雷达效果

相位阵雷达效果

一个简单思路：
在一个扇形范围内，用多个射线检测来每tick判断

点击查看代码

#pragma once#include "CoreMinimal.h"
#include "GameFramework/Actor.h"
#include "Components/SphereComponent.h"
#include "MyActor.generated.h"UCLASS()
class TEST_API AMyActor : public AActor
{GENERATED_BODY()public:	// Sets default values for this actor's propertiesAMyActor();UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "Detection Settings")float HorizontalDetectionAngle;UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "Detection Settings")float VerticalDetectionAngle;UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "Detection Settings")float RaycastAngleIncrement;UPROPERTY(EditAnywhere, BlueprintReadWrite, Category = "Detection Settings")float RaycastLength;UFUNCTION(BlueprintCallable,Category = "Detection")TArray<AActor*> PerformRaycastDetection();UPROPERTY(EditAnywhere ,BlueprintReadWrite)USphereComponent* DetectionSphere;protected:// Called when the game starts or when spawnedvirtual void BeginPlay() override;public:	// Called every framevirtual void Tick(float DeltaTime) override;};// Sets default values
AMyActor::AMyActor()
{// Set this actor to call Tick() every frame.  You can turn this off to improve performance if you don't need it.PrimaryActorTick.bCanEverTick = false;DetectionSphere = CreateDefaultSubobject<USphereComponent>(TEXT("Detection Sphere"));RootComponent = DetectionSphere;HorizontalDetectionAngle = 45.0f;VerticalDetectionAngle = 45.0f;RaycastAngleIncrement = 5.0f;RaycastLength = 1000.0f;}TArray<AActor*> AMyActor::PerformRaycastDetection()
{TArray<AActor*> DetectedActors;if (!DetectionSphere)return DetectedActors;FVector StartLocation = DetectionSphere->GetComponentLocation();FRotator Rotation = DetectionSphere->GetComponentRotation();float HalfHorizontalAngle = HorizontalDetectionAngle * 0.5f;float HalfVerticalAngle = VerticalDetectionAngle * 0.5f;UE_LOG(LogTemp, Warning,TEXT("HalfHorizontalAngle %f HalfVerticalAngle %f RaycastAngleIncrement %f"), HalfHorizontalAngle, HalfVerticalAngle, RaycastAngleIncrement);for (float VerticalAngle = -HalfVerticalAngle; VerticalAngle <= HalfVerticalAngle; VerticalAngle += RaycastAngleIncrement){for (float HorizontalAngle = -HalfHorizontalAngle; HorizontalAngle <= HalfHorizontalAngle; HorizontalAngle += RaycastAngleIncrement){FRotator RayRotation = Rotation;RayRotation.Pitch += VerticalAngle;RayRotation.Yaw += HorizontalAngle;FVector EndLocation = StartLocation + RayRotation.Vector() * RaycastLength;DrawDebugLine(GetWorld(), StartLocation, EndLocation, FColor::Red, false, -1.0f, 0, 2.0f);FHitResult HitResult;if (GetWorld()->LineTraceSingleByChannel(HitResult, StartLocation, EndLocation, ECC_Visibility)){AActor* HitActor = HitResult.GetActor();if (HitActor){DetectedActors.AddUnique(HitActor);}}}}return DetectedActors;
}

最后效果

吧drawdebugline换成drawdebugcone

各个参数可调

无人机编队
无人机之间连线

无人机外包洛信息

三维包洛算法

如果要处理三维坐标点的凸包,那么我们需要稍微修改一下算法。基本思路是仍然使用Graham扫描算法,但需要对叉积函数和极角排序方式进行调整。
下面是修改后的C++代码:
cppCopy code#include <iostream>
#include <vector>
#include <algorithm>
#include <cmath>using namespace std;// 定义三维点的结构体
struct Point3D {double x, y, z;Point3D(double x, double y, double z) : x(x), y(y), z(z) {}
};// 叉积计算函数
double crossProduct(const Point3D& p1, const Point3D& p2, const Point3D& p3) {double x1 = p2.x - p1.x, y1 = p2.y - p1.y, z1 = p2.z - p1.z;double x2 = p3.x - p1.x, y2 = p3.y - p1.y, z2 = p3.z - p1.z;return x1 * y2 * z1 - x1 * z2 * y1 - y1 * x2 * z1 + y1 * z2 * x1 + z1 * x2 * y1 - z1 * y2 * x1;
}// Graham扫描算法实现
vector<Point3D> grahamScan(vector<Point3D>& points) {// 找到z坐标最小的点作为起点auto start = min_element(points.begin(), points.end(), [](const Point3D& p1, const Point3D& p2) {return p1.z < p2.z || (p1.z == p2.z && p1.y < p2.y) || (p1.z == p2.z && p1.y == p2.y && p1.x < p2.x);});// 按极角排序点sort(points.begin(), points.end(), [&start](const Point3D& p1, const Point3D& p2) {double cross = crossProduct(*start, p1, p2);if (cross == 0) {double d1 = sqrt((p1.x - start->x) * (p1.x - start->x) + (p1.y - start->y) * (p1.y - start->y) + (p1.z - start->z) * (p1.z - start->z));double d2 = sqrt((p2.x - start->x) * (p2.x - start->x) + (p2.y - start->y) * (p2.y - start->y) + (p2.z - start->z) * (p2.z - start->z));return d1 < d2;}return cross > 0;});// 构造凸包vector<Point3D> hull;for (const Point3D& p : points) {while (hull.size() > 1 && crossProduct(hull[hull.size() - 2], hull.back(), p) <= 0) {hull.pop_back();}hull.push_back(p);}return hull;
}int main() {// 假设无人机坐标存储在drones_list中vector<vector<Point3D>> drones_list = {{Point3D(0, 3, 1), Point3D(1, 1, 2), Point3D(2, 2, 3), Point3D(4, 4, 4), Point3D(0, 0, 0), Point3D(1, 2, 1), Point3D(3, 1, 2), Point3D(3, 3, 3)},{Point3D(2, 3, 1), Point3D(4, 1, 2), Point3D(6, 4, 3), Point3D(5, 2, 4), Point3D(3, 0, 0), Point3D(1, 2, 1), Point3D(0, 1, 2)}};vector<vector<Point3D>> convex_hulls;for (const auto& drones : drones_list) {convex_hulls.push_back(grahamScan(drones));}// 输出结果for (const auto& hull : convex_hulls) {cout << "Convex Hull: ";for (const Point3D& p : hull) {cout << "(" << p.x << ", " << p.y << ", " << p.z << ") ";}cout << endl;}return 0;
}

但对于三维情况,就需要做一些额外的处理来确定各个面是由哪些点构成。一种常见的方法是通过计算点的顺序来确定面的方向,具体步骤如下:

对凸包点坐标序列做一个深拷贝,记为hull_copy。
按照右手法则,判断hull_copy中相邻三个点的顺序是否为逆时针(对于凸多面体,逆时针为内侧normal方向)。如果为顺时针,则将中间那个点与前一个点交换位置。
重复上一步,直到hull_copy中所有相邻三点的顺序都为逆时针。
最终hull_copy中,每相邻三点就构成了一个面。

下面是使用C++实现上述方法的代码:

cppCopy code#include <iostream>
#include <vector>
#include <algorithm>using namespace std;struct Point3D {double x, y, z;Point3D(double x, double y, double z) : x(x), y(y), z(z) {}
};vector<vector<Point3D>> getFaces(const vector<Point3D>& hull) {vector<vector<Point3D>> faces;vector<Point3D> hull_copy = hull;// 确保点的顺序为逆时针for (int i = 0; i < hull_copy.size(); i++) {int j = (i + 1) % hull_copy.size();int k = (i + 2) % hull_copy.size();Point3D& p1 = hull_copy[i];Point3D& p2 = hull_copy[j];Point3D& p3 = hull_copy[k];double x1 = p2.x - p1.x, y1 = p2.y - p1.y, z1 = p2.z - p1.z;double x2 = p3.x - p1.x, y2 = p3.y - p1.y, z2 = p3.z - p1.z;double cross_x = y1 * z2 - z1 * y2;double cross_y = z1 * x2 - x1 * z2;double cross_z = x1 * y2 - y1 * x2;if (cross_x < 0 || (cross_x == 0 && cross_y < 0) || (cross_x == 0 && cross_y == 0 && cross_z < 0)) {swap(hull_copy[j], hull_copy[k]);}}// 构造面for (int i = 0; i < hull_copy.size(); i++) {int j = (i + 1) % hull_copy.size();int k = (i + 2) % hull_copy.size();faces.push_back({hull_copy[i], hull_copy[j], hull_copy[k]});}return faces;
}int main() {// 假设无人机坐标存储在drones_list中vector<Point3D> drones = {Point3D(0, 3, 1), Point3D(1, 1, 2), Point3D(2, 2, 3), Point3D(4, 4, 4),Point3D(0, 0, 0), Point3D(1, 2, 1), Point3D(3, 1, 2), Point3D(3, 3, 3)};vector<Point3D> hull = grahamScan(drones); // 获取凸包点vector<vector<Point3D>> faces = getFaces(hull); // 获取构成面的点// 输出结果cout << "Convex Hull Faces:" << endl;for (const auto& face : faces) {cout << "Face: ";for (const Point3D& p : face) {cout << "(" << p.x << ", " << p.y << ", " << p.z << ") ";}cout << endl;}return 0;
}

在上述代码中,getFaces函数实现了确定每个面的点序列的逻辑。它首先对hull做一个拷贝,然后遍历这个拷贝,对每三个相邻点,根据叉积判断它们的顺序是否为逆时针,如果不是则交换中间两点的位置。最终hull_copy中每三个相邻点就构成了一个面。
在main函数中,我们首先获取无人机坐标的凸包hull,然后调用getFaces(hull)获取每个面的点序列,最后输出结果。

效果不好,算法有问题

通过射线扫中的范围来确定