PRM代码实现c++

PRM 是一种路径规划算法，用于在给定环境中找到起点和终点之间的可行路径。以下是一个基本的 PRM 算法的 C 代码实现示例：

#include <stdio.h>
#include <stdlib.h>
#include <math.h>

#define NUM_SAMPLES 1000
#define NEIGHBOR_RADIUS 10.0

typedef struct {
    double x;
    double y;
} Point;

typedef struct {
    int pointIndex;
    int* neighbors;
    int numNeighbors;
} PRM_Node;

double distance(Point p1, Point p2) {
    double dx = p1.x - p2.x;
    double dy = p1.y - p2.y;
    return sqrt(dx*dx + dy*dy);
}

int* findNeighbors(Point* points, int numPoints, Point p) {
    int* neighbors = (int*)malloc(numPoints * sizeof(int));
    int numNeighbors = 0;

    for (int i = 0; i < numPoints; i++) {
        if (distance(points[i], p) <= NEIGHBOR_RADIUS) {
            neighbors[numNeighbors] = i;
            numNeighbors++;
        }
    }

    neighbors = (int*)realloc(neighbors, numNeighbors * sizeof(int));
    return neighbors;
}

int main() {
    Point start = {0.0, 0.0};
    Point goal = {10.0, 10.0};

    Point* samples = (Point*)malloc(NUM_SAMPLES * sizeof(Point));

    for (int i = 0; i < NUM_SAMPLES; i++) {
        samples[i].x = rand() / (double)RAND_MAX * 10.0;
        samples[i].y = rand() / (double)RAND_MAX * 10.0;
    }

    PRM_Node* graph = (PRM_Node*)malloc(NUM_SAMPLES * sizeof(PRM_Node));

    for (int i = 0; i < NUM_SAMPLES; i++) {
        graph[i].pointIndex = i;
        graph[i].neighbors = findNeighbors(samples, NUM_SAMPLES, samples[i]);
        graph[i].numNeighbors = 0;
    }

    for (int i = 0; i < NUM_SAMPLES; i++) {
        for (int j = 0; j < graph[i].numNeighbors; j++) {
            int neighborIndex = graph[i].neighbors[j];
            graph[i].numNeighbors++;
        }
    }

    // 在这里执行路径规划算法，查找从 start 到 goal 的路径

    // 释放内存
    for (int i = 0; i < NUM_SAMPLES; i++) {
        free(graph[i].neighbors);
    }
    free(graph);
    free(samples);

    return 0;
}

这是一个简单的 PRM 算法示例，其中一个随机采样的点集用于构建路径规划的图，并使用欧几里德距离来计算点之间的距离。你可以根据需要进行修改和扩展。注意，此示例尚未实现实际的路径搜索，你需要在代码中添加适当的算法来查找路径。