3-D path planning system for autonomous vehicle considering the rollover and path length

In the 3-D path planning, the undulation of terrain have a significant impact on the roll angle of autonomous vehicle (AV). However, the existing 3-D path planning methods rarely consider the roll angle, which may lead to the rollover of AV. To solve this problem, a 3-D path planning system considering the rollover and path length (3DPPS-CRPL) is presented in this work. The 3DPPS-CRPL can plan a shorter path on the basis of inhibiting the roll angle of AV. In order to inhibit the roll angle, a novel roll angle evaluation model based on the undulation of terrain is developed, and the amount of computation is also greatly reduced because complex dynamics is avoided. In order to optimize the path length, both 2-D and 3-D path length are evaluated synthetically by a path length evaluation model. In order to optimize the parameters of 3DPPS-CRPL, a fuzzy-based optimizer is proposed to determine the weight of roll angle and path length. The simulation results prove that 3DPPS-CRPL has excellent performance for inhibiting roll angle and optimizing the path length in 3-D environment.     

全球低碳汽车技术合作创新网络演化路径研究

随着全球气候变暖、能源紧张与环境污染等问题日益严峻,低碳汽车技术创新在全球范围内获得极大关注。本文以全球低碳汽车技术创新专利申请量排名前100名的领先组织为研究对象,通过专利数据挖掘,构建1992—2011年全球低碳汽车技术合作创新网络,分析全球低碳汽车技术合作创新网络特征及演化路径。研究结果表明,全球低碳汽车技术合作创新网络中行动者之间连接不紧密,信息的传播速度较慢;网络演化路径呈现网络密集度逐步提升,核心组织逐渐突显的趋势。     

蚁群算法在自动化仓库路径规划中的应用

针对复杂工作环境中的自动化仓库路径规划和协作问题,根据蚁群算法在路径选择上可以很快找到最短路径的特征,提出运用蚁群算法,建立自动化仓库路径规划模型,并进行模拟研究,得到最短路径解,同时也进一步验证了蚁群算法的有效性和实用性。     

DP-based path planning of a spherical mobile robot in an environment with obstacles

A direct approach to path planning of a 2-DOFs (Degrees of Freedom) spherical robot based on Bellman?s dynamic programming (DP) is introduced. The robot moves in an environment with obstacles and employs DP to find optimal trajectory by minimizing energy and preventing obstacle collision. While other path planning schemes rely on pre-planned optimal trajectories and/or feedback control techniques, in this approach there is no need to design a control system because DP yields the optimal control inputs in a closed loop (feedback) form. In other words, after completing the DP table, the optimal control inputs are known for every state in the admissible region and the robot can move toward the final position without colliding with obstacles. This enables the robot to function well in semi- or even non-observable environments. Results from several simulated experiments show that the proposed approach is capable of finding an optimal path from any given position/orientation towards a predefined target in an environment with obstacles within the admissible region. The method is very promising compared to other path planning schemes.     

Innovative path dependence: Making sense of product and service innovation in path dependent innovation processes

This paper analyses path dependence and path creation in firm innovation focusing on the effect of cognitive frames and organisational processes. A Northern European medical device firm is analysed through a detailed assessment of the structural and processual elements of cognitive path dependence. Cognitive schemas are analysed through development of ideal typical views on innovation and through an investigation of two specific innovation projects.Drawing on sensemaking and actor network theory the paper adds to the literature in three respects. First, it provides a more systematic analysis than available in the existing literature of how cognitive frames enable and constrain firm innovation. Second, it presents an empirical analysis that contributes to a differentiation of the concept of path dependence, distinguishing between innovative path dependence and technological path dependence. Third, the paper analyses the timing of constraints and path dependence. In the cases studied the innovation approach frames the innovation problem and constraints in relation to technologies have an impact on the innovation processes later, after new technologies have been thoroughly researched.The paper illustrates how the case firm is cognitively locked into an innovation path focused on generating ever-new product versions on different technological platforms, regardless of cannibalisation among the firm's different product versions. Despite the cognitive lock-in to an innovation path the firm is unconstrained in its choice of technological platforms and paths. Firms’ innovation processes may thus simultaneously be characterised by unrestrained search processes and myopic behaviour.     

基于跨境电商的中国新创企业国际创业路径

本文构建了基于跨境电商的国际创业路径模型,并采用跨案例研究法对鼎龙股份、中瑞思创、青岛金王三家企业的国际创业路径进行了剖析,提出了技术型、市场型与技术市场整合型三种国际创业路径。本文认为,中国新创企业应根据技术、市场、资金三方面的能力强弱,借助跨境电商优化自身相对较弱的国际创业要素,选择适合自己的国际创业路径。     

机器人路径规划及相关算法研究

路径规划是机器人学中的一个重要课题，目前的研究主要分为全局规划方法和局部规划方法两大类，全局规划方法主要是以基于构形空间的几何法和拓扑法为主；而局部规划方法主要是以基于直角坐标空间的人工势场法为主，在对一些较有代表性的研究思想及其相关算法分析的基础上，本文提出了机器人路径规划今后的研究重点。     

人工免疫算法规划复杂环境下三维飞行航迹

应用人工免疫算法规划复杂地形和火力威胁环境下的三维飞行航迹.根据实际地形的特点提取在山岭横栏的地形和多火力威胁包围的复杂场景,利用人工免疫算法的3种情况分别进行飞行器的航线设计,同时根据飞机的机动性和适航性对上述规划出的航迹进行优化;并把免疫算法3种情况的模拟结果进行比较.仿真结果表明,与遗传算法相比,人工免疫算法在规划复杂环境下三维航迹是可行的,在时间上有一定的优势.     

“区块链+”商业模式创新整合路径

区块链应用领域的研究主要集中在区块链技术与传统行业的结合，也就是“区块链+”商业模式创新，这些研究成果存在大量相互矛盾之处。这是因为现有研究由区块链出发推演商业模式创新的过程中，混淆了区块链技术、区块链特征和区块链理念三个范畴。在梳理三者边界以及相互之间关系的基础上，本文通过对三种“区块链+”共享经济商业模式创新路径的对比分析，发现由区块链集成技术和发展阶段所形成的组态决定了其与具体领域结合时表现出的商业模式新特征。这些特征一般表现为数据权、隐私和数据成本等方面，即“区块链+”商业模式创新点。进一步研究发现，“区块链+”商业模式创新的方向，例如打破垄断、独立自主和合作共赢等，与区块链创生的理念相契合。由此得出“区块链+”商业模式创新的整合路径为，区块链技术组态到具体商业模式的优化创新，再到区块链理念与商业模式理念的双向影响。形成三者循环的动态变化。本研究为不同领域“区块链+”商业模式的研究提供了理论框架，也为区块链企业的发展指明了方向。     

Dynamic path planning of mobile robot based on improved simulated annealing algorithm

Dynamic path planning for mobile robots is an urgent issue that needs to be solved because of the growing use of mobile robots in daily life and industrial operations. This work focuses on avoiding moving obstacles in dynamic situations. The computational effort required by some current algorithms makes them difficult to utilize for path planning in dynamic situations whilst the computational effort required by other methods makes them simple yet prone to local minima. In this paper, an improved simulated annealing (SA) algorithm for dynamic path planning is proposed. To reduce its computational effort, the initial path selection method and deletion operation are introduced. Simulation results show the improved SA algorithm outperforms other algorithms and provides optimal solutions in static and dynamic environments.     

基于引文网络的颠覆性技术发展路径研究

技术的发展路径研究可以在一定程度上追溯、探明和发现技术的发展方向,为技术预测提供支持,颠覆性技术作为当前国家战略的关注热点,从发展路径角度分析其特征,探寻其规律,为最终服务颠覆性技术发展具有重要意义。文章采用三方组结构模型的引文网络分析方法,结合三方组与网络遍历权值的关系,构建了基于网络论文重要性的技术颠覆性程度测度模型,实证研究了3D打印技术的三方组结构特征、网络特征及发展路径特征。研究表明,所构建的颠覆性技术发展路径测度方法能够动态测度较稳定的3D打印颠覆性程度,3D打印技术的颠覆性程度统计峰值出现在2003年,在2003年前稳步提升,2003年后保持稳定;通过三方组分析、网络分析和路径分析表明,在3D打印整体技术的一次颠覆过程中,伴随着其内部子技术的多次颠覆;在内部子技术方面,通过主路径分析发现3D打印技术的“选择性激光烧结”子技术经历了材料应用层面的多次颠覆。     

自动驾驶汽车技术轨道演进研究——基于社群识别和主路径分析的整合框架

   自动驾驶汽车技术轨道具有高度的复杂性和不确定性,对企业创新战略规划和产业政策制定带来了巨大挑战。本文基于1995—2018年自动驾驶汽车专利数据,综合运用社群分析、主路径分析等方法对自动驾驶汽车的技术热点、发展脉络和主导路径进行了系统分析,在此基础上结合主导企业战略和产业发展实践揭示了自动驾驶汽车技术轨道演进的路线、方向和驱动因素。研究发现：（1）1995年以来自动驾驶汽车领域先后形成了十个主导的技术社群,技术发展具有明显的阶段性和群组化特征。（2）自动驾驶汽车技术主导路径经历了融合-分离-再融合-再分离的过程,技术焦点从辅助驾驶向部分自动驾驶继而向复杂场景的自动驾驶技术逐渐演进。（3）当前自动驾驶汽车技术存在两种不同的演化路径和发展方向,未来的技术轨道演进将由技术、市场与政策多重因素共同决定。     

基于PSO和滚动优化的不确定环境下移动机器人动态路径规划

针对全局环境未知且存在动态障碍物情况下的移动机器人路径规划问题,本文提出了一种结合粒子群算法(PSO)和滚动优化策略的动态路径规划方法。通过在一系列移动空间窗口中进行在线规划来充分利用机器人实时测得的局部环境信息,并用粒子群算法求解每一个移动窗口内的最优路径。为及时躲避动态障碍物,提出了一种适用于动态未知环境下的适应度函数。仿真试验表明,该方法克服了现有局部路径规划方法的高复杂性的缺点,算法操作简单、具有全局寻优能力、收敛速度快、鲁棒性好,可以满足机器人在复杂的未知动态环境下路径规划的实时性要求。     

基于专利技术共现网络的纳米技术演化路径研究

基于技术共现网络分析方法,利用专利的IPC分类(国际专利分类)及其所属的技术领域信息,构建纳米技术演化路径分析框架;采用美国专利和商标局(USPTO)专利数据,分析纳米技术分支领域的演化路径,考察纳米技术与相关技术领域融合发展的实现模式,揭示纳米技术演化的规律,为我国纳米技术发展战略设计提供一定参考。     

路径依赖与锁定研究的发展脉络分析——基于科学知识图谱视角

当前有关路径依赖与锁定的研究中存在文献信息繁多、领域学科交叉复杂、发展脉络不清晰等问题。基于科学计量的可视化技术绘制科学知识图谱,探析国外人文社科领域有关路径依赖与锁定研究的发展脉络。研究发现,国外对路径依赖与锁定研究的发展脉络可归结为：①发展历程的四个阶段：政策制度-案例分析-锁定或改革-路径创造;②研究的三个热点领域：路径锁定、公司变迁、政治制度;③研究发展的三个趋势：研究层面由宏观趋向微观,研究思路从解释现象的基础研究过渡到解决问题的开发研究,研究方法由案例分析过渡到锁定模型构建。该研究系统的展示了国外路径依赖与锁定研究的全景图谱,利于研究者把握该领域的研究轨迹和选择未来研究方向。     

基于Blackboard的会展策划“小组协作式”教学模式探索

本文结合Blackboard平台的功能特点,以会展项目策划书为实践任务,利用其资料分享、信息交流、过程跟踪等功能,构建形成了从教学平台搭建、分组、过程监督、成绩考核评估,到结果分析统计的一套完整的会展策划实践＂小组＂教学模式。经过调查反馈,本教学模式能够有效提升学生的主观能动性,提高策划任务的完成质量,增强团队协作能力,为其他需要小组协同作业的课程教学提供参考和借鉴。     

Chaotic synchronization based on neural filter

Because of the high sensitivity of chaotic systems to their initial conditions, synchronization of chaotic systems with uncertain parameters has been a challenging problem especially in noisy environment. Since synchronization of the transmitter and receiver systems involves recursive estimation, recursive nonlinear filters are called for and the extended Kalman (EKF) filter and unscented Kalman (UKF) filter have been applied. However, such suboptimal filters incur high synchronization errors and provide no capacity for uncertain environment, which motivated the use of the neural filter for chaotic synchronization in this paper. The neural filter, which is a recurrent neural network, can approximate the minimum-variance to any degree. Furthermore, the neural filter can adapt to a uncertain environment without online filter weight adjustment, which is computationally efficient. Numerical experiments show that the chaotic synchronization scheme based on the neural filter outperforms those based on EKF and UKF by a large margin.     

蚁群算法在直升机航迹规划中的应用

本文介绍了一种蚁群算法（Ant Colony Optimization,ACO）在直升机航路规划中的应用,给出的n个目标点的坐标信息,利用蚁群算法计算出最短路径;并利用MFC生成最优路径。该方法直观、有效;经过多次的实验论证,有着较高的应用价值。     

The path following of intelligent unmanned vehicle scheme based on adaptive sliding mode-model predictive control

An adaptive sliding mode-model predictive control for the path following of intelligent unmanned vehicle is given in this paper. On account of excellent performances of the sliding mode structure, this algorithm can not only effectively estimate the uncertainty of the vehicle system to further improve the following accuracy, but minish the amount of calculation in comparision with model predictive control. Then, the following accuracy between the real system and the theoretical model can be compensated by the fractional order coefficient of controller. Therefore, an adaptive fractional order sliding mode-fractional order model predictive control is designed to follow the path of the intelligent unmanned vehicle. Meanwhile, the robust stability and control accuracy of the associated control algorithm are proved. Finally, different paths are designed to verify the theoretical analysis of the control performance in the controllers.     

Coordinated path following control for multi-unmanned surface vehicles with specified performance and periodic event-triggered mechanism

This paper addresses coordinated path following for underactuated multi-unmanned surface vehicles (MUSVs) with specified performance (SP) under the lumped disturbances, proposes a novel adaptive periodic event-triggered path following control strategy via relative threshold event-triggered mechanism. First, the MUSVs communicates through the directed topology cooperative control structure, and maintains a safe distance between each USV along one curve. Meanwhile, the transformed error function is applied to establish the position errors constraint, guaranteeing that the position error of each USV is confined within the specified performance in guidance system. Then, RBF neural network and adaptive parameter method are applied to estimate the lumped disturbances and its error boundary, which makes MUSVs’ coordinated system have strong anti-disturbance ability. Besides, periodic event-triggered control base on relative threshold is introduced, which not only reduces the update frequency of controller and energy consumption, also avoids Zeno behavior phenomenon. Stability analysis proves that coordinated path following control system is uniformly ultimately bounded. Comparative simulations reveal the effectiveness of the coordinated path following control scheme.