A new dynamic path planning method in high dimensional workspace, radial based probabilistic roadmap motion (RBPRM) planning method, is presented. Different from general probabilistic roadmap motion planning methods, ...A new dynamic path planning method in high dimensional workspace, radial based probabilistic roadmap motion (RBPRM) planning method, is presented. Different from general probabilistic roadmap motion planning methods, it uses straight lines as long as possible to construct a path graph, so the final path obtained from the graph is relatively shorter and straighter. Experimental results show the efficiency of the algorithm in finding shorter paths in sparse environment.展开更多
Task allocation is a key issue of agent cooperation mechanism in Multi-Agent Systems. The important features of an agent system such as the latency of the network infrastructure, dynamic topology, and node heterogenei...Task allocation is a key issue of agent cooperation mechanism in Multi-Agent Systems. The important features of an agent system such as the latency of the network infrastructure, dynamic topology, and node heterogeneity impose new challenges on the task allocation in Multi-Agent environments. Based on the traditional parallel computing task allocation method and Ant Colony Optimization (ACO), a novel task allocation method named Collection Path Ant Colony Optimization (CPACO) is proposed to achieve global optimization and reduce processing time. The existing problems of ACO are analyzed; CPACO overcomes such problems by modifying the heuristic function and the update strategy in the Ant-Cycle Model and establishing a threedimensional path pheromone storage space. The experimental results show that CPACO consumed only 10.3% of the time taken by the Global Search Algorithm and exhibited better performance than the Forward Optimal Heuristic Algorithm.展开更多
In order to improve the battle effectiveness of the unmanned aerial vehicle （UAV） under the increasingly complex threat environment, a three-dimension path planning method based on an A ＊ al- gorithm is proposed an...In order to improve the battle effectiveness of the unmanned aerial vehicle （UAV） under the increasingly complex threat environment, a three-dimension path planning method based on an A ＊ al- gorithm is proposed and simulated in this paper which makes the UAV satisfy requirements of different missions. At first, the digital map information is processed vdth an integrated terrain smoothing algorithm, and a safe flight surface which integrates the vehicle dynamic is built and added on the terrain, and then, models of the complicated threats are established and integrated into the digital terrain. At last, an improved A ＊ algorithm is used to plan the three-dimension path on the safe sur- face, and then smooth the path. Simulation results indicate that the approach has a good perform- ance in creating an optimal path in the three-dimension environment and the path planning algorithm is more simple, efficient and easily realized in the engineering field.展开更多
文摘A new dynamic path planning method in high dimensional workspace, radial based probabilistic roadmap motion (RBPRM) planning method, is presented. Different from general probabilistic roadmap motion planning methods, it uses straight lines as long as possible to construct a path graph, so the final path obtained from the graph is relatively shorter and straighter. Experimental results show the efficiency of the algorithm in finding shorter paths in sparse environment.
基金supported by National Natural Science Foundation of China under Grant No.61170117Major National Science and Technology Programs under Grant No.2010ZX07102006+3 种基金National Key Technology R&D Program under Grant No.2012BAH25B02the National 973 Program of China under Grant No.2011CB505402the Guangdong Province University-Industry Cooperation under Grant No.2011A090200008the Scientific Research Foundation, Returned Overseas Chinese Scholars, State Education Ministry
文摘Task allocation is a key issue of agent cooperation mechanism in Multi-Agent Systems. The important features of an agent system such as the latency of the network infrastructure, dynamic topology, and node heterogeneity impose new challenges on the task allocation in Multi-Agent environments. Based on the traditional parallel computing task allocation method and Ant Colony Optimization (ACO), a novel task allocation method named Collection Path Ant Colony Optimization (CPACO) is proposed to achieve global optimization and reduce processing time. The existing problems of ACO are analyzed; CPACO overcomes such problems by modifying the heuristic function and the update strategy in the Ant-Cycle Model and establishing a threedimensional path pheromone storage space. The experimental results show that CPACO consumed only 10.3% of the time taken by the Global Search Algorithm and exhibited better performance than the Forward Optimal Heuristic Algorithm.
文摘In order to improve the battle effectiveness of the unmanned aerial vehicle （UAV） under the increasingly complex threat environment, a three-dimension path planning method based on an A ＊ al- gorithm is proposed and simulated in this paper which makes the UAV satisfy requirements of different missions. At first, the digital map information is processed vdth an integrated terrain smoothing algorithm, and a safe flight surface which integrates the vehicle dynamic is built and added on the terrain, and then, models of the complicated threats are established and integrated into the digital terrain. At last, an improved A ＊ algorithm is used to plan the three-dimension path on the safe sur- face, and then smooth the path. Simulation results indicate that the approach has a good perform- ance in creating an optimal path in the three-dimension environment and the path planning algorithm is more simple, efficient and easily realized in the engineering field.
