Cocos2d-x 寻路算法之二 离目的地的距离优先

前端之家收集整理的这篇文章主要介绍了Cocos2d-x 寻路算法之二 离目的地的距离优先前端之家小编觉得挺不错的,现在分享给大家,也给大家做个参考。

转自--->Waiting For You:http://www.waitingfy.com/archives/831


1.介绍:

Figure 1

上一篇《Cocos2d-x 寻路算法之一 距离优先》,看这个图,我们发现这个寻路算法有点傻,明明终点在右侧却每个方向都找。难道没有其他办法了吗?从现实生活中我们知道东西如果在东边,当然是往东边搜索才是最好的办法。

2.开始动手

Figure 2

计算机中如何表示离目标近呢? 用图来解释就是这样的,目标在右上角,我们往右走,从X轴的角度来说离目标又近了一步,同理往上走是在Y轴上里目标近一步。最好的一步应该是图中-2的点,X轴和Y轴同时离目标近了一步。简单地转换成代码就是下面的这样:

?
1
2
3
4
5
6
7
8
9
bool comparebyWhichNearerGoalSimpleWay(Cell *c1,Cell *c2){
int distanceOfC1AndGoal = abs (g_goalX - c1->getX()) + (g_goalY - c1->getY());
distanceOfC2AndGoal = (g_goalX - c2->getX()) + (g_goalY - c2->getY());
if (distanceOfC1AndGoal <= distanceOfC2AndGoal){
return false ;
} else {
true ;
}
}

扔到heap的比较条件中我们轻易地就实现了按照离目标距离优先的寻路算法,startPathFinding整个方法都不要改,只需要传进去上面提到的比较方法就行了。

9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
@H_301_201@ 35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
typedef bool (*compareTwoCells)(Cell *c1,Cell *c2);
void HelloWorld::startPathFinding(compareTwoCells compareMethod, startX,monospace!important; border:0px!important; bottom:auto!important; float:none!important; height:auto!important; left:auto!important; outline:0px!important; overflow:visible!important; position:static!important; right:auto!important; top:auto!important; vertical-align:baseline!important; width:auto!important; min-height:inherit!important; background:none!important"> startY,monospace!important; border:0px!important; bottom:auto!important; float:none!important; height:auto!important; left:auto!important; outline:0px!important; overflow:visible!important; position:static!important; right:auto!important; top:auto!important; vertical-align:baseline!important; width:auto!important; min-height:inherit!important; background:none!important"> goalX,monospace!important; border:0px!important; bottom:auto!important; float:none!important; height:auto!important; left:auto!important; outline:0px!important; overflow:visible!important; position:static!important; right:auto!important; top:auto!important; vertical-align:baseline!important; width:auto!important; min-height:inherit!important; background:none!important"> goalY){
Cell *startCell = _m_Map.Get(startX,startY);
vector<Cell*> vecCells;
vecCells.push_back(startCell);
make_heap(vecCells.begin(),vecCells.end(),compareMethod);
startCell->setMarked( true );
Cell *nowProcessCell;
while (vecCells.size() != 0){
pop_heap(vecCells.begin(),compareMethod);
nowProcessCell = vecCells.back();
vecCells.pop_back();
(nowProcessCell->getX() == _goalX && nowProcessCell->getY() == _goalY){ //the goal is reach
return ;
}
for ( i = 0; i < 8; ++i){ //check eight direction
indexX = nowProcessCell->getX() + DIRECTION[i][0];
indexY = nowProcessCell->getY() + DIRECTION[i][1];
(indexX >= 0 && indexX < xLineCount && indexY >= 0 && indexY < yLineCount
&& _m_Map.Get(indexX,indexY)->getPassable() == ){ //check is a OK cell or not
Cell *cell = _m_Map.Get(indexX,indexY);
float beforeDistance = DISTANCE[i] * cell->getWeight() + _m_Map.Get(nowProcessCell->getX(),
nowProcessCell->getY())->getDistance(); //calculate the distance
(cell->getMarked() == false ){
cell->setMarked( );
cell->setLastX(nowProcessCell->getX());
cell->setLastY(nowProcessCell->getY());
cell->setDistance(beforeDistance);
vecCells.push_back(cell); //only push the unmarked cell into the vector
push_heap(vecCells.begin(),compareMethod);
@H_561_404@ { // if find a lower distance,update it
(beforeDistance < cell->getDistance()){
cell->setDistance(beforeDistance);
cell->setLastX(nowProcessCell->getX());
cell->setLastY(nowProcessCell->getY());
//distance change,so make heap again
}
}
}
}
}
}
startPathFinding(comparebyWhichNearerGoalSimpleWay,_playerX,_playerY,_goalX,_goalY); //demo

3.离目的地的距离优先效果图:

Figure 3

我们惊奇地发现似乎我们成功了,就用了9步就找到了目的地!

4.算法改进

从图2中我们用的是X轴和Y轴上的相对距离,并不是真正的物理距离,意识到这个问题我们马上修改了比较函数。物理距离当然容易算了,公式如下:

换成C++函数就是下面的样子:

15
distanceBetweenTwoCells( c1X,monospace!important; border:0px!important; bottom:auto!important; float:none!important; height:auto!important; left:auto!important; outline:0px!important; overflow:visible!important; position:static!important; right:auto!important; top:auto!important; vertical-align:baseline!important; width:auto!important; min-height:inherit!important; background:none!important"> c1Y,monospace!important; border:0px!important; bottom:auto!important; float:none!important; height:auto!important; left:auto!important; outline:0px!important; overflow:visible!important; position:static!important; right:auto!important; top:auto!important; vertical-align:baseline!important; width:auto!important; min-height:inherit!important; background:none!important"> c2X,monospace!important; border:0px!important; bottom:auto!important; float:none!important; height:auto!important; left:auto!important; outline:0px!important; overflow:visible!important; position:static!important; right:auto!important; top:auto!important; vertical-align:baseline!important; width:auto!important; min-height:inherit!important; background:none!important"> c2Y){
return sqrt ( pow (c2X - c1X,2) + (c2Y - c1Y,2));
}
comparebyWhichNearerGoalPhysicWay(Cell *c1,Cell *c2){
distanceOfC1AndGoal = distanceBetweenTwoCells(( )c1->getX(),( )c1->getY(),monospace!important; border:0px!important; bottom:auto!important; float:none!important; height:auto!important; left:auto!important; outline:0px!important; overflow:visible!important; position:static!important; right:auto!important; top:auto!important; vertical-align:baseline!important; width:auto!important; min-height:inherit!important; background:none!important">)g_goalX,monospace!important; border:0px!important; bottom:auto!important; float:none!important; height:auto!important; left:auto!important; outline:0px!important; overflow:visible!important; position:static!important; right:auto!important; top:auto!important; vertical-align:baseline!important; width:auto!important; min-height:inherit!important; background:none!important">) g_goalY);
distanceOfC2AndGoal = distanceBetweenTwoCells(( )c2->getX(),monospace!important; border:0px!important; bottom:auto!important; float:none!important; height:auto!important; left:auto!important; outline:0px!important; overflow:visible!important; position:static!important; right:auto!important; top:auto!important; vertical-align:baseline!important; width:auto!important; min-height:inherit!important; background:none!important">)c2->getY(),monospace!important; border:0px!important; bottom:auto!important; float:none!important; height:auto!important; left:auto!important; outline:0px!important; overflow:visible!important; position:static!important; right:auto!important; top:auto!important; vertical-align:baseline!important; width:auto!important; min-height:inherit!important; background:none!important">) g_goalY);
(distanceOfC1AndGoal <= distanceOfC2AndGoal){
;
{
;
}
演示了下发现没有什么变化。但我们知道我们变的更好了。

5.该算法存在的问题

1.很容易想到的一个问题是,它没有考虑权重!如果目标在右侧,而右侧是一条非常难走的路,那么这个算法将毫无顾虑地走过去,丝毫不考虑就在不远处有条非常轻松的路。下面这个图就可以说明这个问题。

2.还有个问题,即使没有权重Cell的存在,只有可通过和不可通过Cell的存在,这个算法也有问题,我们可以人为地制造一个陷阱,虽然目标在起点的下方,但是上面有条更近的路,这个算法应该会愚蠢地在往下找吧,这个就跟人一样,有时候目光短浅。下图是演示结果。

对比之前的算法发现其实上面的这条路更好的,虽然它查询了大量的Cell才发现这点(人家很努力的好不好)。

看看还有什么更好的办法没有?期待下篇的寻路算法吧。

6.项目下载

(请用7z解压,开发工具vs2010)

http://www.waitingfy.com/?attachment_id=828

http://www.waitingfy.com/?p=831

A*算法应用可以看下这篇文章贪吃蛇 AI 的实现 snake AI

原文链接:https://www.f2er.com/cocos2dx/342660.html

猜你在找的Cocos2d-x相关文章