focus of our framework is on accuracy and fast responses, such as delivering tools or items in a specific area while avoiding collisions with other robots and obstacles. CARLA is designed to provide quick responses during emergencies, unlike most existing algorithms that are integrated into site control units or distributed among mobile robots on-site. By being loaded onto a remote server node rather than individual robots, CARLA helps to conserve the robots' capabilities, hardware resources, and power consumption. Additionally, our system utilizes cloud computing and Fog servers technology to improve data transmission times between the cloud and smart devices, especially for applications with strict timing requirements like emergency response. The Fog platform is also leveraged to enhance on-site access to real-time interaction and location-based services by bringing processing power closer to the robots from far-off Cloud servers. CARLA has various applications, such as in factories and warehouses, where mobile robots need to be selected and directed by a central control system remotely. The proposed framework consists of three main modules: Robot Knowledge Module, Robot Selection Module, and Route Reservation Module, which will all be discussed in detail in this paper. The results of simulations using this framework show that the robots have improved flexibility and efficiency in terms of computing paths and successfully fulfiling requests without colliding, compared to traditional methods used in similar scenarios.

Efficacy and learning curve of 69 cases of robot-assisted resection of retroperitoneal benign tumors

Objectives: To explore the efficacy of robotic-assisted retroperitoneal benign tumor resection and to analyze its learning curve. Methods: This is a retrospective case series study. The data of patients who underwent robotic-assisted retroperitoneal benign tumor resection from August 2015 to February 2023 at the Department of Retroperitoneal Tumor Surgery was analyzed retrospectively. There were 24 males and 45 females, with an age of (46.3±10.6) years (range: 19 to 76 years). The perioperative data, postoperative pathological results, and follow-up data were recorded. The cumulative sum (CUSUM) method was used to analyze the robotic system setup time and operative time to plot the learning curve. A linear regression model was applied to determine the best-fit curve, selecting the model with the highest R² value. Based on the vertex of the learning curve for surgical time, the patients were divided into a learning group and a mastery group. The general data and perioperative conditions of the two groups were compared. Independent sample t-tests, Mann-Whitney U tests, and χ2 tests were used for comparisons. Results: All 69 patients successfully completed the surgery without intraoperative complications. The diameter of tumors was (49.7±18.6) mm (range: 16 to 131 mm). The setup time for the robotic surgical system was (35.3±9.8) minutes (range: 20 to 61 minutes); the surgical time was (169.2±36.5) minutes (range: 70 to 305 minutes); intraoperative blood loss (M(IQR)) was 10.0 (15.0) ml (range: 2.0 to 200.0 ml). The tumors in 32 patients (46.4%) were adherent to major blood vessels. All patients were discharged without complications. The follow-up period lasted until February 2024, and no patients required reoperation, readmission, or died due to retroperitoneal benign tumors. There were no severe long-term complications, and no radiological evidence of tumor recurrence was found. The best-fit equation for the learning curve based on surgical time was CUSUM=0.010X³-1.648X²-68.573X-61.091, and the best-fit equation for the learning curve based on robotic system setup time was CUSUM=0.0018X³-0.285X²+10.460X+57.541 (where X represents the number of surgeries). The R² values of 2 learning curve models were 0.953 and 0.957, respectively, and the fit model tests had P<0.05. The inflection point of the learning curve based on surgical time was the 28th case, which is considered the minimum number of surgeries required to achieve proficiency in robotic-assisted retroperitoneal benign tumor resection. Based on this, the patients were divided into a learning group (cases 1 to 28) and a mastery group (cases 29 to 69). The surgical time for the learning group was significantly longer than that of the mastery group ((194.7±30.0) minutes vs. (151.9±31.4) minutes, t=4.126,P<0.01). No statistically significant differences were found for other parameters (all P>0.05). Conclusions: Robotic-assisted retroperitoneal benign tumor resection is feasible. The minimum number of surgeries required to achieve proficiency in overcoming the learning curve is about 28 cases.

Customer Support Automation of Ticket Creation

It has become a critical research area and innovation in itself to meet the efficiency and scale in handling customer inquiries because automation in customer support is critical. This paper comes as a robust solution toward the automatic creation of customer support tickets by using UiPath with Robotic Process Automation, or RPA. In such an approach, the proposed system will leverage the more advanced capability of UiPath automation so that all incoming queries from customers through different sources, including emails, even chatbots or social media, could be extracted, classified, and prioritized. The proposed system thus encompasses along with ZOHO application so that a good system is made ensuring it helps in extracting intent as well as related data while creating tickets seamlessly. Automated workflow eliminates human intervention, thereby cutting the time taken for processing quite appreciably and minimizing error. The automated workflow eliminates manual intervention, which cuts down the processing time quite significantly and minimizes errors. The key features are data validation, dynamic template mapping, and real-time updates to the CRM system. Experimental results show improvement in operational efficiency with 40% reduction in ticket handling time and 95% accuracy in query classification. This work opens up the possibility of scalability and flexibility of RPA-based solutions to enhance customer support processes in the future. KEYWORD: Email Parsing and Data Extraction, Integration with Ticketing Systems, Zoho application, UI path, RPA (robotic process automation systems), ticket creation, excel automation.