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在致力于自然地形中实施自主导航的机器人研究中,人们发现:导航规划是自主机器人所有控制和推理任务的基础,当前虽然人工智能、机器人领域的研究者们开发了许多路径规划算法,但是所有这些算法都是针对结构化环境这样一种简单地形,并且在将这种地图形成地形数据结构时,都是由人工键入到计算机中去的。这样,为表达一个简单环境,常常需要花费很大的代价,并且当地形比较复杂时,无法人工去描述,即使可以描述,算法的效率也很成问题。现在,机器人研究的重心已开始倾向于自主移动机器人,但没有一个有效、快速的越野规划算法,要使自主机器人在野外实施自主行驶是不可能的。因此,自然地形中
In robotics research devoted to autonavigation in natural terrains, it has been found that navigation planning is the basis of all autonomous robot control and inference tasks. At present, although researchers in artificial intelligence and robotics have developed many path planning algorithms, all These algorithms are all based on a simple topography of the structured environment and are manually typed into the computer when they are formatted into a topographic data structure. In this way, it often takes a great deal to express a simple environment, and when the terrain is complex, it can not be described artificially. Even if it can be described, the efficiency of the algorithm is also problematic. Now, the focus of robotics research has begun to favor autonomous robotics, but without an efficient and fast off-road planning algorithm it is impossible to make autonomous robots autonomous in the field. Therefore, the natural terrain