Introduction to ray casting in 2D game engines, featuring mathematical algorithms and optimization techniques for game development

Introduction to ray casting in 2D game engines

#math#ray-casting#2d#game-engine#dev

Ray casting is a fascinating concept that isn’t overly complex to grasp. However, finding high-quality learning materials on the subject can be a challenge. We’ll delve into the mathematical aspects, making it easy for you to integrate into your future projects. I’ll explain things clearly, covering potential challenges and pitfalls. We’ll also explore optimization strategies, such as the significant advantages of using spatial hash maps. Keep in mind that the demos are intentionally kept simple; the goal is to understand the concept rather than delve into intricate coding details.

What is ray casting

Ray casting is the most basic of many computer graphics rendering algorithms that use the geometric algorithm of ray tracing. Ray tracing-based rendering algorithms operate in image order to render three-dimensional scenes to two-dimensional images… The idea behind ray casting is to trace rays from the eye, one per pixel, and find the closest object blocking the path of that ray – think of an image as a screen-door, with each square in the screen being a pixel. This is then the object the eye sees through that pixel. — Wikipedia on Ray casting

Let me break it down. Ray casting is a crucial and widely-used method to figure out if certain objects (polygons) are visible. This is done by tracing rays from the eye (like the player’s hero) to every pixel (though not exactly in our case - more on that later) and identifying the closest intersections with objects.

Wolfenstein 3D

Wolfenstein 3D stands out as a prime example of a game that extensively utilized this technique. In the process, rays were traced to identify the closest objects. The distances from the player’s position were then used to scale these objects appropriately within the player’s view.

Wolfenstein 3D

Point-in-polygon problem

The PIP problem involves determining whether a given point is inside, outside, or on the boundary of a polygon. Using the ray casting algorithm, we can track the number of times the point intersects the edges of the polygon. If the count of intersections is even, the point is outside the polygon. Conversely, if the count is odd, the point is located either inside the polygon or on its boundary.

PIP problem

Object visibility and light casting

This section will cover fundamental concepts, including the calculation of intersection points, the process of casting rays, sorting intersection points to illuminate the visible area, and a brief discussion about circles.

Segment - ray intersection point

Let’s get into intersection points. We’ll break it down step by step, figuring out how to find them and make good use of them. First up, we’ll discuss a line’s parametric equation. Then, we’ll dive into the fun part – calculating the points. To wrap it up, we’ll chat about a smart way to figure out which one of these points is the closest.

Deriving line parametric equation

We can express vector AP\vec{AP} by the following equation: AP=tAB\vec{AP} = t\vec{AB}, where t{t} is an equation parameter defining how much do we stretch, shrink, or if we flip the direction of vector AP\vec{AP} in relation to vector AB\vec{AB}.

Let’s get through with an example:

Vectors

As you might have noticed, we can use tt as a scale factor: d(A,P)=td(A,B)d(A,P) = t*d(A,B), where dd denotes the euclidean distance between two points. We’ll make good use of that fact when figuring out which intersection point is the closest.

Now we can easily see, that if we want the point to be contained on:

  • line - tRt \in \mathbb{R}
  • ray - t0t \geqslant 0
  • segment - 0t10 \leqslant t \leqslant 1

If you still do not know what happens here, I can recommend an awesome short lecture by Norm Prokup.

Calculating the intersection point

Let’s consider point PP as the intersection point between the segment defined by points AA and BB and the ray defined by points CC and DD. The expression for point PP can then be represented by a set of two equations:

  • P=s(BA)+AP = s(B - A) + A, where 0s10 \leqslant s \leqslant 1,
  • P=r(DC)+CP = r(D - C) + C, where r0r \geqslant 0.

By solving for ss and rr, we obtain:

  • r=(CyAy)(BxAx)(CxAx)(ByAy)(DxCx)(ByAy)(BxAx)(DyCy)r = \tfrac{(C_y - A_y)(B_x - A_x) - (C_x - A_x)(B_y - A_y)}{(D_x - C_x)(B_y - A_y) - (B_x - A_x)(D_y - C_y)}
  • s=(AxCx)(DyCy)(DxCx)(AyCy)(DxCx)(ByAy)(BxAx)(DyCy)s = \tfrac{(A_x - C_x)(D_y - C_y) - (D_x - C_x)(A_y-C_y)}{(D_x - C_x)(B_y - A_y) - (B_x - A_x)(D_y - C_y)}

Next, we can calculate PP using one of the equations from the set.

Finding the closest intersection point

To find the closest intersection point for properly drawing the visible area, a straightforward approach involves calculating distances between the ray starting point and intersection points using the Pythagorean Theorem: (CxPx)2+(Cy+Py)2\sqrt{(C_x - P_x)^2 + (C_y + P_y)^2}. However, taking into account the line equation parameter rr, we can use it as a scale factor. To compare distances along the ray, we simply check for the smallest parameter value: CP1<CP2r1<r2\lvert\vec{CP_1}\rvert < \lvert\vec{CP_2}\rvert \Leftrightarrow \lvert r_1 \rvert < \lvert r_2 \rvert.

Casting rays

Casting rays by offset angle

One approach is to cast rays in all directions with a specified offset angle. For example, we could cast a total of 30 rays, each offset by 12°. Let’s start by exploring how to generate all these rays.

Let P1=(x1,y1)P_1=(x_1,y_1) be an anchor point of our rays, and let P2=(x2,y2)P_2=(x_2,y_2) be a point on a line going through P1P_1 at an angle ϕ\phi:

Offset angle

Let’s define x2=x1+dxx_2 = x_1 + d_x and y2=y1dyy_2 = y_1 - d_y (inverted y-axis).

Using the image above, we can derive formulas for dxd_x and dyd_y:

  • dx=d(P1,P2)cos(ϕ)d_x = d(P_1, P_2) * cos(\phi),
  • dy=d(P1,P2)sin(ϕ)d_y = d(P_1, P_2) * sin(\phi).

In our case, the distance d(P1,P2)d(P_1, P_2) has an arbitrary (greater than 0) value, as we are looking for any point on the line. Therefore, we can safely assume d(P1,P2)=1d(P_1, P_2) = 1 to simplify the calculations. Taking this into consideration, P2=(x1+sin(ϕ),y1cos(ϕ))P_2 = (x_1 + sin(\phi), y_1 - cos(\phi)) where ϕ\phi is our angle offset.

Casting rays on vertices

Casting rays on vertices is probably your preferred approach. Rather than casting rays in all directions, we can simplify the process by casting them directly on the vertices of our polygons. This approach, depending on the number of vertices, allows us to conserve computing power by avoiding unnecessary ray casts. It will be the only method utilized in the upcoming sections.

Illuminating the visible area

Get ready for the exciting part! We’re about to light up the visible area by filling in a massive polygon.

Sorting intersection points

To arrange vertices correctly and construct a proper polygon, we need to first sort them by angle. For this, we’ll utilize the atan2(y, x) function.

Now, let’s check how it looks:

It seems to be glitchy, jumpy, and inaccurate. Let’s investigate the underlying reasons for these issues.

Casting slightly offset rays

Take note of what occurs when rays are cast directly onto vertices - they are expected to extend beyond that vertex, but we are currently only obtaining the closest intersection point. A common solution involves casting two additional rays offset by a small angle (in both directions) for every primary ray cast.

Offset rays

Consider a ray R starting at A=(Ax,Ay)A=(A_x, A_y) and going through B=(Bx,By)B=(B_x, B_y). We aim to find a point C=(Cx,Cy)C=(C_x, C_y) such that the ray R would be rotated by an angle ϕ\phi with A being the origin point. The coordinates of C would be as follows:

  • Cx=(BxAx)cos(ϕ)(ByAy)sin(ϕ)+AxC_x = (B_x - A_x)cos(\phi) - (B_y - A_y)sin(\phi) + A_x
  • Cy=(BxAx)sin(ϕ)+(ByAy)cos(ϕ)+AyC_y = (B_x - A_x)sin(\phi) + (B_y - A_y)cos(\phi) + A_y

For further explanation you can check this article.

Introducing flashlight

To restrict the player’s visibility, we can establish a clipping region in the desired shape. In the demonstrations below, I utilized the CanvasRenderingContext2D.clip() method.

Optimization techniques

In this section, we will explore the utilization of spatial hashmaps and a modified Bresenham’s line algorithm. I won’t delve into implementation details, as they are readily available on the Internet. Nevertheless, I’ll provide you with some demos to experiment with and encourage you to come up with your own ideas on how to apply these techniques.

Spatial hashmaps

Currently, we are drawing all polygons and calculating all intersection points, but this is often inefficient. Typically, our play area will be much larger than the viewport. By implementing spatial hashmaps, we can easily identify which polygons are visible to the player and carry out appropriate calculations.

Essentially, the idea is to partition the play area into smaller cells of a predefined size. Each cell comprises a list containing our shapes, which are most likely line segments. If a single shape spans across multiple cells, it will be included in all of them.

Although the technique’s name suggests using hashmaps, in our case, employing a simple 2D array is more practical.

Below is a basic demo illustrating how this approach might function:

Bresenham-based supercover line algorithm

It’s about time we address the matter of finding the closest intersection points. By incorporating spatial hashmaps and a modified Bresenham’s line algorithm, we can navigate the grid efficiently, minimizing the number of checks needed. The algorithm should halt as soon as the first cell with an intersection point is discovered.

Read more about Bresenham’s line algorithm here, and its modified version here.

Everything has an end

I believe I’ve covered everything to assist you in getting started. I’ll do my best to expand on it in the future if I identify areas that need additional explanation.

If you enjoyed the content, be sure to follow me for more similar content in the future. Also, don’t hesitate to reach out if you find any topic poorly explained or if you have other suggestions.

See you!

← Back to Blog