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再译《A *路径搜索入门》之一

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发布于 2015/06/07 11:47
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A *路径搜索

A* Pathfinding for Beginners

 

帕特里克·莱斯特表于2003108日下午833人工智能

By Patrick Lester Published Oct 08 2003 08:33 PM in Artificial Intelligence

 

如果您发现本文中包含错误或问题,导致无法读取它(丢失的影像或文件,受损代码,不正确的文本格式等),请联系编辑,以便能更正。感谢您帮助我们改善此资源。

If you find this article contains errors or problems rendering it unreadable (missing images or files, mangled code, improper text formatting, etc) please contact the editor so corrections can be made. Thank you for helping us improve this resource.

 

更新2005718

Updated July 18, 2005

 

篇文章已被翻成阿巴尼亚语,中文,法,德,葡萄牙,俄和西班牙。其他的翻迎的。篇文章的底部件地址。

This article has been translated into Albanian, Chinese, French, German, Portuguese, Russian, and Spanish. Other translations are welcome. See email address at the bottom of this article.

 

于初学者 A *A-,译者注:老外读A-star)算法可能有些在网上有很多解A *的文章,大多数写给有A *础的篇文章是真正的初学者。

The A* (pronounced A-star) algorithm can be complicated for beginners. While there are many articles on the web that explain A*, most are written for people who understand the basics already. This article is for the true beginner.

 

本文并不试图成为一主威著作。相反,它描述的基本原并准你去阅读所有其他材料和明白他什么。在篇文章的末尾提接到一些最好的来一步阅读

This article does not try to be the definitive work on the subject. Instead it describes the fundamentals and prepares you to go out and read all of those other materials and understand what they are talking about. Links to some of the best are provided at the end of this article, under Further Reading.

 

最后,篇文章不是具体方案。你应该里的任何算机言。正如你所期望的,然而, 篇文章的末尾,我有一个接到本文的示例程序。例子包中包含两个版本:一个是C++,一个Blitz Basichttp://www.blitzbasic.com/Home/_index_.php。它包含可行文件,如果你只是想看看A *的行

Finally, this article is not program-specific. You should be able to adapt what's here to any computer language. As you might expect, however, I have included a link to a sample program at the end of this article. The sample package contains two versions: one in C++ and one in Blitz Basic. It also contains executables if you just want to see A* in action.

 

但是我越来越提前。从开始......

But we are getting ahead of ourselves. Let's start at the beginning ...

 

介:搜索区域

Introduction: The Search Area

 

假设有想要A点到达B点。设有墙把AB点隔开示,绿表示起点A,用表示B并用填充的表示中间的那面

Let's assume that we have someone who wants to get from point A to point B. Let's assume that a wall separates the two points. This is illustrated below, with green being the starting point A, and red being the ending point B, and the blue filled squares being the wall in between.

[1]

[Figure 1]

 

首先,我搜索区域分割方形网格。这叫简化搜索区域,是路径搜索的第一步。种方法搜索区域简化一个二。数中的每一个元素代表网格里的一个方块,它的地位被记录为行走和不可行走。从AB经过的方块叫路径一旦路径被找到发现就可以从一个正的中心到下一个中心,直到到达目

The first thing you should notice is that we have divided our search area into a square grid. Simplifying the search area, as we have done here, is the first step in pathfinding. This particular method reduces our search area to a simple two dimensional array. Each item in the array represents one of the squares on the grid, and its status is recorded as walkable or unwalkable. The path is found by figuring out which squares we should take to get from A to B. Once the path is found, our person moves from the center of one square to the center of the next until the target is reached.

 

些中心点被称点”。在看别的路径搜索资料时常会看到讨论节点。什么不叫它们方格呢?因有可能路径搜索积不分割成方格。可以是矩形,六形,三角形或任何形状,真的。点可以任何形状表示- 在中心或者沿着边缘,或其他任何地方。不,我使用,因它是最简单的。

These center points are called "nodes". When you read about pathfinding elsewhere, you will often see people discussing nodes. Why not just call them squares? Because it is possible to divide up your pathfinding area into something other than squares. They could be rectangles, hexagons, triangles, or any shape, really. And the nodes could be placed anywhere within the shapes – in the center or along the edges, or anywhere else. We are using this system, however, because it is the simplest.

 

开始搜索

Starting the Search

 

一旦搜索区域化成管理数量的点,就像上面所说的网格布局,下一步就是行搜索找到最短路径。A开始检查方块并向外普及搜索,直到找到目

Once we have simplified our search area into a manageable number of nodes, as we have done with the grid layout above, the next step is to conduct a search to find the shortest path. We do this by starting at point A, checking the adjacent squares, and generally searching outward until we find our target.

 

们执行以下操作开始搜索:

We begin the search by doing the following:

 

1.起点A开始,并将添加到 “开列表”。开列表有点像一张购物清尽管列表里只有一个目,但以后会有更多。它包含了可能是你想要的,也可能不是。基本上,是需要被检查的方的列表。

1.Begin at the starting point A and add it to an "open list" of squares to be considered. The open list is kind of like a shopping list. Right now there is just one item on the list, but we will have more later. It contains squares that might fall along the path you want to take, but maybe not. Basically, this is a list of squares that need to be checked out.

 

2.寻找起点所有到达或可行走的方,忽略有,水或其他非法地形。添加到开列表。于每一个方,保存A点作它们的“父方”。当要追溯路径时父方格西是很重要的。稍后会解它。

2.Look at all the reachable or walkable squares adjacent to the starting point, ignoring squares with walls, water, or other illegal terrain. Add them to the open list, too. For each of these squares, save point A as its "parent square". This parent square stuff is important when we want to trace our path. It will be explained more later.

 

3.从开列表删除开始A,并将添加到不需要再次寻找的“关闭列表”。

3.Drop the starting square A from your open list, and add it to a "closed list" of squares that you don't need to look at again for now.

 

一点上,你应该下面插形象。在该图中,位于中心的深绿色方就是开始方。它是色,以指示已被添加到封列表。在开启列表的所有相块进检查,并且绿来框记它们。每个方格都有一个灰色的指指回它们的父方格,也就是开始方

At this point, you should have something like the following illustration. In this illustration, the dark green square in the center is your starting square. It is outlined in light blue to indicate that the square has been added to the closed list. All of the adjacent squares are now on the open list of squares to be checked, and they are outlined in light green. Each has a gray pointer that points back to its parent, which is the starting square.

 

[2]

[Figure 2]

 

下一步,我们选择了开启列表上的一个,并或多或少重复前面的,如下所述。但是,我们选择哪方?一个与最小F

Next, we choose one of the adjacent squares on the open list and more or less repeat the earlier process, as described below. But which square do we choose? The one with the lowest F cost.

 




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