Design and Implementation of Bidirectional Dijkstra Algorithm

Bidirectional Dijkstra algorithm whose time complexity is 8O(n~2) is proposed. The theory foundation is that the classical Dijkstra algorithm has not any directional feature during searching the shortest path. The algorithm takes advantage of the adjacent link and the mechanism of bidirectional search, that is, the algorithm processes the positive search from start point to destination point and the negative search from destination point to start point at the same time. Finally, combining with the practical application of route-planning algorithm in embedded real-time vehicle navigation system (ERTVNS), one example of its practical applications is given, analysis in theory and the experimental results show that compared with the Dijkstra algorithm, the new algorithm can reduce time complexity, and guarantee the searching precision, it satisfies the needs of ERTVNS.

Improved Dijkstra Algorithm for Mobile Robot Path Planning and Obstacle Avoidance

Optimal path planning avoiding obstacles is among the most attractive applications of mobile robots(MRs)in both research and education.In this paper,an optimal collision-free algorithm is designed and implemented practically based on an improved Dijkstra algorithm.To achieve this research objectives,first,the MR obstacle-free environment is modeled as a diagraph including nodes,edges and weights.Second,Dijkstra algorithm is used offline to generate the shortest path driving the MR from a starting point to a target point.During its movement,the robot should follow the previously obtained path and stop at each node to test if there is an obstacle between the current node and the immediately following node.For this aim,the MR was equipped with an ultrasonic sensor used as obstacle detector.If an obstacle is found,the MR updates its diagraph by excluding the corresponding node.Then,Dijkstra algorithm runs on the modified diagraph.This procedure is repeated until reaching the target point.To verify the efficiency of the proposed approach,a simulation was carried out on a hand-made MR and an environment including 9 nodes,19 edges and 2 obstacles.The obtained optimal path avoiding obstacles has been transferred into motion control and implemented practically using line tracking sensors.This study has shown that the improved Dijkstra algorithm can efficiently solve optimal path planning in environments including obstacles and that STEAM-based MRs are efficient cost-effective tools to practically implement the designed algorithm.

Global optimal path planning for mobile robot based onimproved Dijkstra algorithm and ant system algorithm

A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.

A Fire Escape Simulation System Based on the Dijkstra Algorithm

Despite the support of all kinds of fire prevention measures and high-tech fire prevention equipment,fires still occur frequently because of both anthro-pogenic factors and natural disasters.This issue has drawn the attention of schools,all levels of government,and other organizations.Many types of organi-zations carry out fire drills throughout the year.Because this kind of drill cannot anticipate the specific circumstances of each fire,which are generally far more complicated than drills,most people cannot correctly choose the optimal escape route from real fires.Thus,a fire-scene virtual simulation system based on the Dijkstra algorithm is here proposed to address such problems as casualties caused by frequent fires and the inability of most people to correctly choose a fire escape route.This virtual fire escape simulation system uses Maya to carry out 3D recon-struction of the fire scene,the Unity engine to conduct interactive function design,and the Dijkstra algorithm to calculate the best escape route.The results of the example indicate that the simulation system solves the problems of the traditional simulation system,such as stiffness,lack of intelligence,and poor simulation.

Application of Dijkstra Algorithm to Proposed Tramway of a Potential World Class University

Nowadays, the development of “smart cities” with a high level of quality of life is becoming a prior challenge to be addressed. In this paper, promoting the model shift in railway transportation using tram network towards more reliable, greener and in general more sustainable transportation modes in a potential world class university is proposed. “Smart mobility” in a smart city will significantly contribute to achieving the goal of a university becoming a world class university. In order to have a regular and reliable rail system on campus, we optimize the route among major stations on campus, using shortest path problem Dijkstra algorithm in conjunction with a computer software called LINDO to arrive at the optimal route. In particular, it is observed that the shortest path from the main entrance gate (Canaan land entrance gate) to the Electrical Engineering Department is of distance 0.805 km.

Research on the Optimization and Simulation of the Shortest Path Based on Algorithm of Dijkstra

Dijkstra algorithm is a theoretical basis to solve transportation network problems of the shortest path, which has a wide range of application in path optimization. Through analyzing traditional Dijkstra algorithm,on account of the insufficiency of this algorithm in path optimization,this paper uses adjacency list and circular linked list with combination to store date,and through the improved quick sorting algorithm for weight sorting, accomplish a quick search to the adjacent node,and so an improved Dijkstra algorithm is got.Then apply it to the optimal path search,and make simulation analysis for this algorithm through the example,also verify the effectiveness of the proposed algorithm.

基于Dijkstra算法的平滑路径规划方法

移动机器人在复杂环境下沿Dijkstra算法规划的路径运动时,由于所规划的路径存在转折点多、部分转折角度小等问题,导致移动机器人不得不频繁转向,甚至要暂停才能完成转向,严重影响机器人的工作效率。利用几何拓扑学方法,结合实际场景信息,提出一种基于Dijkstra算法的平滑路径规划方法。根据应用场景获取连续化地图,将连续化地图离散化后随机生成离散点阵,计算各点之间的欧氏距离,选取与各离散点距离较近、且连线不跨越障碍的多个点,将其连接并生成离散图。在离散图中利用Dijkstra算法搜索最优路径作为引导路径。当移动机器人沿引导路径运动时,结合实际场景信息,采用几何拓扑学计算出移动机器人每一时刻应该采取的最佳动作和运行路线。实验结果表明:所提方法能够有效减少移动机器人运动中的累计转弯角度,增大最小平均转折角度,提高所规划路径的平滑度,从而缩短移动机器人的运动时间,提升机器人的工作效率。

裂缝泡沫流动特征及改进Dijkstra算法优势通道预测

泡沫在复杂缝网中的流动规律尚不明确,利用多种组合可视化裂缝模型,观察了泡沫在裂缝中的流动特征,采用改进的Dijkstra算法确定裂缝网络节点的加权图,预测了泡沫流动路径。结果表明,泡沫体积分数为90%时其流动阻力达到最大,泡沫在不同开度的平行裂缝流动时,优先在大开度裂缝中流动,在小开度的裂缝中存在气体滞留。在复杂缝网模型中,基于泡沫流体的波及范围和调堵机制对Dijkstra算法进行改进,模拟结果能够在一定程度上与实验结果进行拟合。这些发现验证了泡沫在裂缝型油藏中流动时考虑裂缝的必要性。

融合改进Dijkstra算法和动态窗口法的移动机器人路径规划

为解决移动机器人在智能制造车间的全局路径规划和局部动态避障问题,提出一种融合改进的Dijkstra算法和改进的DWA算法,对传统Dijkstra算法的路径进行平滑优化,使得路径轨迹更加平滑,动态改变DWA算法中速度评价权重函数,提高避障效率。仿真结果表明,改进Dijkstra算法路径平滑优化后,平均路程缩短比例为0.65%,平均偏航角震荡次数减少了67.70%,改进后的DWA算法运行路程缩小9.68%,路径转折次数降低了33%,运行时间缩短3.88%。基于改进的Dijkstra算法和改进的DWA算法提出一种融合算法,仿真和样机实验结果表明:面对静态、动态障碍物,机器人运行线速度平缓,轨迹光滑,角速度波动明显,证明机器人运动稳定,实时调整方位,具有良好的避障能力。并且多次机器人循环定点实验中机器人纵向(X轴方向)平均误差≤30 mm,横向(Y轴)平均误差≤30 mm,定位精度满足工业需求。

基于改进Dijkstra算法的民机信号敷设路径规划方法

针对规划电气原理信号在全机布线网络中敷设路径时存在不兼容线束通道、计算效率低、敷设路径长等问题,设计了一种基于改进Dijkstra算法的信号敷设方法。由全机布线网络建立敷设通道模型,在信号端接点处采用映射扩展连接,综合布线网络形成整体计算结构,并根据待敷设信号的隔离代码与余度动态定义线束通道的权值大小。结合Blender建模软件与某机型数据进行实例分析,结果表明:改进的Dijkstra算法能够准确地将信号敷设至兼容的线束通道中,路径搜索耗时更短,同时在信号数量较大的情况下能够得到总长度与质量更小的敷设结果。

基于Dijkstra算法的工业园区应急疏散路径规划

针对工业园区道路状况和气体泄露风险,并基于扩散模型泄漏范围的预测,应用Dijkstra算法提出了液体泄漏蒸发后的应急疏散路线规划方法。针对泄漏蒸发事故危险区域内外不同的情况生成相应的应急疏散路线。实际案例分析表明,该方案可以为工业园区提供泄漏蒸发情况下安全的疏散路线。

融合改进Dijkstra算法和MPC的单舵轮机器人路径规划

为提高单舵轮机器人在路径规划性能和路径跟踪精度,提出一种融合改进Dijkstra算法和MPC的路径规划算法。首先,对比Dijkstra算法和A^(*)算法两种方法获得的路径规划轨迹长度;随后,改进Dijkstra算法,替换与障碍物碰撞的子路径段,并对路径进行平滑优化处理;再者,建立单舵轮机器人数学模型,基于优化后的MPC算法,分别以直线和圆弧路径跟踪进行仿真。仿真实验结果表明,跟踪直线速度从1.19 m/s平稳到达1.91 m/s,角加速度为1 rad/s^(2),跟踪圆弧速度从1.19 m/s增加至2 m/s,角速度平稳变化;最后,通过样机实验结果表明,MPC算法能够使得单舵轮移动机器人运动高度贴合改进的Dijkstra算法路径规划的轨迹,且行驶平稳。

Optimizing Connections:Applied Shortest Path Algorithms for MANETs

This study is trying to address the critical need for efficient routing in Mobile Ad Hoc Networks(MANETs)from dynamic topologies that pose great challenges because of the mobility of nodes.Themain objective was to delve into and refine the application of the Dijkstra’s algorithm in this context,a method conventionally esteemed for its efficiency in static networks.Thus,this paper has carried out a comparative theoretical analysis with the Bellman-Ford algorithm,considering adaptation to the dynamic network conditions that are typical for MANETs.This paper has shown through detailed algorithmic analysis that Dijkstra’s algorithm,when adapted for dynamic updates,yields a very workable solution to the problem of real-time routing in MANETs.The results indicate that with these changes,Dijkstra’s algorithm performs much better computationally and 30%better in routing optimization than Bellman-Ford when working with configurations of sparse networks.The theoretical framework adapted,with the adaptation of the Dijkstra’s algorithm for dynamically changing network topologies,is novel in this work and quite different from any traditional application.The adaptation should offer more efficient routing and less computational overhead,most apt in the limited resource environment of MANETs.Thus,from these findings,one may derive a conclusion that the proposed version of Dijkstra’s algorithm is the best and most feasible choice of the routing protocol for MANETs given all pertinent key performance and resource consumption indicators and further that the proposed method offers a marked improvement over traditional methods.This paper,therefore,operationalizes the theoretical model into practical scenarios and also further research with empirical simulations to understand more about its operational effectiveness.

Optimal path finding algorithms based on SLSD road network model

A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is proposed.Unlike the traditional road network model,in the SLSD conceptual model,being single-directional and single-line style,a road is no longer a linkage of road nodes but abstracted as a network node.Similarly,a road node is abstracted as the linkage of two ordered single-directional roads.This model can describe turn restrictions,circular roads,and other real scenarios usually described using a super-graph.Then a computing framework for optimal path finding（OPF）is presented.It is proved that classical Dijkstra and A algorithms can be directly used for OPF computing of any real-world road networks by transferring a super-graph to an SLSD network.Finally,using Singapore road network data,the proposed conceptual model and its corresponding optimal path finding algorithms are validated using a two-step optimal path finding algorithm with a pre-computing strategy based on the SLSD road network.

基于Dijkstra算法的变电站三维电缆最优敷设模型

为了规划最短、最优电缆敷设路径,针对变电站环境复杂、空间三维避障效果较差的问题,研究基于Dijkstra算法的变电站三维电缆最优敷设模型。通过GIM软件搭建包含设备、桥梁、土建结构以及电缆通道与其连接点五大部分的变电站三维电缆敷设空间模型,经空间划分与批量埋管处理后,采用分网格法进行电缆敷设路径规划空间建模,并以电缆敷设过程中容积率限制、转弯数减少以及夹角处扇形搜索为前提,应用Dijkstra算法在路径规划空间模型中规划电缆敷设路径,获取电缆最优敷设路径。将该路径导入三维电缆敷设空间模型,获得变电站三维电缆最优敷设模型。实验结果证明:该模型可获取电缆最优敷设路径,不受变电站实地环境影响,敷设路径短且转折点少,电缆敷设避障效果好。

基于Dijkstra-ACO混合算法的煤矿井下应急逃生路径动态规划

煤矿井下应急逃生路径规划需要根据煤矿井下环境的变化及时调整,但传统方法依赖静态网络和固定权重而无法实现逃生路径规划适应井下环境动态变化。针对上述问题,提出了一种基于Dijkstra-ACO(蚁群优化)混合算法的煤矿井下应急逃生路径动态规划方法。基于巷道坡度和水位对逃生的影响分析,建立了煤矿井下应急逃生最优路径动态规划模型,实现逃生路径随巷道坡度、水位等环境变化而实时调整,从而提高逃生效率和安全性。采用Dijkstra-ACO混合算法求解煤矿井下应急逃生最优路径动态规划模型,即利用Dijkstra算法快速确定初始路径,引入ACO算法寻找距离最短且安全性最高的逃生路径,实现规划路径能够适应环境变化。搭建了模拟某煤矿多种巷道类型及其坡度、水位等参数的仿真环境,开展了应急逃生路径动态规划实验。结果表明,在50 m×100 m,100 m×200 m,150 m×250 m 3种不同尺寸的测试区域中,基于Dijkstra-ACO混合算法规划的路径长度比基于A^(*)算法和基于改进蚁群算法规划的路径长度缩短了19%以上,同时避障率提高了5%以上。

基于ArcGIS和Dijkstra算法的疏散路径优化选择

在应对紧急情况时,高效的疏散路径规划至关重要。为了积极应对水库溃坝风险,从受灾区到安全区预先为居民规划最优逃生路径具有重要的现实意义。文章基于ArcGIS在地理空间数据处理和分析方面的强大功能,以及Dijkstra算法在寻找最短路径上的原理和优势,探讨了如何将数据与Dijkstra算法相结合,以实现疏散路径的优化计算。考虑到灾害等级不同对路网的破坏程度不同,文章将路网的破坏程度划分为轻度、中度和重度3个等级,路段通行时间离散成基于灾害等级的随机变量。为了避免拥堵,将路面宽度刻画为路段通行能力作为约束,以最小通行时间为目标函数建立疏散路径优化模型,设计改进的Dijkstra算法求解模型。将该模型算法应用于福建省新罗区水库下游居民区的结果表明,该算法能够快速找到高质量解。

基于Dijkstra算法的移动机器人最短路径规划设计研究

本研究针对移动机器人的路径规划问题,结合Dijkstra算法进行了深入探讨。设计了一套针对移动机器人的最短路径规划系统,该系统全面考虑了机器人的运动约束、环境信息以及目标位置等关键因素。在此基础上,提出了一种基于Dijkstra算法的路径规划方案,旨在实现高效且精准的路径规划,为移动机器人的自主导航提供有力支持。

基于Dijkstra算法的震后路径规划软件设计

针对地震后救援人员的路径规划问题,设计一款基于Dijkstra算法的多应急配送中心、多应急需求点震后路径规划软件。该软件能够自动规划灾区救援路线,对多个需求点的物资进行合理分配,并且可根据震后路网信息的变化实时调整路线,从而减少救援时间,提高救援效率。

基于Dijkstra算法的搬运车省时路径规划研究

近年来,制造业快速向着自动化、智能化发展,智能搬运车逐渐映入我们的眼帘。随着智能搬运车的普及,其路径规划的重要性也被重视。Dijkstra算法是经典的路径规划算法之一,而传统的Dijkstra算法只能保留一条最短路径。本文对Dijkstra算法进行改进,使其能够保留所有最短路径,再将保留的所有路径进行行驶时间的计算,经计算对比筛选出耗时最短的路径。达到不仅路程短,还耗时少的目标,可以有效地节省工作时间,提高效率。