The Studies On Spatial Path Planning With Obstacles Based On QPSO

Path planning problem is the multi-disciplinary classical questions which including thecomputer fields, and it has been widely used in the geography information system, roboticsand other fields. Spatial path planning problem with obstacles constraints means that in thespatial environment with obstacles, according to some evaluation criterion, planning a routeavoiding obstacles from the starting point to the object point. The efficient algorithmsresearch of spatial path planning with obstacles has been long concerned by the relateddomain experts and scholars.Quantum-behaved Particle Swarm Optimization (QPSO) algorithm was brought out in2004by Sun etc., contrapose the defect that Particle Swarm Optimization (PSO) can notguarantee the particle global convergence to the optimal solution. QPSO algorithm has someadvantages, such as has less parameters, easily to control and achieve, and has better globalsearch capability etc., it has been applied in many application areas successfully, such asneural network, training support vector machine and image segmentation etc.The background, research significance and the research status from domestic and abroadof the path planning are first introduced in this paper, and some common spatial indextechnology and path planning method are expatiated, and then the basic principle of particleswarm optimization algorithm and quantum-behaved particle swarm optimization algorithmare introduced. On this basis, this paper puts special stress on studing the spatial path planningbased on quantum-behaved particle swarm optimization algorithm in static environment withobstacles. The paper uses the grid method for the space environment modeling first, thencontrapose the defect that the gird method modeling space utilization rate is low and planningefficiency is low when obstacles are aparse, a method of quadtree on spatial environmentmodeling based on location code is studied, and based on the quadtree spatial modeling, usingquantum-behaved particle swarm optimization algorithm to search out a global optimalobstacle-avoiding path. The simulation result shows that, compared with path planning basedon grid method modeling, optimal path planning using the quadtree on spatial environmentmodeling not only distance is short, but also efficiency is higher in the planning. This paperfinally put the global spatial path planning algorithm with obstacles which is based onquadtree quantum-behaved particle swarm optimization application to the optimal pathplanning on one community to the designated park on Zhengzhou map, the actual experimental results shows that the method is effective and practical.In the end, the paper summarizes the work done and gives the analysis of furtherimprovement, and also the future is prospected simultaneously.