| Unmanned Surface Vehicles (USVs) have some good properties such as moving fast, invisible and intelligent, and they can be used to take action in accordance with various requirements. At present, west countries especially America and Israel have made a lot of progress, whereas we have just started researching on USVs, and still have much work to do to improve the intelligence of USVs. Path planning is one of the main tasks in USV's navigation system. Global path planning problem is an important research issue for USVs, and the research on Global Path planning is very meaningful. Global path planning is virtually, under certain restriction, the planning of a path from the starting point to the ending point avoiding collision, based on priori knowledge.Has been widely used in path planning problems of mobile robots, Genetic Algorithm (GA) is the most representative one of evolutionary algorithms, and more and more people begin to research and use this intelligent algorithm. Artificial Potential Field (APF) method is one of the most widely used methods today, because APF has a simple mathematic model, and is easy to realize. This Dissertation researches the application of GA and APF to path planning problem of USVs, the following aspects are investigated and discussed.Firstly, the developing situation including both domestic and overseas is introduced, meanwhile, the research background of USVs and the significance of the research are introduced.Secondly, the definition, classification and common approaches of global path planning are introduced. It can help choose the proper approach by knowing these.Finally, path planning programs for USVs based on GA and APF are designed, and the results of simulation experiments are analyzed. |
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