javascript - A*(A-star) 算法给出错误的路径并崩溃
问题描述
我正在 react.js 中实现 A*(A-star) 算法,但是每当 startNode(green) 或 destinationNode(blue) 有多个邻居或图中存在循环时,我的程序就会崩溃。从/向 openList 添加和删除邻居或在 getPath() 函数中更新 parentId 时出现问题。我什至看不到控制台,因为网站出现故障。每个节点有:id, name, x, y, connectedToIdsList:[], gcost:Infinity, fcost:0, heuristic:0, parentId:null。我将路径发送到另一个打印出路径的组件“TodoList”。我的程序不应该返回路径,而是在向列表中添加节点和边时不断更新路径。请帮忙,我已经被困了几个小时了:/
我的代码:
export default class TurnByTurnComponent extends React.PureComponent {
constructor(props) {
super(props);
this.state = { shortestPath: [] }
}
render() {
const {
destinationLocationId,
locations,
originLocationId
} = this.props;
let path = []
if (destinationLocationId != null && originLocationId != null) {
if (originLocationId == destinationLocationId) { //check if the startNode node is the end node
return originLocationId;
}
var openList = [];
let startNode = getNodeById(originLocationId);
let destinationNode = getNodeById(destinationLocationId)
if (startNode.connectedToIds.length > 0 && destinationNode.connectedToIds.length > 0) { //check if start and destination nodes are connected first
startNode.gcost = 0
startNode.heuristic = manhattanDistance(startNode, destinationNode)
startNode.fcost = startNode.gcost + startNode.heuristic;
//perform A*
openList.push(startNode); //starting with the startNode
while (openList.length > 0) {
console.log("inside while")
var currentNode = getNodeOfMinFscore(openList); //get the node of the minimum f cost of all nodes in the openList
if (currentIsEqualDistanation(currentNode)) {
path = getPath(currentNode);
}
deleteCurrentFromOpenList(currentNode, openList);
for (let neighbourId of currentNode.connectedToIds) {
var neighbourNode = getNodeById(neighbourId);
currentNode.gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);
if (currentNode.gcost < neighbourNode.gcost) {
neighbourNode.parentId = currentNode.id; // keep track of the path
// total cost saved in neighbour.g
neighbourNode.gcost = currentNode.gcost;
neighbourNode.heuristic = manhattanDistance(neighbourNode, destinationNode);
neighbourNode.fcost = neighbourNode.gcost + neighbourNode.heuristic; //calculate f cost of the neighbourNode
addNeighbourNodeToOpenList(neighbourNode, openList);
}
}
}
path = path.reverse().join("->");
}
}
function addNeighbourNodeToOpenList(neighbourNode, openList) {
//add neighbourNode to the open list to be discovered later
if (!openList.includes(neighbourNode)) {
openList.push(neighbourNode);
}
}
function deleteCurrentFromOpenList(currNode, openList) {
const currIndex = openList.indexOf(currNode);
openList.splice(currIndex, 1); //deleting currentNode from openList
}
function currentIsEqualDistanation(currNode) {
//check if we reached out the distanation node
return (currNode.id == destinationLocationId)
}
function getNodeById(nid) {
var node;
for (let i = 0; i < locations.length; i++) {
if (locations[i].id == nid) {
node = locations[i]
}
}
return node
}
function getPath(destNode) {
console.log("inside getpath")
var parentPath = []
var parent;
while (destNode.parentId != null) {
parentPath.push(destNode.name)
parent = destNode.parentId;
destNode = getNodeById(parent);
}
//adding startNode to the path
parentPath.push(getNodeById(originLocationId).name)
return parentPath;
}
function getNodeOfMinFscore(openList) {
var minFscore = openList[0].fcost; //initValue
var nodeOfminFscore;
for (let i = 0; i < openList.length; i++) {
if (openList[i].fcost <= minFscore) {
minFscore = openList[i].fcost //minFvalue
nodeOfminFscore = openList[i]
}
}
return nodeOfminFscore
}
//manhattan distance is for heuristic and gScore. Here I use Manhattan instead of Euclidean
//because in this example we dont have diagnosal path.
function manhattanDistance(stNode, dstNode) {
var x = Math.abs(dstNode.x - stNode.x);
var y = Math.abs(dstNode.y - stNode.y);
var dist = x + y;
return dist;
}
return (
<div className="turn-by-turn-component">
<TodoList
list={"Shortest path: ", [path]}
/>
<TodoList
list={[]}
/>
</div>
);
}
}
TurnByTurnComponent.propTypes = {
destinationLocationId: PropTypes.number,
locations: PropTypes.arrayOf(PropTypes.shape({
id: PropTypes.number.isRequired,
name: PropTypes.string.isRequired,
x: PropTypes.number.isRequired,
y: PropTypes.number.isRequired,
connectedToIds: PropTypes.arrayOf(PropTypes.number.isRequired).isRequired
})),
originLocationId: PropTypes.number
};
更新新问题 链接新节点前后的图片。当我更新图表并添加一个新节点时,路径消失了。如果我仍然向图中添加新节点和边,有时会回来等等。正如我所说,每个节点都有:id、name、x、y、connectedToIdsList:[]、gcost:Infinity、fcost:0、heuristic:0、parentId:null。 我现在的新代码是:
export default class TurnByTurnComponent extends React.PureComponent {
constructor(props) {
super(props);
this.state = { shortestPath: [] }
}
render() {
const {
destinationLocationId,
locations,
originLocationId
} = this.props;
let path = []
if (destinationLocationId != null && originLocationId != null) {
console.log(JSON.stringify(locations))
path = [getNodeById(originLocationId).namne];
if (originLocationId != destinationLocationId) {
var openList = [];
let startNode = getNodeById(originLocationId);
let destinationNode = getNodeById(destinationLocationId)
if (startNode.connectedToIds.length > 0 && destinationNode.connectedToIds.length > 0) {
startNode.gcost = 0
startNode.heuristic = manhattanDistance(startNode, destinationNode)
startNode.fcost = startNode.gcost + startNode.heuristic;
openList.push(startNode); //starting with the startNode
while (openList.length > 0) {
var currentNode = getNodeOfMinFscore(openList); //get the node of the minimum f cost of all nodes in the openList
if (currentIsEqualDistanation(currentNode)) {
path = getPath(currentNode);
break;
}
deleteCurrentFromOpenList(currentNode, openList);
for (let neighbourId of currentNode.connectedToIds) {
var neighbourNode = getNodeById(neighbourId);
let gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);
if (gcost < (neighbourNode.gcost ?? Infinity)) {
neighbourNode.parentId = currentNode.id;
// keep track of the path
// total cost saved in neighbour.g
neighbourNode.gcost = gcost;
neighbourNode.heuristic = manhattanDistance(neighbourNode, destinationNode);
neighbourNode.fcost = neighbourNode.gcost + neighbourNode.heuristic; //calculate f cost of the neighbourNode
addNeighbourNodeToOpenList(neighbourNode, openList);
}
}
}
}
}
}
path = path.reverse().join("->");
function addNeighbourNodeToOpenList(neighbourNode, openList) {
//add neighbourNode to the open list to be discovered later
if (!openList.includes(neighbourNode)) {
openList.push(neighbourNode);
}
}
function deleteCurrentFromOpenList(currentNode, openList) {
const currIndex = openList.indexOf(currentNode);
openList.splice(currIndex, 1); //deleting currentNode from openList
}
function currentIsEqualDistanation(currentNode) {
//check if we reached out the distanation node
return (currentNode.id == destinationLocationId)
}
function getNodeById(id) {
var node;
for (let i = 0; i < locations.length; i++) {
if (locations[i].id == id) {
node = locations[i]
}
}
return node
}
function getPath(destinationNode) {
console.log("inside getpath")
var parentPath = []
var parent;
while (destinationNode.parentId != null) {
parentPath.push(destinationNode.name)
parent = destinationNode.parentId;
destinationNode = getNodeById(parent);
}
//adding startNode to the path
parentPath.push(getNodeById(originLocationId).name)
return parentPath;
}
function getNodeOfMinFscore(openList) {
var minFscore = openList[0].fcost; //initValue
var nodeOfminFscore;
for (let i = 0; i < openList.length; i++) {
if (openList[i].fcost <= minFscore) {
minFscore = openList[i].fcost //minFvalue
nodeOfminFscore = openList[i]
}
}
return nodeOfminFscore
}
//manhattan distance is for heuristic and gScore. Here I use Manhattan instead of Euclidean
//because in this example we dont have diagnosal path.
function manhattanDistance(startNode, destinationNode) {
var x = Math.abs(destinationNode.x - startNode.x);
var y = Math.abs(destinationNode.y - startNode.y);
var dist = x + y;
return dist;
}
return (
<div className="turn-by-turn-component">
<TodoList
title="Mandatory work"
list={[path]}
/>
<TodoList
title="Optional work"
list={[]}
/>
</div>
);
}
}
TurnByTurnComponent.propTypes = {
destinationLocationId: PropTypes.number,
locations: PropTypes.arrayOf(PropTypes.shape({
id: PropTypes.number.isRequired,
name: PropTypes.string.isRequired,
x: PropTypes.number.isRequired,
y: PropTypes.number.isRequired,
connectedToIds: PropTypes.arrayOf(PropTypes.number.isRequired).isRequired
})),
originLocationId: PropTypes.number
};
解决方案
您的代码中有几个问题:
return originLocationId;
不应该发生。当源等于目标时,然后设置路径,并确保return
执行该函数的final,因为您要返回div
元素。当在循环中找到目标时,不仅应该
path
构建,而且应该退出循环。所以添加一个break
currentNode.gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);
是不对的:您不想修改currentNode.gcost
:它的值不应该取决于该邻居的传出边缘。而是将此总和存储在临时变量中(如gcost
)neighbourNode.gcost
当该节点还没有成员时,与的比较将不起作用gcost
。我在您的代码中没有看到它具有确保此条件为真的默认值,因此您应该在此处使用默认值,例如(neighbourNode.gcost ?? Infinity)
path = path.reverse().join("->");
最好总是执行,即使没有解决方案(path
字符串也是如此)或源和目标是同一节点时。
这是一个更正的版本,稍微适应了在此处作为可运行片段运行:
function render() {
const {
destinationLocationId,
locations,
originLocationId
} = this.props;
let path = [];
if (destinationLocationId != null && originLocationId != null) {
path = [originLocationId]; // The value for when the next if condition is not true
if (originLocationId != destinationLocationId) {
var openList = [];
let startNode = getNodeById(originLocationId);
let destinationNode = getNodeById(destinationLocationId)
if (startNode.connectedToIds.length > 0 && destinationNode.connectedToIds.length > 0) {
startNode.gcost = 0
startNode.heuristic = manhattanDistance(startNode, destinationNode)
startNode.fcost = startNode.gcost + startNode.heuristic;
openList.push(startNode);
while (openList.length > 0) {
var currentNode = getNodeOfMinFscore(openList);
if (currentIsEqualDistanation(currentNode)) {
path = getPath(currentNode);
break; // Should end the search here!
}
deleteCurrentFromOpenList(currentNode, openList);
for (let neighbourId of currentNode.connectedToIds) {
var neighbourNode = getNodeById(neighbourId);
// Should not modify the current node's gcost. Use a variable instead:
let gcost = currentNode.gcost + manhattanDistance(currentNode, neighbourNode);
// Condition should also work when neighbour has no gcost yet:
if (gcost < (neighbourNode.gcost ?? Infinity)) {
neighbourNode.parentId = currentNode.id;
neighbourNode.gcost = gcost; // Use the variable
neighbourNode.heuristic = manhattanDistance(neighbourNode, destinationNode);
neighbourNode.fcost = neighbourNode.gcost + neighbourNode.heuristic;
addNeighbourNodeToOpenList(neighbourNode, openList);
}
}
}
}
}
}
// Convert the path to string in ALL cases:
path = path.reverse().join("->");
function addNeighbourNodeToOpenList(neighbourNode, openList) {
if (!openList.includes(neighbourNode)) {
openList.push(neighbourNode);
}
}
function deleteCurrentFromOpenList(currNode, openList) {
const currIndex = openList.indexOf(currNode);
openList.splice(currIndex, 1);
}
function currentIsEqualDistanation(currNode) {
return (currNode.id == destinationLocationId)
}
function getNodeById(nid) {
var node;
for (let i = 0; i < locations.length; i++) {
if (locations[i].id == nid) {
node = locations[i]
}
}
return node
}
function getPath(destNode) {
var parentPath = []
var parentId;
while (destNode.parentId != null) {
parentPath.push(destNode.name)
parentId = destNode.parentId;
destNode = getNodeById(parentId);
}
parentPath.push(getNodeById(originLocationId).name)
return parentPath;
}
function getNodeOfMinFscore(openList) {
var minFscore = openList[0].fcost;
var nodeOfminFscore;
for (let i = 0; i < openList.length; i++) {
if (openList[i].fcost <= minFscore) {
minFscore = openList[i].fcost
nodeOfminFscore = openList[i]
}
}
return nodeOfminFscore
}
function manhattanDistance(stNode, dstNode) {
var x = Math.abs(dstNode.x - stNode.x);
var y = Math.abs(dstNode.y - stNode.y);
var dist = x + y;
return dist;
}
return "Shortest path: " + path;
}
// Demo
let props = {
locations: [
{ id: 1, x: 312, y: 152, connectedToIds: [4,2], name: "Thetaham" },
{ id: 2, x: 590, y: 388, connectedToIds: [1,3], name: "Deltabury" },
{ id: 3, x: 428, y: 737, connectedToIds: [2], name: "Gammation" },
{ id: 4, x: 222, y: 430, connectedToIds: [1], name: "Theta City" },
],
originLocationId: 1,
destinationLocationId: 3,
};
console.log(render.call({props}));
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