| Autonomous land vehicle (ALV) is an unpiloted intelligent mobile robot. Research about it involves theories and technologies of many disciplines, and embodies the latest achievements of information and artificial intelligence, is of great value. The path planning of autonomous land vehicle is an important part of mobile robot system. The method of environment modeling established on cross-country and the balance between efficiency and precision of path planning are the challenges around the world.Firstly, the research situation of the commonly used planning algorithms is elaborated and summarized, with analysis of the advantage and deficiency of the algorithms, which makes an important basis for the research on mobile robot path planning in the thesis. Secondly, ways and difficulties about mobile robot environment modeling are recommended, an approach of framed-quadtree is managed which is on the basis of traditional grid and quadtree model, cells of quadtree is ameliorated and relevant property of each cell associated with cross-country characters is put. Framed-quadtree approach not only guarantees the connectivity of environment structure model, but also deal with complex terrain instances and truly reflects terrain detail color. During the process of obstacle expression, geometrical predigestions and improvements are carried out with the structure characters of obstacle polygon. A new method of vertex judgement - tangent way is proposed during polygon vertex judgement in this paper. It conquers the limitation of traditional plans, which is the same with either obstacle vertex judgement. In the end, considering the actual issues, classical Simulate Anneal Algorithm (SAA) is introduced, this paper explains the relation between performance and parameters of SAA in detail, and researches the way to set parameters, as well as purposes efficient ways to improve the performance of SAA.The simulation shows that the improved SAA is both feasible and efficient. |
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