A path planning method for robot patrol inspection in chemical industrial parks

Safety patrol inspection in chemical industrial parks is a complex multi-objective task with multiple degrees of freedom.Traditional pointer instruments with advantages like high reliability and strong adaptability to harsh environment,are widely applied in such parks.However,they rely on manual readings which have problems like heavy patrol workload,high labor cost,high false positives/negatives and poor timeliness.To address the above problems,this study proposes a path planning method for robot patrol in chemical industrial parks,where a path optimization model based on improved iterated local search and random variable neighborhood descent(ILS-RVND)algorithm is established by integrating the actual requirements of patrol tasks in chemical industrial parks.Further,the effectiveness of the model and algorithm is verified by taking real park data as an example.The results show that compared with GA and ILS-RVND,the improved algorithm reduces quantification cost by about 24%and saves patrol time by about 36%.Apart from shortening the patrol time of robots,optimizing their patrol path and reducing their maintenance loss,the proposed algorithm also avoids the untimely patrol of robots and enhances the safety factor of equipment.

Three-dimensional multi-constraint route planning of unmanned aerial vehicle low-altitude penetration based on coevolutionary multi-agent genetic algorithm

To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.

Three-Dimensional Computed Tomography Assessment and Planning for Severe Lower Limb Deformities: A Case Report of Bilateral Fibular Hemimelia

To correct a lower limb deformity, orthopedic surgeons must have an exact understanding of the deformity. In general, preoperative planning is carried out using anterior-posterior (AP) and lateral radiographs. However, for severe cases with a combination of angular and rotational deformities of the lower limb, obtaining true AP and lateral radiographs is difficult and accurate calculation of the rotational deformity from radiographs is impossible. In this report, we propose to focus on preoperative assessment using three-dimensional (3D) reconstruction images of computed tomography (CT) scans for severe lower limb deformity in a patient with bilateral fibular hemimelia type II according to the Achterman- Kalamchi classification. She underwent bifocal deformity corrections of the bilateral tibiae using Taylor spatial frames in combination with the Ilizarov external fixator. Complete bony union was achieved, without angular deformity or limb length discrepancy.

Cost-Benefit Assessment of Inspection and Repair Planning for Ship Structures Considering Corrosion Model Uncertainty

Owing to high costs and unnecessary inspections necessitated by the traditional inspection planning for ship structures, the risk-based inspection and repair planning should be investigated for the most cost-effective inspection. This paper aims to propose a cost-benefit assessment model of risk-based inspection and repair planning for ship structures subjected to corrosion deterioration. Then, the benefit-cost ratio is taken to be an index for the selection of the optimal inspection and repair strategy. The planning problem is formulated as an optimization problem where the benefit-cost ratio for the expected lifetime is maximized with a constraint on the minimum acceptalbe reliability index. To account for the effect of corrosion model uncertainty on the cost-benefit assessment, two corrosion models, namgly, Paik＇ s model and Guedes Soares＇ model, are adopted for analysis. A numerical example is presented to illustrate the proposed method. Sensitivity studies are also providet. The results indicate that the proposed method of risk-based cost-benefit analysis can effectively integrate the economy with reliability of the inspection and repair planning. A balance can be achieved between the risk cost and total expected inspection and repair costs with the proposed method, which is very. effective in selecting the optimal inspection and repair strategy. It is pointed out that the corrosion model uncertainty and parametric uncertaintg have a significant impact on the cost-benefit assessment of inspection and repair planning.

Minimum dose path planning for facility inspection based on the discrete Rao-combined ABC algorithm in radioactive environments with obstacles

Workers who conduct regular facility inspections in radioactive environments will inevitably be affected by radiation.Therefore,it is important to optimize the inspection path to ensure that workers are exposed to the least amount of radiation.This study proposes a discrete Rao-combined artificial bee colony(ABC)algorithm for planning inspection paths with minimum exposure doses in radioactive environments with obstacles.In this algorithm,retaining the framework of the traditional ABC algorithm,we applied the directional solution update rules of Rao algorithms at the employed bee stage and onlooker bee stage to increase the exploitation ability of the algorithm and implement discretion using the swap operator and swap sequence.To increase the randomness of solution generation,the chaos algorithm was used at the initialization stage.The K-opt operation technique was introduced at the scout bee stage to increase the exploration ability of the algorithm.For path planning in an environment with complex structural obstacles,an obstacle detour technique using a recursive algorithm was applied.To evaluate the performance of the proposed algorithm,we performed experimental simulations in three hypothetical environments and compared the results with those of improved particle swarm optimization,chaos particle swarm optimization,improved ant colony optimization,and discrete Rao’s algorithms.The experimental results show the high performance of the proposed discrete Rao-combined ABC algorithm and its obstacle detour capability.

A CAD-based inspection planning strategy for video measuring instrument

A CAD-based inspection planning strategy for video measuring instrument is proposed to improve manufacturing effec- tiveness. The system consists of a video probe that enables itself to inspect a work piece based on a CAD model. The measurement software includes CAIP module and MDP module. The CAIP module is developed based on a CAD development platform whose kernel is the Open CASCADE. The entire system was tested, and relevant examples show that the system can accomplish automatic inspection planning task for common parts efficiently.

Intraoperative application of three-dimensional printed guides in total hip arthroplasty: A systematic review

BACKGROUND Acetabular component positioning in total hip arthroplasty(THA)is of key importance to ensure satisfactory post-operative outcomes and to minimize the risk of complications.The majority of acetabular components are aligned freehand,without the use of navigation methods.Patient specific instruments(PSI)and three-dimensional(3D)printing of THA placement guides are increasingly used in primary THA to ensure optimal positioning.AIM To summarize the literature on 3D printing in THA and how they improve acetabular component alignment.METHODS PubMed was used to identify and access scientific studies reporting on different 3D printing methods used in THA.Eight studies with 236 hips in 228 patients were included.The studies could be divided into two main categories;3D printed models and 3D printed guides.RESULTS 3D printing in THA helped improve preoperative cup size planning and post-operative Harris hip scores between intervention and control groups(P=0.019,P=0.009).Otherwise,outcome measures were heterogeneous and thus difficult to compare.The overarching consensus between the studies is that the use of 3D guidance tools can assist in improving THA cup positioning and reduce the need for revision THA and the associated costs.CONCLUSION The implementation of 3D printing and PSI for primary THA can significantly improve the positioning accuracy of the acetabular cup component and reduce the number of complications caused by malpositioning.

Plans for the Development and Revision of Industry Standards on Inspection and Quarantine from 2005-2007

The inspection and quarantine standard is one of important basics to executeinspection and quarantine by laws. In recent years, with the development of economy and trade inChina, standardization has played an important role in inspection and quarantine. During 2002-2004,department of Standards of Inspection and Quarantine, Certification and Accreditation Administrationof China has organized the research of the standards of inspection and quarantine, and has builtstandard sub- systems of nine fields in inspection and quarantine.

Three-dimensional visualization and virtual reality simulation role in hepatic surgery:Further research warranted

Artificial intelligence(AI)is the study of algorithms that enable machines to analyze and execute cognitive activities including problem solving,object and word recognition,reduce the inevitable errors to improve the diagnostic accuracy,and decision-making.Hepatobiliary procedures are technically complex and the use of AI in perioperative management can improve patient outcomes as discussed below.Three-dimensional(3D)reconstruction of images obtained via ultrasound,computed tomography scan or magnetic resonance imaging,can help surgeons better visualize the surgical sites with added depth perception.Preoperative 3D planning is associated with lesser operative time and intraoperative complications.Also,a more accurate assessment is noted,which leads to fewer operative complications.Images can be converted into physical models with 3D printing technology,which can be of educational value to students and trainees.3D images can be combined to provide 3D visualization,which is used for preoperative navigation,allowing for more precise localization of tumors and vessels.Nevertheless,AI enables surgeons to provide better,personalized care for each patient.

Topological approach of liver segmentation based on 3D visualization technology in surgical planning for split liver transplantation

BACKGROUND Split liver transplantation(SLT)is a complex procedure.The left-lateral and right tri-segment splits are the most common surgical approaches and are based on the Couinaud liver segmentation theory.Notably,the liver surface following right trisegment splits may exhibit different degrees of ischemic changes related to the destruction of the local portal vein blood flow topology.There is currently no consensus on preoperative evaluation and predictive strategy for hepatic segmental necrosis after SLT.AIM To investigate the application of the topological approach in liver segmentation based on 3D visualization technology in the surgical planning of SLT.METHODS Clinical data of 10 recipients and 5 donors who underwent SLT at Shenzhen Third People’s Hospital from January 2020 to January 2021 were retrospectively analyzed.Before surgery,all the donors were subjected to 3D modeling and evaluation.Based on the 3D-reconstructed models,the liver splitting procedure was simulated using the liver segmentation system described by Couinaud and a blood flow topology liver segmentation(BFTLS)method.In addition,the volume of the liver was also quantified.Statistical indexes mainly included the hepatic vasculature and expected volume of split grafts evaluated by 3D models,the actual liver volume,and the ischemia state of the hepatic segments during the actual surgery.RESULTS Among the 5 cases of split liver surgery,the liver was split into a left-lateral segment and right trisegment in 4 cases,while 1 case was split using the left and right half liver splitting.All operations were successfully implemented according to the preoperative plan.According to Couinaud liver segmentation system and BFTLS methods,the volume of the left lateral segment was 359.00±101.57 mL and 367.75±99.73 mL,respectively,while that measured during the actual surgery was 397.50±37.97 mL.The volume of segment IV(the portion of ischemic liver lobes)allocated to the right tri-segment was 136.31±86.10 mL,as determined using the topological approach to liver segmentation.However,during the actual surgical intervention,ischemia of the right tri-segment section was observed in 4 cases,including 1 case of necrosis and bile leakage,with an ischemic liver volume of 238.7 mL.CONCLUSION 3D visualization technology can guide the preoperative planning of SLT and improve accuracy during the intervention.The simulated operation based on 3D visualization of blood flow topology may be useful to predict the degree of ischemia in the liver segment and provide a reference for determining whether the ischemic liver tissue should be removed during the surgery.

Underground space planning in Helsinki

This paper gives insight into the use of underground space in Helsinki,Finland.The city has an underground master plan(UMP) for its whole municipal area,not only for certain parts of the city.Further,the decision-making history of the UMP is described step-by-step.Some examples of underground space use in other cities are also given.The focus of this paper is on the sustainability issues related to urban underground space use,including its contribution to an environmentally sustainable and aesthetically acceptable landscape,anticipated structural longevity and maintaining the opportunity for urban development by future generations.Underground planning enhances overall safety and economy efficiency.The need for underground space use in city areas has grown rapidly since the 21 st century;at the same time,the necessity to control construction work has also increased.The UMP of Helsinki reserves designated space for public and private utilities in various underground areas of bedrock over the long term.The plan also provides the framework for managing and controlling the city’s underground construction work and allows suitable locations to be allocated for underground facilities.Tampere,the third most populated city in Finland and the biggest inland city in the Nordic countries,is also a good example of a city that is taking steps to utilise underground resources.Oulu,the capital city of northern Finland,has also started to ‘go underground’.An example of the possibility to combine two cities by an 80-km subsea tunnel is also discussed.A new fixed link would generate huge potential for the capital areas of Finland and Estonia to become a real Helsinki-Tallinn twin city.

Optimal Risk-Based Maintenance Planning of Ship Hull Structure

Various structures such as marine structures age over time. In order to always maintain safety conditions, maintenance processes including inspection and repair should be implemented on them. Corrosion and fatigue cracks are two main factors that reduce the ultimate strength of the ship's hull girder over time and thus increase the probability and risk of failure. At the time of inspection,the structural conditions must be checked so that, if necessary, the required repairs can be done on it. The main objective of this paper is to provide optimized maintenance plans of the ship structure based on probabilistic concepts with regard to corrosion and fatigue cracks. Maintenance activities increase the operational costs of ships; therefore, it is advisable to inspect and repair in the optimal times. Optimal maintenance planning of the ship structure can be conducted by formulating and solving a multi-objective optimization problem. The use of risk as a structural performance indicator has become more common in recent years. The objective functions of the optimization problem include minimizing the structure's lifecycle maintenance costs, including inspection and repair costs, and also minimizing the maximum risk of structural failure during the ship's life. In the following,to achieve better responses, reliability index has been added to the problem as the third objective function. The multi-objective optimization problem is solved using genetic algorithms. The proposed risk-based approach is applied to the hull structure of a tanker ship.

Quadratic Programming-based Approach for Autonomous Vehicle Path Planning in Space

Path planning for space vehicles is still a challenging problem although considerable progress has been made over the past decades.The major difficulties are that most of existing methods only adapt to static environment instead of dynamic one,and also can not solve the inherent constraints arising from the robot body and the exterior environment.To address these difficulties,this research aims to provide a feasible trajectory based on quadratic programming（QP） for path planning in three-dimensional space where an autonomous vehicle is requested to pursue a target while avoiding static or dynamic obstacles.First,the objective function is derived from the pursuit task which is defined in terms of the relative distance to the target,as well as the angle between the velocity and the position in the relative velocity coordinates（RVCs）.The optimization is in quadratic polynomial form according to QP formulation.Then,the avoidance task is modeled with linear constraints in RVCs.Some other constraints,such as kinematics,dynamics,and sensor range,are included.Last,simulations with typical multiple obstacles are carried out,including in static and dynamic environments and one of human-in-the-loop.The results indicate that the optimal trajectories of the autonomous robot in three-dimensional space satisfy the required performances.Therefore,the QP model proposed in this paper not only adapts to dynamic environment with uncertainty,but also can satisfy all kinds of constraints,and it provides an efficient approach to solve the problems of path planning in three-dimensional space.

新型蚁群算法规划核电厂巡检机器人路径

为了使核电厂巡检机器人更加高效地完成巡检任务,本文提出一种改进的蚁群算法进行路径规划。针对基本蚁群算法在路径规划当中存在拐点多、收敛速度慢、易陷入局部最优的问题,首先利用A~*算法构建次优路径并调整初始信息素浓度。然后,构建方向性函数以减少路径的拐弯次数。在搜索过程中,蚂蚁若发生死锁,极易导致算法陷入局部最优。为此,本文提出了防止死锁的策略,并将蚁群算法与遗传算法相结合,以提高算法的全局搜索能力。实验结果表明,本算法能够高效地规划出距离更短、更平滑的路径,对于核电厂巡检机器人高效完成巡检任务、延长单次巡检时间、减少巡检机器人磨损等具有重要意义。

多障碍环境下巡检机器人路径规划优化研究

针对大规模、密集的障碍物分布,高效地搜索最佳路径是一个挑战,为规划出更短的巡检路线,并实现多障碍环境下的灵活避障,文中提出一种多障碍环境下巡检机器人路径规划优化方法。使用二维矩阵构建巡检环境模型,应用D*算法在巡检环境模型中进行巡检机器人路径规划,并将传统D*算法中的扩展步长方式改变为自适应扩展步长,使机器人在面积较大的巡检场地能够更快地完成巡检;将代价函数由欧氏距离替换为切比雪夫诺距离和曼哈顿距离融合的代价函数,并引入了平滑度函数优化线路规划结果,使规划的路径更为平滑,在遇到由于多种原因产生的新障碍物时可以重新规划路径。通过实验结果可知,无论是静态地图还是动态地图,该方法均可以快速准确地规划出一条最佳路线,并且在多种环境中应用该方法能够高效获取路径规划结果。

农业巡检机器人路径规划研究应用现状

农业巡检机器人作为智能农业技术的一部分,能够在农业生产中执行作物监测、施肥、喷药等多种任务。其中,路径规划技术是巡检机器人自主导航和高效作业的关键技术之一,不仅影响机器人的巡检效果,还直接关系到作业效率。归纳了农业巡检机器人的路径规划研究现状,涵盖背景技术、路径规划技术及应用实例。研究发现,农业巡检机器人的路径规划研究目前还存在着计算复杂度高、三维环境下路径规划研究少、复杂环境下规划难度高等问题。针对这些问题,从优化SLAM技术、路径规划和计算能力等角度提出了建议,以期为相关领域的研究与实践提供参考。

煤矿井下水泵房巡检机器人系统设计与应用

针对煤矿井下水泵房传统工人巡检存在劳动强度大、巡检耗时较长、成本较高、检测结果不准确等问题,本文对煤矿井下水泵房智能巡检机器人系统进行研究,采用模块化和轻量化设计思想,在分析水泵房巡检内容和要求的基础上,提出了一种履带式水泵房智能巡检机器人系统,实时采集井下水泵房现场被参数信息,代替工人完成井下水泵房的巡检任务。完成了智能巡检机器人硬件系统设计,利用模块化思想编写了控制系统程序,并且编写了巡检轨迹程序,可根据设定的轨迹自主巡检。经在山西某煤矿进行现场调试和试运行表明,井下水泵房智能巡检机器人系统可代替4~6名工人实施巡检,降低了工人劳动强度,巡检周期从单日1次增加到单日3次,巡检效率大大提高,机器人本体移动定位误差≤5 cm,能准确获取设备运行异常特征并报警。

Printed Three-dimensional Anatomic Templates for Virtual Preoperative Planning Before Reconstruction of Old Pelvic Injuries： Initial Results

Background：Old pelvis fractures are among the most challenging fractures to treat because of their complex anatomy,difficult-to-access surgical sites,and the relatively low incidence of such cases.Proper evaluation and surgical planning are necessary to achieve the pelvic ring symmetry and stable fixation of the fracture.The goal of this study was to assess the use of three-dimensional （3D） printing techniques for surgical management of old pelvic fractures.Methods：First,16 dried human cadaveric pelvises were used to confirm the anatomical accuracy of the 3D models printed based on radiographic data.Next,nine clinical cases between January 2009 and April 2013 were used to evaluate the surgical reconstruction based on the 3D printed models.The pelvic injuries were all type C,and the average time from injury to reconstruction was 11 weeks （range：8-17 weeks）.The workflow consisted of.：（1） Printing patient-specific bone models based on preoperative computed tomography （CT） scans,（2） virtual fracture reduction using the printed 3D anatomic template,（3） virtual fracture fixation using Kirschner wires,and （4） preoperatively measuring the osteotomy and implant position relative to landmarks using the virtually defined deformation.These models aided communication between surgical team members during the procedure.This technique was validated by comparing the preoperative planning to the intraoperative procedure.Results：The accuracy of the 3D printed models was within specification.Production of a model from standard CT DICOM data took 7 hours （range：6-9 hours）.Preoperative planning using the 3D printed models was feasible in all cases.Good correlation was found between the preoperative planning and postoperative follow-up X-ray in all nine cases.The patients were followed for 3-29 months （median：5 months）.The fracture healing time was 9-17 weeks （mean：l0 weeks）.No delayed incision healing,wound infection,or nonunions occurred.The results were excellent in two cases,good in five,and poor in two based on the Majeed score.Conclusions：The 3D printing planning technique for pelvic surgery was successfully integrated into a clinical workflow to improve patient-specific preoperative planning by providing a visual and haptic model of the injury and allowing patient-specific adaptation of each osteosynthesis implant to the virtually reduced pelvis.

Three-dimensional path following control system for net cage inspection using bionic robotic fish

With the increasing impacts of overfishing and environmental pollution,the deep-sea cage culture of marine fishes has become an important direction of mariculture.In this paper,a tuna-like robotic fish with a three-dimensional helix path-following control system is designed for deep-sea net cage inspection.To mimic the flexibility of the fish’s movement,the kinematic model of the robotic fish adopts a tuna-like double-joint design with an addi-tional thruster device at the tail.Since the descending interval control plays a critical role in deep-sea net cage inspection,the control system utilizes the proportion integration differ-entiation(PID)based fuzzy logic control method to control the descending interval and yaw angle during the helix path movement.A polar coordinate path definition method is also proposed to simplify the reference path definition during net cage inspection.The experi-mental results demonstrates that the proposed three-dimensional path-following model can conduct net inspection task in an interferential environment and move along prede-fined reference path.

A New Fusion Chemical Reaction Optimization Algorithm Based on Random Molecules for Multi-Rotor UAV Path Planning in Transmission Line Inspection

A fusion chemical reaction optimization algorithm based on random molecules(RMCRO) is proposed to meet the special demand of power transmission line inspection. This new algorithm improves the shortcomings of chemical reaction algorithm by merging the idea of repellent-attractant rule and accelerates convergence by using difference algorithm. The molecules in this algorithm avoid obstacles and search optimal path of transmission line inspection by using sensors on multi-rotor unmanned aerial vehicle(UAV). The option of optimal path is based on potential energy of molecules and cost function without repeated parameter adjustment and complicated computation. By compared with an improved particle swarm optimization(IMPSO) in different circumstances of simulation, it can be concluded that the new algorithm presented not only can obtain more optimal path and avoid to trap in local minimum, but also can keep related sensors in a more stable status.