Ant Colony Algorithm Based On 3D Path Planning Of Elevation Scene

With the increasingly deep studying of artificial intelligence and the menace from challenge of national safe, the intelligent robot which could specially protect human safe and replace people to finish the extremely risk mission has played a unique role in the world. The automatic unmanned ground vehicle is a military mobile carrier, which combines the remote sensing and control technique, satellite navigation technique and other high-tech measures to complement various military missions in the complex and unstable 3D scene. Path planning is seriously restrained from adverse elements which are uncertain whether status, complex road scene and unstable obstacle station in the unconstructed scene of 3D outdoor environment.In this paper, the work is that the ant colony algorithm is employed in 3D scene of abstract modeling or elevation modeling respectively. The specific work will be described as follows:1) According to discussing for development and current situation of unmanned military grounder vehicle, its future is identified. Furthermore, the structure and works of this paper is expressed in detail here.2) According to analyzing and comparing of path planning algorithm, the ant colony algorithm is employed from two-dimensional scene to three-dimensional scene.3) The 3D scene of abstract modeling is build by abstract modeling primarily, and then the elevation modeling is built according to its modeled method and the scene is simplified in this process, which will make the ant colony algorithm be employed in above-constructed three-dimensional scene advantageously.4) Based on above-mentioned, the entire structure of ant colony algorithm under 3D scene is produced and fulfilled.5) According to analyzing to a plenty of experimental results, the validity and feasibility of the proposed entire structure system of ant colony algorithm under 3D path planning is verified in this paper.According to a large amount of experimental results and statistics, the method mentioned in the research is proved to cost the shortest time and show the best obstacle-avoiding effect in finding the best path in the elevation space environment. Meanwhile, it also illustrates the validity and feasibility of the method.