Application of A* Algorithm for Real-time Path Re-planning of an Unmanned Surface Vehicle Avoiding Underwater Obstacles

This paper describes path re-planning techniques and underwater obstacle avoidance for unmanned surface vehicle(USV) based on multi-beam forward looking sonar(FLS). Near-optimal paths in static and dynamic environments with underwater obstacles are computed using a numerical solution procedure based on an A* algorithm. The USV is modeled with a circular shape in 2 degrees of freedom(surge and yaw). In this paper, two-dimensional(2-D) underwater obstacle avoidance and the robust real-time path re-planning technique for actual USV using multi-beam FLS are developed. Our real-time path re-planning algorithm has been tested to regenerate the optimal path for several updated frames in the field of view of the sonar with a proper update frequency of the FLS. The performance of the proposed method was verified through simulations, and sea experiments. For simulations, the USV model can avoid both a single stationary obstacle, multiple stationary obstacles and moving obstacles with the near-optimal trajectory that are performed both in the vehicle and the world reference frame. For sea experiments, the proposed method for an underwater obstacle avoidance system is implemented with a USV test platform. The actual USV is automatically controlled and succeeded in its real-time avoidance against the stationary undersea obstacle in the field of view of the FLS together with the Global Positioning System(GPS) of the USV.

Investigating path loss characteristics of UWB signals in vacancy indoor environment based on time-domain technique

The path loss analysis model based on 5 rays in vacancy indoor environment is proposed. The relationship between multipath overlapping and the path loss is analyzed mathematically. Time-domain technique is introduced to compute reflection coefficient in a very short time interval. A 5 rays path loss calculation method, which is satisfactory accurate, is developed. 5 typical environments are involved to analyze and generalize the common path loss characteristics in vacancy indoor environment. The simulation result shows that the path loss can be characterized as 3 zones with different path loss exponent as distance between transmitter and receiver increasing.

Cooperative path planning for multi-AUV in time-varying ocean flows

For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning. There are still lack of authoritative indicator and method for the cooperating path planning. The calculation of the voyage time is a difficult problem in the time-varying ocean, for the existing methods of the cooperating path planning, the computation time will increase exponentially as the autonomous underwater vehicle（AUV） counts increase, rendering them unfeasible. A collaborative path planning method is presehted for multi-AUV under the influence of time-varying ocean currents based on the dynamic programming algorithm. Each AUV cooperates with the one who has the longest estimated time of sailing, enabling the arrays of AUV to get their common goal in the shortest time with minimum timedifference. At the same time, they could avoid the obstacles along the way to the target. Simulation results show that the proposed method has a promising applicability.

The Algorithm of the Time-Dependent Shortest Path Problem with Time Windows

In this paper, we present a new algorithm of the time-dependent shortest path problem with time windows. Give a directed graph , where V is a set of nodes, E is a set of edges with a non-negative transit-time function . For each node , a time window ?within which the node may be visited and ?, is non-negative of the service and leaving time of the node. A source node s, a destination node d and a departure time?t0, the time-dependent shortest path problem with time windows asks to find an s, d-path that leaves a source node s at a departure time t0;and minimizes the total arrival time at a destination node d. This formulation generalizes the classical shortest path problem in which ce are constants. Our algorithm of the time windows gave the generalization of the ALT algorithm and A* algorithm for the classical problem according to Goldberg and Harrelson [1], Dreyfus [2] and Hart et al. [3].

Nearly time-optimal paths for a ground vehicle

It is well known that the sufficient family of time-optimal paths for both Dubins' as well as Reeds-Shepp' s car models consist of the concatenation of circular arcs with maximum curvature and straight line segments, all tangentially connected. These time-optimal solutions suffer from some drawbacks. Their discontinuous curvature profile, together with the wear and impairment on the control equipment that the bang-bang solutions induce, calls for ' smoother' and more supple reference paths to follow. Avoiding the bang-bang solutions also raises the robustness with respect to any possible uncertainties. In this paper, our main tool for generating these “nearly time-optimal” , but nevertheless continuous-curvature paths, is to use the Pontryagin Maximum Principle (PMP) and make an appropriate and cunning choice of the Lagrangian function. Despite some rewarding simulation results, this concept turns out to be numerically divergent at some instances. Upon a more careful investigation, it can be concluded that the problem at hand is nearly singular. This is seen by applying the PMP to Dubins car and studying the corresponding two point boundary value problem, which turn out to be singular. Realizing this, one is able to contradict the widespread belief that all the information about the motion of a mobile platform lies in the initial values of the auxiliary variables associated with the PMP. Keywords Time-optimal paths - Motion planning - Optimal control - Pontryagin maximum principle - UGV

Real-time accurate hand path tracking and joint trajectory planning for industrial robots(Ⅰ)

Previously, researchers raised the accuracy for a robot′s hand to track a specified path in Car-tesian space mainly through increasing the number of knots on the path and the number of the path′s segments, which results in the heavier online computational burden for the robot controller. Aiming at overcoming this drawback, the authors propose a new kind of real-time accurate hand path tracking and joint trajectory planning method. Through selecting some extra knots on the specified hand path by a certain rule and introducing a sinusoidal function to the joint displacement equation of each segment, this method can greatly raise the path tracking accuracy of robot′s hand and does not change the number of the path′s segments. It also does not increase markedly the computational burden of robot controller. The result of simulation indicates that this method is very effective, and has important value in increasing the application of industrial robots.

A Constrained Time-Dependent K Shortest Paths Algorithm Addressing Overlap and Travel Time Deviation

Theoretical research often assumes all users arc homogeneous in their route choice decision and will always pick the route with the shortest travel cost,which is not necessarily the case in reality.This paper documents the research effort in developing a Constrained Time-Dependent K Shortest Paths Algorithm inorder to find K Shortest Paths between two given locations.The goal of this research is to provide sound route options to travelers in order to assist their route choice decision process,during which the overlap and travel time deviation issues between the K paths will be considered.The proposed algorithm balancing overlap and travel time deviation is developed in this research.A numerical analysis is conducted on the Tucson 1-10 network,the outcome of the case study shows that our proposed algorithm is able to find different shortest paths with a reasonable degree of similarity and close travel time,which indicates that the result of the proposed algorithm is satisfactory.

Optimal Path Finding Method Study Based on Stochastic Travel Time

Finding optimal path in a given network is an important content of intelligent transportation information service. Static shortest path has been studied widely and many efficient searching methods have been developed, for example Dijkstra’s algorithm, Floyd-Warshall, Bellman-Ford, A* et al. However, practical travel time is not a constant value but a stochastic value. How to take full use of the stochastic character to find the shortest path is a significant problem. In this paper, GPS floating car is used to detect road section’s travel time. The probability distribution of travel time is estimated according to Bayes estimation method. The combined probability distribution of a feasible route is calculated according to probability operation. The objective function is to find the route that has the biggest probability to arrive for desired time thresholds. Improved Genetic Algorithm is used to calculate the optimal path. The efficiency of the proposed method is illustrated with a practical example.

Real-time accurate hand path tracking and joint trajectory planning for industrial robots(Ⅱ)

Previously, researchers raised the accuracy for a robot′s hand to track a specified path in Cartesian space mainly through increasing the number of knots on the path and the segments of the path. But, this method resulted in the heavier on line computational burden for the robot controller. In this paper, aiming at this drawback, the authors propose a new kind of real time accurate hand path tracking and joint trajectory planning method for robots. Through selecting some extra knots on the specified hand path by a certain rule, which enables the number of knots on each segment to increase from two to four, and through introducing a sinusoidal function and a cosinoidal function to the joint displacement equation of each segment, this method can raise the path tracking accuracy of robot′s hand greatly but does not increase the computational burden of robot controller markedly.

A Multi-Hop Dynamic Path-Selection (MHDP) Algorithm for the Augmented Lifetime of Wireless Sensor Networks

In Wireless Sensor Networks (WSN), the lifetime of sensors is the crucial issue. Numerous schemes are proposed to augment the life time of sensors based on the wide range of parameters. In majority of the cases, the center of attraction will be the nodes’ lifetime enhancement and routing. In the scenario of cluster based WSN, multi-hop mode of communication reduces the communication cast by increasing average delay and also increases the routing overhead. In this proposed scheme, two ideas are introduced to overcome the delay and routing overhead. To achieve the higher degree in the lifetime of the nodes, the residual energy (remaining energy) of the nodes for multi-hop node choice is taken into consideration first. Then the modification in the routing protocol is evolved (Multi-Hop Dynamic Path-Selection Algorithm—MHDP). A dynamic path updating is initiated in frequent interval based on nodes residual energy to avoid the data loss due to path extrication and also to avoid the early dying of nodes due to elevation of data forwarding. The proposed method improves network’s lifetime significantly. The diminution in the average delay and increment in the lifetime of network are also accomplished. The MHDP offers 50% delay lesser than clustering. The average residual energy is 20% higher than clustering and 10% higher than multi-hop clustering. The proposed method improves network lifetime by 40% than clustering and 30% than multi-hop clustering which is considerably much better than the preceding methods.

基于space-time的二叉树表示动态环境中的路径规划

研究具有空间和时间的三维动态环境下的机器人路径规划分析了四叉树表示二维空间的搜索算法,在此基础上,提出采space-time,用二叉树表示二维空间的方法时间信息中增加加速度利用二叉树遍历方法和算法设计一个在动态障碍物环境下进行路径规划的新算法并,,A*,,在足球机器人系统中进行仿真,实现了较好的路径规划。

基于path RTL的弱硬实时系统

弱硬实时系统是实时系统中的一个重要研究领域.经典弱硬实时系统以任务流中任务满足或错过的个数来约束系统性能,存在着无法准确表达系统实时特性的不足,以及弱硬实时的可靠性无法证明的缺陷.通过提出弹性截止期的概念,定义基于path RTL的弱硬实时系统,有效解决了经典弱硬实时系统可靠性无法证明的难题;实现了弱硬实时系统的约束由时间特性来表达的目标;对于新兴出现的弱硬实时应用提供了完整的解决方案;同时也对经典弱硬实时系统提出了规约算法,以充分利用经典弱硬实时系统在约束规范、调度算法等方面已有研究成果.通过比较,path RTL弱硬实时系统在系统完整性、系统可靠性和应用领域等方面,比经典弱硬实时系统具有优势.

A Novel Parallel Scheme for Fast Similarity Search in Large Time Series

The similarity search is one of the fundamental components in time series data mining,e.g.clustering,classification,association rules mining.Many methods have been proposed to measure the similarity between time series,including Euclidean distance,Manhattan distance,and dynamic time warping(DTW).In contrast,DTW has been suggested to allow more robust similarity measure and be able to find the optimal alignment in time series.However,due to its quadratic time and space complexity,DTW is not suitable for large time series datasets.Many improving algorithms have been proposed for DTW search in large databases,such as approximate search or exact indexed search.Unlike the previous modified algorithm,this paper presents a novel parallel scheme for fast similarity search based on DTW,which is called MRDTW(MapRedcuebased DTW).The experimental results show that our approach not only retained the original accuracy as DTW,but also greatly improved the efficiency of similarity measure in large time series.

A STUDY ON THE ENSEMBLE FORECAST REAL-TIME CORRECTION METHOD

Using real-time correction technology for typhoons, this paper discusses real-time correction for forecasting the track of four typhoons during 2009 and 2010 in Japan, Beijing, Guangzhou, and Shanghai. It was determined that the short-time forecast effect was better than the original objective mode. By selecting four types of integration schemes after multiple mode path integration for those four objective modes, the forecast effect of the multi-mode path integration is better, on average, than any single model. Moreover, multi-mode ensemble forecasting has obvious advantages during the initial 36 h.

裁剪优化的Anytime算法

解决路径规划问题时,传统的Anytime算法有时候会遇到花费过多存储空间和计算时间的问题。该文提出的裁剪优化的Anytime算法旨在提高这两方面的性能。该算法在已有的Anytime算法的基础上,通过裁剪非均衡表中的节点来降低存储空间,然后通过分析裁剪后的节点信息来判断是否进入下次循环,以此减少计算时间。最后通过仿真试验,验证了算法的可行性和有效性。

EULER SCHEME FOR FRACTIONAL DELAY STOCHASTIC DIFFERENTIAL EQUATIONS BY ROUGH PATHS TECHNIQUES

In this note, we study a discrete time approximation for the solution of a class of delayed stochastic differential equations driven by a fractional Brownian motion with Hurst parameter H ∈(1/2,1). In order to prove convergence, we use rough paths techniques. Theoretical bounds are established and numerical simulations are displayed.

德育一体化的时代转向与可行路径——专访北京师范大学韩震教授

德育是塑造国家认同,即公民的同一性、共同性和“我们感”的重要渠道。加强大中小学德育工作一直是党和国家教育事业的重要任务。新时代背景下,大中小学德育一体化更具高度、广度与深度等特点。就高度而言,新时代德育一体化是党和国家从培养担当中华民族伟大复兴使命的时代新人的高度提出来的理念;就广度而言,新时代德育一体化是从全社会、全员、全过程、全方位参与的角度进行设计的体系;就深度而言,新时代德育一体化是在借助新的教育教学研究成果以及中国特色社会主义建设成果基础上对德育工作进行深入探索的结果。因此,开展新时代德育一体化建设可以推进和深化对德育规律的认识。未来,大中小学德育一体化建设要坚持系统观念、直面问题、守正创新,并进一步在管理机制、教材建设以及教师教学等方面狠下功夫。

大运河沿线省市文旅商产业融合发展研究——基于耦合协调、时空演进与发展路径分析

推动大运河沿线省市文旅商产业融合和高质量发展,是有效衔接国家重大发展战略的重要抓手。通过构建文旅商产业评价指标体系,测算大运河沿线省市2012-2020年文旅商产业耦合协调度,分析空间演化特征和影响路径。研究发现:研究期内大运河沿线省市文旅商融合水平整体呈现出逐年上升趋势;文旅商融合水平不同,且具有空间集聚性;在政策保障基础上及文旅商相关因素影响下,文旅商产业通过交叉、渗透和重组,从而实现产业协同发展形成文旅商产业综合体。因此,应采取差异化文旅商融合发展策略,以区域协同发展为基础,以大运河文化带建设为抓手,进一步推动大运河沿线省市形成全域统筹、区域协同的文旅商融合发展格局,实现大运河沿线省市经济社会文化高质量发展。

网络文明建设的时代语境、重要特征和实现路径

网络文明是伴随人类进入互联网时代而产生的一种新的文明形式,是人类文明的重要组成部分和重要标志,是社会发展进步的重要体现。加强网络文明建设是实施文化强国和网络强国战略的重要内容。当前,纷繁复杂的国际话语格局、风谲云诡的社会思潮持续威胁我国网络文明建设进程。基于人类文明新形态的时代语境,网络文明建设不仅是社会主义精神文明建设的现实需要,更是推进网络强国战略向纵深发展的重要抓手。网络文明建设应深刻把握党性与人民性统一的价值特征、技术驱动性与发展融合性统一的发展特征、共建性与共享性统一的实践特征和系统性与前瞻性统一的战略特征。为了高质量建设网络文明,须从顶层设计优化、内容生态建设、网络道德建设、网络法治建设和聚力科技赋能五个维度精准把握,坚持制度引领、政治导向、以德促管、依法治网和强化智治支撑,凝聚强大发展合力,构筑积极健康、向上向善的网络文化,为中国式现代化提供风清气正的网络空间与健康和谐的网络生态。