采取

E是射线的起点， L是射线的端点， C是你测试的圆心 R是球面的半径

计算: d = L - E(射线方向矢量，从头到尾) f = E - C(从中心球到射线起点的向量)

然后通过…找到交点。 堵塞: P = E + t * d 这是一个参数方程 Px = Ex + tdx Py = Ey + tdy 成 (x - h)2 + (y - k)2 = r2 (h,k) =圆心。

注意:我们在这里将问题简化为2D，我们得到的解决方案也适用于3D

得到:

Expand x2 - 2xh + h2 + y2 - 2yk + k2 - r2 = 0 Plug x = ex + tdx y = ey + tdy ( ex + tdx )2 - 2( ex + tdx )h + h2 + ( ey + tdy )2 - 2( ey + tdy )k + k2 - r2 = 0 Explode ex2 + 2extdx + t2dx2 - 2exh - 2tdxh + h2 + ey2 + 2eytdy + t2dy2 - 2eyk - 2tdyk + k2 - r2 = 0 Group t2( dx2 + dy2 ) + 2t( exdx + eydy - dxh - dyk ) + ex2 + ey2 - 2exh - 2eyk + h2 + k2 - r2 = 0 Finally, t2( d · d ) + 2t( e · d - d · c ) + e · e - 2( e · c ) + c · c - r2 = 0 Where d is the vector d and · is the dot product. And then, t2( d · d ) + 2t( d · ( e - c ) ) + ( e - c ) · ( e - c ) - r2 = 0 Letting f = e - c t2( d · d ) + 2t( d · f ) + f · f - r2 = 0

所以我们得到: T2 *(d·d) + 2t*(f·d) + (f·f - r2) = 0

求解二次方程:

float a = d.Dot( d ) ;
float b = 2*f.Dot( d ) ;
float c = f.Dot( f ) - r*r ;

float discriminant = b*b-4*a*c;
if( discriminant < 0 )
{
  // no intersection
}
else
{
  // ray didn't totally miss sphere,
  // so there is a solution to
  // the equation.
  
  discriminant = sqrt( discriminant );

  // either solution may be on or off the ray so need to test both
  // t1 is always the smaller value, because BOTH discriminant and
  // a are nonnegative.
  float t1 = (-b - discriminant)/(2*a);
  float t2 = (-b + discriminant)/(2*a);

  // 3x HIT cases:
  //          -o->             --|-->  |            |  --|->
  // Impale(t1 hit,t2 hit), Poke(t1 hit,t2>1), ExitWound(t1<0, t2 hit), 

  // 3x MISS cases:
  //       ->  o                     o ->              | -> |
  // FallShort (t1>1,t2>1), Past (t1<0,t2<0), CompletelyInside(t1<0, t2>1)
  
  if( t1 >= 0 && t1 <= 1 )
  {
    // t1 is the intersection, and it's closer than t2
    // (since t1 uses -b - discriminant)
    // Impale, Poke
    return true ;
  }

  // here t1 didn't intersect so we are either started
  // inside the sphere or completely past it
  if( t2 >= 0 && t2 <= 1 )
  {
    // ExitWound
    return true ;
  }
  
  // no intn: FallShort, Past, CompletelyInside
  return false ;
}

在此post circle中，通过检查圆心与线段上的点(Ipoint)之间的距离来检查线碰撞，该点表示从圆心到线段的法线N(图2)之间的交点。

(https://i.stack.imgur.com/3o6do.png)

在图像1中显示一个圆和一条直线，向量A指向线的起点，向量B指向线的终点，向量C指向圆的中心。现在我们必须找到向量E(从线起点到圆中心)和向量D(从线起点到线终点)这个计算如图1所示。

(https://i.stack.imgur.com/7098a.png)

在图2中，我们可以看到向量E通过向量E与单位向量D的“点积”投影到向量D上，点积的结果是标量Xp，表示向量N与向量D的直线起点与交点(Ipoint)之间的距离。 下一个向量X是由单位向量D和标量Xp相乘得到的。

现在我们需要找到向量Z(向量到Ipoint)，它很容易它简单的向量加法向量A(在直线上的起点)和向量x。接下来我们需要处理特殊情况，我们必须检查是Ipoint在线段上，如果不是我们必须找出它是它的左边还是右边，我们将使用向量最接近来确定哪个点最接近圆。

(https://i.stack.imgur.com/p9WIr.png)

当投影Xp为负时，Ipoint在线段的左边，距离最近的向量等于线起点的向量，当投影Xp大于向量D的模时，距离最近的向量在线段的右边，距离最近的向量等于线终点的向量在其他情况下，距离最近的向量等于向量Z。

现在，当我们有最近的向量，我们需要找到从圆中心到Ipoint的向量(dist向量)，很简单，我们只需要从中心向量减去最近的向量。接下来，检查向量距离的大小是否小于圆半径，如果是，那么它们就会碰撞，如果不是，就没有碰撞。

(https://i.stack.imgur.com/QJ63q.png)

最后，我们可以返回一些值来解决碰撞，最简单的方法是返回碰撞的重叠(从矢量dist magnitude中减去半径)和碰撞的轴，它的向量d。如果需要，交点是向量Z。

You can find a point on a infinite line that is nearest to circle center by projecting vector AC onto vector AB. Calculate the distance between that point and circle center. If it is greater that R, there is no intersection. If the distance is equal to R, line is a tangent of the circle and the point nearest to circle center is actually the intersection point. If distance less that R, then there are 2 intersection points. They lie at the same distance from the point nearest to circle center. That distance can easily be calculated using Pythagorean theorem. Here's algorithm in pseudocode:

{
dX = bX - aX;
dY = bY - aY;
if ((dX == 0) && (dY == 0))
  {
  // A and B are the same points, no way to calculate intersection
  return;
  }

dl = (dX * dX + dY * dY);
t = ((cX - aX) * dX + (cY - aY) * dY) / dl;

// point on a line nearest to circle center
nearestX = aX + t * dX;
nearestY = aY + t * dY;

dist = point_dist(nearestX, nearestY, cX, cY);

if (dist == R)
  {
  // line segment touches circle; one intersection point
  iX = nearestX;
  iY = nearestY;

  if (t < 0 || t > 1)
    {
    // intersection point is not actually within line segment
    }
  }
else if (dist < R)
  {
  // two possible intersection points

  dt = sqrt(R * R - dist * dist) / sqrt(dl);

  // intersection point nearest to A
  t1 = t - dt;
  i1X = aX + t1 * dX;
  i1Y = aY + t1 * dY;
  if (t1 < 0 || t1 > 1)
    {
    // intersection point is not actually within line segment
    }

  // intersection point farthest from A
  t2 = t + dt;
  i2X = aX + t2 * dX;
  i2Y = aY + t2 * dY;
  if (t2 < 0 || t2 > 1)
    {
    // intersection point is not actually within line segment
    }
  }
else
  {
  // no intersection
  }
}

编辑:增加了代码来检查所找到的交点是否实际上在线段内。

圆真的是一个坏人:)所以一个好办法是避免真正的圆，如果可以的话。如果你正在为游戏做碰撞检查，你可以进行一些简化，只做3个点积，并进行一些比较。

我称之为“胖点”或“瘦圈”。它是平行于线段方向上半径为0的椭圆。而是垂直于线段方向的全半径

首先，我会考虑重命名和切换坐标系统，以避免过多的数据:

s0s1 = B-A;
s0qp = C-A;
rSqr = r*r;

其次，hvec2f中的索引h意味着vector必须支持水平操作，如dot()/det()。这意味着它的组件被放置在一个单独的xmm寄存器中，以避免shuffle /hadd'ing/hsub'ing。现在我们开始，最简单的2D游戏碰撞检测的最佳性能版本:

bool fat_point_collides_segment(const hvec2f& s0qp, const hvec2f& s0s1, const float& rSqr) {
    auto a = dot(s0s1, s0s1);
    //if( a != 0 ) // if you haven't zero-length segments omit this, as it would save you 1 _mm_comineq_ss() instruction and 1 memory fetch
    {
        auto b = dot(s0s1, s0qp);
        auto t = b / a; // length of projection of s0qp onto s0s1
        //std::cout << "t = " << t << "\n";
        if ((t >= 0) && (t <= 1)) // 
        {
            auto c = dot(s0qp, s0qp);
            auto r2 = c - a * t * t;
            return (r2 <= rSqr); // true if collides
        }
    }   
    return false;
}

我怀疑你能进一步优化它。我正在用它进行神经网络驱动的赛车碰撞检测，处理数百万个迭代步骤。

好吧，我不会给你代码，但既然你已经标记了这个算法，我认为这对你来说无关紧要。 首先，你要得到一个垂直于这条直线的向量。

y = ax + c是一个未知变量c是未知变量 为了解决这个问题，计算直线经过圆心时的值。

也就是说, 将圆心的位置代入直线方程，解出c。 然后计算原直线与其法线的交点。

这样就能得到直线上离圆最近的点。 计算该点到圆中心之间的距离(使用矢量的大小)。 如果这个小于圆的半径，看，我们有一个交点!

基于@Joe Skeen的python解决方案

def check_line_segment_circle_intersection(line, point, radious):
    """ Checks whether a point intersects with a line defined by two points.

    A `point` is list with two values: [2, 3]

    A `line` is list with two points: [point1, point2]

    """
    line_distance = distance(line[0], line[1])
    distance_start_to_point = distance(line[0], point)
    distance_end_to_point = distance(line[1], point)

    if (distance_start_to_point <= radious or distance_end_to_point <= radious):
        return True

    # angle between line and point with law of cosines
    numerator = (math.pow(distance_start_to_point, 2)
                 + math.pow(line_distance, 2)
                 - math.pow(distance_end_to_point, 2))
    denominator = 2 * distance_start_to_point * line_distance
    ratio = numerator / denominator
    ratio = ratio if ratio <= 1 else 1  # To account for float errors
    ratio = ratio if ratio >= -1 else -1  # To account for float errors
    angle = math.acos(ratio)

    # distance from the point to the line with sin projection
    distance_line_to_point = math.sin(angle) * distance_start_to_point

    if distance_line_to_point <= radious:
        point_projection_in_line = math.cos(angle) * distance_start_to_point
        # Intersection occurs whent the point projection in the line is less
        # than the line distance and positive
        return point_projection_in_line <= line_distance and point_projection_in_line >= 0
    return False

def distance(point1, point2):
    return math.sqrt(
        math.pow(point1[1] - point2[1], 2) +
        math.pow(point1[0] - point2[0], 2)
    )