基于改进A*算法的移动机器人路径规划研究

A*算法广泛应用于移动机器人路径规划中，而传统A*算法在寻路时，普遍存在搜索时间较长、效率低下等问题，因此，采用双向搜索的方式，对传统A*算法加以改进，该算法在路径规划过程中，可同时进行正反向路径搜索，同时采用正反向搜索交替机制，保证了最终目标节点搜索在连线中点区域内相遇，从而缩短了寻路计算时间。在MATLAB平台上，针对改进后的A*算法进行仿真实验，结果证明，双向A*算法减少了规划时间，且可生成最优路径。最后，将该算法应用到基于开源机器人操作系统的Turtlebot2移动平台上，进行现场实验，实验结果表明，双向A*算法减少了寻路计算时间，从而使得路径搜索效率得到显著提升，且规划路径合理，满足路径规划要求。     

描述逻辑SHIN的ABox一致性判定算法

为了判定描述逻辑SHIN的ABox一致性,提出了一种Tableau算法。给定TBox T、ABox A和角色层次H,该算法通过预处理将A转换成标准的ABox [A],按照特定的完整策略将一套Tableau规则应用于[A],直到将它扩展成完整的ABox [A]为止。A与T和H一致,当且仅当算法能产生一个完整且无冲突的ABox [A]。算法所采用的阻塞机制可以避免Tableau规则的无限次执行,该机制允许一个新个体被在其之前创建的任意新个体直接阻塞,而不仅仅局限于其祖先。通过对算法的可终止性、合理性和完备性进行证明,算法的正确性得以确认。     

A robust filtering algorithm for subpixel reconstruction of chain coded line drawings

A robust algorithm is presented for smoothing and achieving subpixel accuracy in the reconstruction of chain coded line drawings. The algorithm does not remove sharp corners and does not need a priori knowledge of curvature statistics. A fast on-line implementation can be achieved using a table look-up. A simplified algorithm can be used for reconstructing digitized polygons.     

游戏中路径搜索算法研究

路径搜索是游戏中非常重要的一部分,A*算法是最常用的搜索算法,但是使用A*算法搜索出的路径的真实性常常不能让人满意。本文介绍A*搜索算法及存在的路径问题,针对该算法在游戏中暴露的问题,提出一种平滑改进的算法,较好地解决了这个问题。     

Binary search trees in secondary memory

Summary Binary search trees are shown to be reasonable alternatives to multiway trees for files stored in magnetic bubble memory. An algorithm for maintaining AVL trees is shown to be by far the most efficient of eight algorithms considered, when applied to secondary memory. A simplified model for analyzing the AVL algorithm is developed. A practical AVL algorithm for secondary memory is presented. Simulation results showing the performance of the AVL algorithm and a basic nonbalancing algorithm are given.     

L* Algorithm—A Linear Computational Complexity Graph Searching Algorithm for Path Planning

The state-of-the-art graph searching algorithm applied to the optimal global path planning problem for mobile robots is the A* algorithm with the heap structured open list. In this paper, we present a novel algorithm, called the L* algorithm, which can be applied to global path planning and is faster than the A* algorithm. The structure of the open list with the use of bidirectional sublists (buckets) ensures the linear computational complexity of the L* algorithm because the nodes in the current bucket can be processed in any sequence and it is not necessary to sort the bucket. Our approach can maintain the optimality and linear computational complexity with the use of the cost expressed by floating-point numbers. The paper presents the requirements of the L* algorithm use and the proof of the admissibility of this algorithm. The experiments confirmed that the L* algorithm is faster than the A* algorithm in various path planning scenarios. We also introduced a method of estimating the execution time of the A* and the L* algorithm. The method was compared with the experimental results.     

基于改进A*算法的分拣搬运机器人路径规划

为了解决分拣搬运机器人在路径规划过程中,遇到目标点众多的情况时存在路径寻优效率低、容易出错等问题。针对A*算法存在多个最小值时,无法实现路径最优化的问题进行研究,提出一种将蚁群算法与A*算法相结合的改进A*算法。首先使用A*算法筛选出一条最优化的路线来分布信息素,从而简化A*算法在路径规划上的运算。其次以筛选出的路线为基础,针对不同情况结合蚁群算法设计了三种通用方案,以此为基础进行具体的路径规划,从而解决A*算法本身存在的容易带入大量重复数据的问题。通过仿真与实际实验验证了本文提出的改进的A*算法能够满足自动分拣搬运的需求,值得推广与使用。     

描述逻辑SHIQ的ABox一致性判定算法

为判定描述逻辑SHIQ的ABox一致性,提出一种Tableau算法。给定TBox几ABoxA和角色层次H,通过预处理将A转换成标准的ABox A’,按照特定的完整策略将一套Tableau规则应用于A,从而不断地对A’进行扩展,直到将其扩展成完整的ABoxA”为止。A、T和H一致,当且仅当算法能产生一个完整且无冲突的ABox A”。该算法采用的阻塞机制能防止Tableau规则被无限次执行,避免多余的规则应用。通过证明Tableau规则的执行次数为有限次,确认算法的可终止性。通过证明由A”能构造一个同时满足A、T和H的解释,确认算法的合理性。通过证明Tableau规则的执行不会破坏A’与H的一致关系,确认算法的完备性。     

凸多边形窗口线裁剪的折半查找算法

在Skala算法基础上,提出了一个更加快速的线裁剪算法．该算法将裁剪窗口分割成4条折线,依据折线的两个端点与被裁剪直线的位置关系,确定折线是否与直线相交;采用折半查找方法,快速确定与直线相交的窗口边界线,并求出交点位置．与Cyrus-Beck算法相比,该算法在乘除法次数和计算速度方面具有非常明显的优势,也比、Skala算法的效率更高。     

An evolutionary method for general surface-surface intersection problems

A new approach to surface-surface intersection problems is proposed. Surface-surface intersection forms a fundamental function in computational geometry and geometric modeling. A geometric modeler needs to be equipped with a robust and accurate SSI algorithm to deal with a wide range of complex models. Although many methods have been proposed, it is generally known that computation of surface intersections is not an easy task in a computer environment. A new genetic algorithm, called Surface Intersection with Genetic Algorithm (SIGA), is developed. Several steps of an existing genetic algorithm are modified so that the new algorithm can be well suited to the intersection problems. A main advantage of SIGA is that it guarantees probabilistically finding all intersection curves.     

Fault-tolerant wormhole routing in mesh with overlapped solid fault regions

A fault-tolerant wormhole routing algorithm on mesh-connected processors is proposed. The proposed algorithm is based on the solid fault model and allows the fault polygons to be overlapped. The algorithm utilizes the position of fault region relative to the current channel to route a message around overlapped fault polygons. A node deactivating algorithm to convert a non-solid fault region into a solid fault region is also proposed. The proposed routing algorithm uses four virtual channels and is deadlock- and livelock-free.     

轮式机器人室内行走路径的探索算法

机器人行走路径的决策是机器人运动过程中相对比较复杂的课题，要对所处的环境给予准确的判断，并且还要确定正确的行走路径，这要求算法必须有一定的适应性和快速的计算能力。基于此，在A*探索算法的基础上提出一种路径生成算法，克服A*算法无法产生光滑连续的曲线路径的缺点，并且计算耗时非常少。该算法可以用于机器人在行走过程中对周围环境进行及时分析。     

基于蚁群遗传算法的网格资源调度研究

传统的资源调度算法在网格环境下存在一定缺陷,如不能很好地平衡资源节点的负载,不能很好满足用户服务质量需求等.为了提高网络质量,应用遗传算法全局快速收敛的优点,将遗传算法融入到蚁群算法的每一次迭代中,使之具有很强的全局搜索能力,以加快算法的收敛速度,提出了在价格机制驱动下,应用蚁群遗传算法进行网格资源调度的算法.仿真实验结果表明,在价格机制驱动下,应用蚁群遗传算法进行网格资源调度可以减少系统总执行时间和任务完成时间,系统负载均衡度好,提高了资源调度效率,在网格环境下,算法具有稳定性和高效性.     

Path Planning Strategies for UAVS in 3D Environments

The graph-search algorithms developed between 60s and 80s were widely used in many fields, from robotics to video games. The A* algorithm shall be mentioned between some of the most important solutions explicitly oriented to motion-robotics, improving the logic of graph search with heuristic principles inside the loop. Nevertheless, one of the most important drawbacks of the A* algorithm resides in the heading constraints connected with the grid characteristics. Different solutions were developed in the last years to cope with this problem, based on post-processing algorithms or on improvements of the graph-search algorithm itself. A very important one is Theta* that refines the graph search allowing to obtain paths with “any” heading. In the last two years, the Flight Mechanics Research Group of Politecnico di Torino studied and implemented different path planning algorithms. A Matlab based planning tool was developed, collecting four separate approaches: geometric predefined trajectories, manual waypoint definition, automatic waypoint distribution (i.e. optimizing camera payload capabilities) and a comprehensive A*-based algorithm used to generate paths, minimizing risk of collision with orographic obstacles. The tool named PCube exploits Digital Elevation Maps (DEMs) to assess the risk maps and it can be used to generate waypoint sequences for UAVs autopilots. In order to improve the A*-based algorithm, the solution is extended to tri-dimensional environments implementing a more effective graph search (based on Theta*). In this paper the application of basic Theta* to tri-dimensional path planning will be presented. Particularly, the algorithm is applied to orographic obstacles and in urban environments, to evaluate the solution for different kinds of obstacles. Finally, a comparison with the A* algorithm will be introduced as a metric of the algorithm performances.     

基于多维彩色向量空间的火焰图像模糊聚类分割算法

针对火灾探测过程中早期火焰的分割技术研究,提出了一种基于多维彩色向量空间的火焰图像模糊聚类分割算法,该算法以运动目标序列图像之间变化的区域作为聚类模板,提取该聚类模板的RGB多维彩色特征向量,然后将图像的像素与聚类模板通过模糊聚类的方式进行分割。这种分割算法计算简单,时间开销较小,可以较好地获取火焰图像的边缘形态特征,并且能够明显消除不同光线下分割误差,实现快速无监督自动分割。     

G.729A语音压缩算法的多级优化

针对G.729A语音压缩算法存在算法复杂、计算量大的不足,提出一种可快速计算LSP系数的APF-LSP算法,对G.729A算法进行算法级、语言级和编译器级三级优化,使其满足TMS320C5510 DSP硬件平台上的语音实时编解码要求。测试结果表明,优化后的G.729A算法运算量从590.097 MIPS降至50.523 MIPS,程序执行速度提高11倍以上。     

基于混合GA-BP算法优化的神经网络在机器人地面控制中的应用

在机器人地面控制中,针对BP算法易陷入局部极小、收敛速度慢的缺点,根据遗传算法具有全局寻优的特点,将二者结合起来形成一种训练神经网络的混合GA-BP算法;通过算法比较和实例结果分析,表明该算法可以有效、可靠地运用于机器人地面控制,并可方便地应用于其它方面.     

改进的模糊C均值的增量聚类算法

针对FCM算法的缺点,提出了一种基于改进的FCM的增量式聚类方法。该算法首先对模糊C均值算法进行加权,并将权系数归一化,然后将改进的算法与增量式聚类算法结合。改进的方法既提高了FCM算法的性能,避免了FCM算法的缺陷,并能够实现增量式聚类,避免了大量的重复计算,并且不受孤立点的影响。实验表明该算法的有效性。     

应用于机器人路径规划的双向时效A*算法

针对时效A*算法为了大幅减少算法时间,导致路径规划长度增加和路径锯齿过多的问题,提出一种改进的双向时效A*算法,该方法将从起点和终点同时运行时效A*算法寻找路径,并采用多近邻栅格距离计算方案;同时,根据不同环境地图对传统A*算法、时效A*算法和双向时效A*算法运行结果进行对比研究及分析;最后,制定算法时间、路径长度两个指标来评判算法的优劣。实验结果显示,双向时效A*算法相对于传统A*算法,算法时间最大减少76.8%,相对于时效A*算法,时间最大减少55.4%,并解决了时效A*算法规划路径距离增加、路径不够平滑的问题。     

隐写分析算法的模糊综合评估

隐写术和隐写分析技术是信息对抗的重要内容。目前，已经有许多隐写分析算法，但这些算法特点各异，在实际应用时，难以取舍。为此，提出了隐写分析算法的模糊综合评估算法，来实现对各种隐写分析算法的性能评估和比较。该评估算法不仅可以用于从已知隐写分析算法中选择出最优算法，也适合对新的隐写分析算法进行性能评估。