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 alg...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.展开更多
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 prac...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.展开更多
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 ...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.展开更多
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 ...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.展开更多
在环境复杂的柔性制造系统中进行合理地AMR(autonomous mobile robot)调度具有重要意义。针对AMR调度中的路径规划与任务分配,以最小化AMR完成任务时间为目标函数建立数学模型,并通过拓扑法进行地图建模;采用贪婪算法对间隔时间服从定...在环境复杂的柔性制造系统中进行合理地AMR(autonomous mobile robot)调度具有重要意义。针对AMR调度中的路径规划与任务分配,以最小化AMR完成任务时间为目标函数建立数学模型,并通过拓扑法进行地图建模;采用贪婪算法对间隔时间服从定长分布的订单进行任务分配,通过对AMR工作状态分类以减少算法运算量;基于Dijkstra算法进行全局路径规划,搜索AMR的全局最短路径,并通过AMR的激光雷达进行局部避障路径规划;最后,通过在openTCS平台进行调度仿真实验验证其有效性。展开更多
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 a...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.展开更多
文摘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.
基金This research has been funded by Scientific Research Deanship at University of Ha’il–Saudi Arabia through Project Number BA-2107.
文摘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.
文摘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.
基金supported by the "Taishan Scholarship" Construction Engineering and Shandong Province Graduate Innovative Project(SDYC08011).
文摘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.
文摘在环境复杂的柔性制造系统中进行合理地AMR(autonomous mobile robot)调度具有重要意义。针对AMR调度中的路径规划与任务分配,以最小化AMR完成任务时间为目标函数建立数学模型,并通过拓扑法进行地图建模;采用贪婪算法对间隔时间服从定长分布的订单进行任务分配,通过对AMR工作状态分类以减少算法运算量;基于Dijkstra算法进行全局路径规划,搜索AMR的全局最短路径,并通过AMR的激光雷达进行局部避障路径规划;最后,通过在openTCS平台进行调度仿真实验验证其有效性。
文摘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.
