The article investigates some properties of square root of T3 tree’s nodes. It first proves several inequalities that are helpful to estimate the square root of a node, and then proves several theorems to describe th...The article investigates some properties of square root of T3 tree’s nodes. It first proves several inequalities that are helpful to estimate the square root of a node, and then proves several theorems to describe the distribution of the square root of the nodes on T3 tree.展开更多
This paper studies and analyses the character of the tree structure,and then presents an algorithm which is concise and convinent for the construction of tree structure.It is especially fit for the application system ...This paper studies and analyses the character of the tree structure,and then presents an algorithm which is concise and convinent for the construction of tree structure.It is especially fit for the application system using database.The special storege organization needn’t to be established in the database using this algorithm.By SQL statement,the data dispersed in different storeage organization can be dynamically combined into the data set including two fields:father node field and child node field.Then the algorithm can process those data and display the tree structure rapidly. At last,we design a control called TFDTreeView which inherits from TTreeView control using this algorithm. TFDTreeView control provide a interface function,through which we can construct the tree structure convinently. On some occasions,this method will be good for the application system.And ,by building the control ,we can reuse it in many system development.展开更多
针对基本的快速搜索随机树(rapidly-exploring random tree,RRT)算法用于路径规划时存在的树扩展无导向性、密集障碍物区域规划效率低、局部区域节点聚集等问题,提出一种新的RRT改进算法。该算法采用增强的目标偏向策略,并引入可变的权...针对基本的快速搜索随机树(rapidly-exploring random tree,RRT)算法用于路径规划时存在的树扩展无导向性、密集障碍物区域规划效率低、局部区域节点聚集等问题,提出一种新的RRT改进算法。该算法采用增强的目标偏向策略,并引入可变的权值系数,提高随机树扩展的导向性和灵活性;同时采用局部节点过滤机制,过滤局部区域内聚集的节点;最后,使用节点直连策略对初始路径进行优化处理。仿真实验的结果表明,改进的RRT算法规划路径的速度更快且生成的路径质量更高,充分证明了改进算法的有效可行性。展开更多
针对快速扩展随机树(Rapidly-exploring Random Tree,RRT)算法及其衍生算法路径规划时间长且规划效率低的问题,提出RRT算法与人工势场法结合的PAAPF-RRT机械臂路径规划算法,旨在最短的时间、最小的迭代次数内,在静态环境中找到连接起始...针对快速扩展随机树(Rapidly-exploring Random Tree,RRT)算法及其衍生算法路径规划时间长且规划效率低的问题,提出RRT算法与人工势场法结合的PAAPF-RRT机械臂路径规划算法,旨在最短的时间、最小的迭代次数内,在静态环境中找到连接起始点与终点的最优路径。首先,引入基于地图障碍物分布评估策略和采样区域优化策略,根据地图的障碍物分布、数量调整算法的步长以及偏向概率。然后,伴随随机树的生长,更新随机点的采样区域,保证随机树向目标点生长。其次,将RRT算法与人工势场法结合,当随机树与障碍物发生碰撞时,使用人工势场法引导随机树节点生长避开障碍物,解决了RRT算法随机树生长到障碍物附近且朝目标点生长的方向被障碍物遮挡时随机树无法生长的问题。最后,利用节点修剪策略,把算法生成的初始路径中的冗余节点进行修剪,得到拐点更少、路径更简洁的优化路径。实验结果表明,PAAPF-RRT算法在路径规划时间上对于RRT算法、GB-RRT算法以及RRT*算法分别减少了93.64%、73.58%、93.28%,在迭代次数方面分别下降了91.40%、79.64%、90.58%,在路径长度方面只占其他3种算法的79.34%、86.21%、95.58%。展开更多
文摘The article investigates some properties of square root of T3 tree’s nodes. It first proves several inequalities that are helpful to estimate the square root of a node, and then proves several theorems to describe the distribution of the square root of the nodes on T3 tree.
文摘This paper studies and analyses the character of the tree structure,and then presents an algorithm which is concise and convinent for the construction of tree structure.It is especially fit for the application system using database.The special storege organization needn’t to be established in the database using this algorithm.By SQL statement,the data dispersed in different storeage organization can be dynamically combined into the data set including two fields:father node field and child node field.Then the algorithm can process those data and display the tree structure rapidly. At last,we design a control called TFDTreeView which inherits from TTreeView control using this algorithm. TFDTreeView control provide a interface function,through which we can construct the tree structure convinently. On some occasions,this method will be good for the application system.And ,by building the control ,we can reuse it in many system development.
文摘针对基本的快速搜索随机树(rapidly-exploring random tree,RRT)算法用于路径规划时存在的树扩展无导向性、密集障碍物区域规划效率低、局部区域节点聚集等问题,提出一种新的RRT改进算法。该算法采用增强的目标偏向策略,并引入可变的权值系数,提高随机树扩展的导向性和灵活性;同时采用局部节点过滤机制,过滤局部区域内聚集的节点;最后,使用节点直连策略对初始路径进行优化处理。仿真实验的结果表明,改进的RRT算法规划路径的速度更快且生成的路径质量更高,充分证明了改进算法的有效可行性。
文摘针对快速扩展随机树(Rapidly-exploring Random Tree,RRT)算法及其衍生算法路径规划时间长且规划效率低的问题,提出RRT算法与人工势场法结合的PAAPF-RRT机械臂路径规划算法,旨在最短的时间、最小的迭代次数内,在静态环境中找到连接起始点与终点的最优路径。首先,引入基于地图障碍物分布评估策略和采样区域优化策略,根据地图的障碍物分布、数量调整算法的步长以及偏向概率。然后,伴随随机树的生长,更新随机点的采样区域,保证随机树向目标点生长。其次,将RRT算法与人工势场法结合,当随机树与障碍物发生碰撞时,使用人工势场法引导随机树节点生长避开障碍物,解决了RRT算法随机树生长到障碍物附近且朝目标点生长的方向被障碍物遮挡时随机树无法生长的问题。最后,利用节点修剪策略,把算法生成的初始路径中的冗余节点进行修剪,得到拐点更少、路径更简洁的优化路径。实验结果表明,PAAPF-RRT算法在路径规划时间上对于RRT算法、GB-RRT算法以及RRT*算法分别减少了93.64%、73.58%、93.28%,在迭代次数方面分别下降了91.40%、79.64%、90.58%,在路径长度方面只占其他3种算法的79.34%、86.21%、95.58%。
