Variable dimensional state space based global path planning for mobile robot

A variable dimensional state space（VDSS） has been proposed to improve the re-planning time when the robotic systems operate in large unknown environments.VDSS is constructed by uniforming lattice state space and grid state space.In VDSS,the lattice state space is only used to construct search space in the local area which is a small circle area near the robot,and grid state space elsewhere.We have tested VDSS with up to 80 indoor and outdoor maps in simulation and on segbot robot platform.Through the simulation and segbot robot experiments,it shows that exploring on VDSS is significantly faster than exploring on lattice state space by Anytime Dynamic A＊（AD＊） planner and VDSS is feasible to be used on robotic systems.

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.

Energy Planning Considering the Policy Dimension Seeking for Sustainable Development

The objective of this work is to analyze the intrinsic aspects for policy dimension inside the energy planning and energy long term sustainability. In that sense, the methodology intends to take the Brazilian example as a case study and offer a somewhat unorthodox perspective on the subject of State energy planning. This matter is, beyond a purely technical question or a problem for the field of exact sciences, a point of primary interest to the field of social and human sciences. More the backbone methodology in this research is the Integrated Energy-Resources Planning (IRP), chosen for its ability to integrate both the supply and demand perspectives in the discussions about energy planning [1] [2]. A historical perspective is a guideline to approach issue: starting at the early Twentieth century, this study covers the major landmarks of the country energy concern to the present day;particularly noteworthy are the implications of the realpolitik—that is, the elements in politics that are developed within the institutional frameworks, such as governmental plans and decisions. As a result, it presents a complex picture, which we try to understand from the perspective of supply and demand integration. The originality of the study lies in the refusal to accept fallacious technical statements, as we consider the issue primarily a human and social problem, but considering the validity of technical statements that are correct.

Comparison of Dosiology between Three Dimensional Conformal and Intensity-modulated Radiotherapies (5 and 7 fields) in Gastric Cancer Post-surgery

The purpose of this study was to compare the dose distribution of intensity-modulated ra- diotherapy （IMRT） in 7 and 5 fields as well as 3-D conformal radiotherapy （3D-CRT） plans for gastric cancer using dosimetric analysis. In 15 patients with gastric cancer after D1 resection, dosimetric pa- rameters for IMRT （7 and 5 fields） and 3D-CRT were calculated with a total dose of 45 Gy （1.8 Gy/day） These parameters included the conformal index （CI）, homogeneity index （HI）, maximum dose spot for the planned target volume （PTV）, dose-volume histogram （DVH） and dose distribution in the organs at risk （OAR）, mean dose （Dmean）, maximal dose （Dmax） in the spinal cord, percentage of the normal liver volume receiving more than 30 Gy （V30） and percentage of the normal kidney volume receiving more than 20 Gy （V20）. IMRT （7 and 5 fields） and 3D-CRT achieved the PTV coverage. However, IMRT presented significantly higher CI and HI values and lower maximum dose spot distribution than 3D-CRT （P=0.001）. For dose distribution of OAR, IMRT had a significantly lower Dmean and Dmax in spinal cord than 3D-CRT （P=-0.009）. There was no obvious difference in V30 of liver and V20 of kidney between IMRT and 3D-CRT, but 5-field IMRT showed lower Dmean in the normal liver than other two plans （P=0.001）. IMRT revealed favorable tumor coverage as compared to 3D-CRT and IMRT plans. Specifically, 5-field IMRT plan was superior to 3D-CRT in protecting the spinal cord and liver, but this superiority was not observed in the kidney. Further studies are needed to compare differences among the three approaches.

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.

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.

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.

机械臂环境三维重建与避障算法研究

为了解决机器人在未知环境中的避障规划难题,提出了一种基于视觉的三维重建与避障规划方法。通过深度相机(RealSense D435i)与机械臂组成手眼系统,首先,根据目标物体与ArUco码的相对关系,通过相机获取的ArUco标记上的特征点坐标,求解出目标物姿态;然后,改进三维重建方法,通过融合机械臂工具末端位姿和多帧点云数据,对环境进行较高精度的三维重建,作为后续规划的障碍空间;最后,应用了快速扩展随机树(RRT)的改进算法进行机械臂的避障运动规划。研究搭建了仿真及控制平台,来进行验证。实验表明:环境三维建模的精度维持在8mm以内,避障成功率为96.5%,平均规划时间为1.2s,验证了方法的可行性。

融合粒子群的改进金豺算法及应用

为了解决传统金豺算法收敛精度低,搜索速度慢等问题,提出一种融合粒子群算法的改进金豺优化算法(PGJO)。首先,采用Chebyshev混沌映射和精英选择策略结合的方式对种群进行初始化,提高初始解质量;然后,结合粒子群优化算法(PSO)思想,提出一个新的搜索方式。采用动态转换策略,判断PGJO采用原Levy方式搜索还是采用新的搜索方式更新个体位置,以提高算法收敛精度;最后,提出了种群收敛监测策略,帮助算法跳出局部最优。将PGJO与其他智能优化算法经过11个基准测试函数对比实验表明,算法性能均优于其他算法。将PGJO应用于无人机路径规划当中,对比其他算法路径长度下降了3.4%,拐点个数减少了21%,验证了该算法的工程应用能力。

三维桡骨成角楔形截骨术前自动规划算法

针对桡骨成角畸形,仅凭经验很难找到准确的截骨位置,为此提出一种三维(3D)桡骨成角楔形截骨术前自动规划算法,以精确定位具体截骨位置并计算出最佳复位角度。首先,以补偿差异的对侧桡骨镜像模型为参考模板,计算骨畸形区域;其次,基于关节解剖区域的权重配准桡骨远端关节,创建旋转轴方向向量,通过三次样条插值法求解XOZ平面的畸形轮廓曲线,确定复位旋转轴方位;最后,利用单目标优化算法优化迭代,计算最优的截骨位置和复位角度,自动生成楔形截骨矫形术前计划。选择6例桡骨成角实例,以外科医生在三维空间手动截骨矫形规划方法作为实验对照组,对比关节解剖区域的配准精度。仿真结果表明,与Miyake等提出的外科医生手动截骨复位方法相比,所提算法获得的关节解剖区域的配准均方根误差(RMSE)减小0.09~0.42 mm;与Fürnstahl等提出的自动规划方法相比,所提算法可明确楔形类型,临床可行性更高。

多策略改进的猎人猎物优化算法及其应用

针对猎人猎物优化算法易陷入局部最优和收敛精度不足的问题,本文提出多策略改进的猎人猎物优化算法。该算法基于动态搜索思想,通过自适应机制从全局搜索转向局部开发;通过利用种群的历史信息来实施差分进化,从而增强种群的多样性;采用精英池策略和非线性步长相结合的方法,以防止算法陷入局部最优,并提升其收敛精度。在10个大规模(10 000维)测试函数上对改进后的算法和其他6种经典或最新的优化算法进行性能评估,结果显示,该算法在全局优化能力、寻优精度和稳定性方面均表现出色,能有效解决高维优化问题。最后,将多策略改进猎人猎物优化算法应用于三维无人机路径规划问题,仿真实验结果表明,该算法能求解到最优的无人机三维规划路径。

国土空间规划背景下“多维融合”教学模式探索——以国土空间总体规划系列课程为例

国土空间规划背景下,城乡规划专业教学需要不断更新与完善。以内蒙古工业大学城乡规划专业国土空间总体规划系列课程为例,从人才培养目标、教学团队平台、教学模式方法、教学评价体系四个方面,构建了“产学研”相融合、交叉学科理论与规划实践相融合、线上线下与多种教学方法相融合、多元化教学评价主体相融合的“多维融合”教学改革模式。为适应城乡规划发展的新要求、新形势和新使命,探索集理论、实践、方法、研究于一体的教育教学新模式。

应用差分进化-神经网络模型的杀爆弹瞄准点分配方法

为在不增加计算时耗的前提下提升多枚杀爆弹对面目标打击毁伤效能,建立融入动爆威力计算的多瞄准点规划方法.对面目标采用结构化网格划分方法实现多枚杀爆弹对目标毁伤区域的精确计算,并进行计算结果验证,基于多次计算结果采用神经网络方法建立单枚弹药对面目标毁伤区域的计算代理模型,在同样计算条件下,比非代理模型计算时间缩短1000倍;据此,通过差分进化算法实现多枚杀爆弹对面目标打击瞄准点及末端弹道参数的规划.通过实例对比分析表明:该瞄准点规划方法形成的打击方案比传统以毁伤半径为输入的方法毁伤效果大幅提升,最低提升25.5%,且单次规划时间不超过3 s,解决了瞄准点规划中毁伤效能模型复杂度与计算耗时之间的矛盾.

新课标背景下语文“命题规划”的理解与实践

为落实语文新课标理念、进一步提升命题质量,需重视命题规划。命题规划需统筹考虑多个维度,如目标要求、内容范围与水平标准、考试形式、试卷结构、题型、题量、难度、评分标准等。当前,需依据语文新课标更新部分命题规划维度的所指,从多个维度改进命题规划实践,如立足语文学习任务群立体规划考试内容,进一步贴合语文学科内容领域特性确定试题考查的认知水平,兼顾试卷的显性结构和隐性结构等。命题规划结果可根据实际需要酌情选用相应载体呈现:可以继续沿用并优化“多维细目表”,也可以编制整合分领域命题细目表与相关说明的“命题框架”,以增强命题规划的针对性与弹性。

基于改进蚁群优化算法的AUV三维路径规划

针对蚁群算法在三维路径规划时收敛速度慢且难以收敛至最优的缺点,提出一种新的改进蚁群算法,并将其应用于自主式水下机器人(autonomous underwater vehicle,AUV)三维路径规划。与现有算法相比,改进算法优点主要体现在3个方面:首先,引进伪随机状态转移概率提升算法全局搜索能力;其次,将距离和轨迹限定因子引入启发式函数,距离因子保证搜索不断趋近目标点,在轨迹限定因子约束下,轨迹累计转角更小,以此提升收敛速度和精度;最后,通过扩大信息素增量差距并逐步提高信息素衰减系数,进一步提高路径规划效率。实验结果表明,改进蚁群算法能够获得累计转角更小路径,且路径长度更小,收敛速度更快。

面向人员岸滩行进的三维路径规划算法研究

针对当前无法为人员岸滩行进提供科学合理的路径规划这一问题,论文基于蚁群算法提出了面向岸滩行进的最优路径规划算法。首先对基本的蚁群算法进行了改良,包括路径搜索方式、信息素更新策略和启发函数的合理设计等,改善了算法的收敛效率;然后定量结合多类岸滩场路径规划影响因子,构建了满足岸滩行进的代价函数;最终实现了面向岸滩行进的算法构建。该算法可为实现复杂地形条件下岸滩行进的最优路径解算和基于蚁群算法的相关三维路径规划分析研究提供参考借鉴。

基于深度强化学习的移动机器人三维路径规划方法

针对三维未知环境中存在的高复杂度和不确定性的问题,提出一种在有限观测空间优化策略下基于深度强化学习的移动机器人三维路径规划方法。首先,在有限观测空间下采用深度图信息作为智能体的输入,模拟移动受限且未知的复杂三维空间环境;其次,设计了两阶段离散动作空间下的动作选择策略,包括方向动作和位移动作,以减少搜索步数和时间;最后,在近端策略优化(PPO)算法基础上,添加门控循环单元(GRU)结合历史状态信息,以提升未知环境中搜索策略的稳定性,进而提高规划路径准确度和平滑度。实验结果表明,相较于A2C(Advantage ActorCritic),所提方法的平均搜索时间缩短了49.07%,平均规划路径长度缩短了1.04%,同时能够完成线性时序逻辑约束下的多目标路径规划任务。

民机外表面上部自主视觉检查中的降维路径规划研究

传统的民机外表面检查过程中,人工目视检查存在成本高、效率低、工作时间长等诸多不足,而带有机载视觉系统的机器人可以安全、快速、准确地检查民机外表面。本文提出一种用于民机外表面上部自主视觉检查的三维覆盖路径规划方法。通过对民机外表面上部进行初步点云获取,对机身、机翼区域切片,将三维点云映射到平面,然后进行二维覆盖路径的规划及三维空间的路径复原,快速生成优化的三维全覆盖检查路径。结果表明,该方法可以缩短三维覆盖路径规划的时间,较大程度地降低民机外表面上部自主视觉检查的成本,推动自动化检查民机表面技术的发展。

中厚板多层多道焊视觉测量与工艺规划

针对中厚板多层多道焊的焊道测量问题,提出利用焊缝检测和焊道尺寸视觉测量的信息融合自适应微调焊枪位置的方法。首先基于结构光视觉传感器系统采集焊缝图像,在典型图像处理算法的基础上,结合FROSAC提取算法提取焊缝特征信息;将提取到的特征点进行坐标转换,采用视觉测量获得焊道轮廓和尺寸信息,来修正机器人的运动路径;根据焊缝特征信息分析工艺参数对焊道成型的影响,确定焊道层数、各焊道的工艺参数以及焊枪的偏移量,完成多层多道焊接工艺规划;最后基于搭建的机器人焊接视觉系统在12 mm母材上进行V形坡口多层多道焊接试验。结果表明:该方法下坡口填充良好,焊道尺寸平均测量误差小于0.2 mm,满足多层多道焊接工业应用需求。

群体智能优化算法的区域景观规划方法

由于应用传统方法无法因地制宜地进行区域景观规划设计,导致规划后的区域景观适应度较低,因此提出基于群体智能优化算法的区域景观规划方法。采用倾斜摄影测量技术,构建区域景观三维场景,在此基础上,利用群体智能优化算法划分景观建设区域,最后从道路、建筑、水体、绿化设施等方面,得出区域景观的规划结果。将设计的规划方法应用到实际中可以发现,应用所提方法可进行区域景观优化设计,且规划后适宜度综合评分为90.47,优于对比方法,具有更好的规划效果。