csharp
/
MonoGame.XNASamples
mirror of https://github.com/SimonDarksideJ/XNAGameStudio.git


			
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</head><body><div id="mainSection"><div id="mainBody">
  <h1>Pathfinding Sample</h1>

    This sample demonstrates how AIs can use algorithms to navigate a map using 
	waypoints.

  <a name="ID2EK"></a><h1 class="heading">Sample Overview</h1><div id="ID2EK" class="hxnx1">
    

    <p>
      To create realistic enemy movement AI, implementing Pathfinding algorithms 
	  becomes necessary. The goal of pathfinding is to explore possible routes 
	  to get from one point, or node, to another, often with the goal of finding 
	  the quickest route. To get started, this sample demonstrates three common 
	  pathfinding algorithms: Breadth-First, Best-First and A* (A-Star). To 
	  illustrate the logic behind these algorithms, the searched nodes are 
	  represented as red dots, while the nodes available to search are 
	  represented as green dots. Once the algorithm has found the end, the tank 
	  travels the path to its destination.</p>

          
      <p>This sample uses the following controls.</p>
      <table>
        <tr>
          <th>Action</th>
          <th style="width: 192px">Windows Phone</th>
          <th>Windows - Keyboard Control</th>
          <th>Windows/Xbox - Gamepad Control</th>
        </tr>
        <tr>
          <td>Start the pathfinding algorithm</td>
          <td style="width: 192px"><strong>TAP</strong> &quot;Start/Stop&quot; button</td>
          <td>A</td>
          <td>A</td>
        </tr>
        <tr>
          <td>Reset the map</td>
          <td style="width: 192px"><strong>TAP</strong> &quot;Reset&quot; button</td>
          <td>B</td>
          <td>
            B</td>
        </tr>
        <tr>
          <td>Switch the map</td>
          <td style="width: 192px"><strong>TAP</strong> &quot;Next Map&quot; button</td>
          <td>Y</td>
          <td>
            Y</td>
        </tr>
        <tr>
          <td>Switch the pathfinding algorithm</td>
          <td style="width: 192px"><strong>TAP</strong> &quot;Pathfinding Mode:&quot; button</td>
          <td>X</td>
          <td>X</td>
        </tr>
        <tr>
          <td>Change the time step</td>
          <td style="width: 192px"><strong>DRAG</strong> &quot;Time Step&quot; slider</td>
          <td>LEFT ARROW, RIGHT ARROW</td>
          <td>
            D-Pad LEFT, D-Pad RIGHT</td>
        </tr>
        <tr>
          <td style="height: 26px">Exit the game.</td>
          <td style="width: 192px; height: 26px;"><strong>BACK</strong></td>
          <td style="height: 26px">ESC or ALT+F4</td>
          <td style="height: 26px">
            <b>BACK</b>
          </td>
        </tr>
      </table>
    </div>
  </div>

  <a name="ID2EHE"></a><h1 class="heading">How the Sample Works</h1><div id="ID2EHE" class="hxnx1">
    

    <p>
      &nbsp;</p>
		<h2 class="subHeading">Pathfinding Behavior</h2>
		<div id="ID2E1D" class="hxnx2">
			<p>All of the pathfinding algorithms below rely on searching a graph 
			of nodes, named waypoints for the purposes of our sample, to get 
			from a start point to a goal. The algorithms described below can be 
			useful in different situations, and so it is important to understand 
			the way in which your algorithm will be used. Adding cost to your 
			nodes is a prime example. For instance, if you had a game where 
			traveling over mountains resulted in a slower movement speed than 
			traveling over a plain, the cost of a particular mountain node might 
			be 5, where a plain node would be 1. This will allow certain 
			pathfinding algorithms to determine whether it is more efficient to 
			over the mountain or around it. A brief description of each of the 
			supplied algorithms is listed below:</p>
			<p>&nbsp;</p>
			<a name="ID2ECE"></a>
			<span class="auto-style1">Breadth-First</span><div id="ID2EEF" class="hxnx3">
				<p>The Breadth-First algorithm uses a graph search that explores 
				all nodes neighboring a given root node. It then searches the 
				neighbors of the neighbors and continues in this manner until 
				the goal has been found or all available neighbors from the root 
				have been searched. This algorithm is useful if you want to 
				exhaustively search the map for every possible path, but also 
				results in the slowest implementation.</p>
			</div>
			<h4 class="subHeading">Best-First</h4>
			<div id="ID2ECE" class="hxnx3">
				<p>The Best-First algorithm searches through the node graph in 
				an attempt to find the shortest distance to the goal. This 
				algorithm will always find the shortest distance to the goal, 
				but does not take the cost into account. Best-First is best used 
				in scenarios where nodes have a uniform cost.</p>
			</div>
			<a name="ID2EUE"></a>
			<h4 class="subHeading">A*</h4>
			<div id="ID2EUE" class="hxnx3">
				<p>A* pathfinding combines a Best-First search with a heuristic, 
				or educated guess, that searches for the lowest cost route. A* 
				will always return the route with the lowest cost to the goal. 
				This algorithm is most useful where nodes have varying costs 
				associated with them.</p>
			</div>
			<a name="ID2EEF"></a>
			<a name="ID2EYF"></a>
		</div>

  </div>

  <a name="ID2EAH"></a><h1 class="heading">Extending the Sample</h1><div id="ID2EAH" class="hxnx1">
    

    	<ul>
			<li>Add cost to the different nodes to support different types of 
			terrain</li>
			<li>Add the ability to move the goal at runtime and have the path 
			change dynamically </li>
			<li>Add additional algorithms</li>
		</ul>
  </div>

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