It sounds like you’re diving deep into some really interesting concepts in computer graphics! The idea of the canonical viewing volume (CVV) is a fundamental part of transforming 3D points into a 2D perspective, and I can help break it down for you.

Imagine you have a 3D space where all your points (like the ones defining objects) exist. When you want to project this 3D scene onto a 2D plane (like your computer screen), you need a way to ensure that depth is represented correctly so everything appears in the right place from the observer’s point of view.

The canonical viewing volume is like a box within this 3D space that defines what part of the world you’re allowed to see. Think of it like the frame of a painting. Anything outside this frame won’t be visible to the viewer, just like you can’t see outside the edges of a photo.

To get from 3D to 2D, we often use a method called homogeneous coordinates. This adds an extra dimension, which simplifies the math for transforming these points. Instead of dealing directly with x, y, and z coordinates, we can work with (x, y, z, w) coordinates, where ‘w’ helps us manage perspective.

Now, to fit your 3D points into the canonical viewing volume, you perform a series of transformations using matrices. This is where the homogeneous matrices come into play! They allow you to apply multiple transformations (like rotation, translation, and scaling) in one go, which is super handy and efficient.

When rendering a scene:

• You first transform your 3D points into the CVV using these matrices.
• Next, you apply perspective division (using that ‘w’ from the homogeneous coordinates) to bring them back down to 2D.

By understanding how to set up your CVV and use matrix transformations, you’re essentially creating a bridge between the 3D world and the 2D display. This ensures that everything you “see” on the screen represents the 3D points accurately, maintaining relative positions and depth cues.

It can be a bit of a puzzle at first, but once you see how these pieces fit together, it’s like a light bulb goes off! Keep experimenting and playing around with these concepts, and it will start to click.

Handling AI decisions in games is super interesting! It sounds like you’re trying to balance realism in how the AI behaves while also making sure it feels smooth and natural for players. I totally get where you’re coming from with the movement and attack decision-making.

On one hand, separating the actions can give you more control and allow the AI to consider specific details like health or armor before deciding to attack. But I think you’re right that players usually think of their movement in relation to who they want to engage, so combining them seems more intuitive.

If you combine them into one decision, maybe you could still have some checkpoints where the AI evaluates the target’s condition before finalizing that action? Like, does the AI check the target’s health first, then decides to move and attack in one go? This way, you’re not losing the complexity but still keeping that fluidity.

Ultimately, it might depend on how you envision the gameplay. If the AI feels too rigid with separate actions, it might break that immersion for players. But if it’s too mixed, it might feel like it’s missing some strategy aspects. Maybe test both ways in a simplified version and see which feels better!

In the end, your AI should reflect the player’s mindset but still be smart enough to consider those important details that make the game engaging. Good luck, and I’d love to hear what you decide!

Combining Vertex, Texture, and Normal Indices in an OBJ Parser

It sounds like you’re on the right track by wanting to avoid multiple EBOs! The idea of combining vertex, texture, and normal indices into a single structure can definitely help streamline your rendering process.

You could consider creating a single vertex structure that holds all the necessary data for each vertex. For instance, you might set up a structure like this:

    struct Vertex {
        glm::vec3 position;   // Vertex position
        glm::vec2 texCoord;   // Texture coordinate
        glm::vec3 normal;     // Vertex normal
    };
    

After defining your vertex structure, you’ll want to create a single array of vertices instead of separate arrays for positions, texture coordinates, and normals.

When you parse the OBJ file, you’ll read the vertex, texture, and normal indices and then build your vertex array accordingly. Instead of having separate index buffers for vertex positions, texture coordinates, and normals, you can do something like this:

    std::vector vertices;
    for (const auto& face : faces) {
        for (const auto& index : face.indices) {
            Vertex vertex;
            vertex.position = positions[index.vertexIndex];
            vertex.texCoord = texCoords[index.textureIndex];
            vertex.normal = normals[index.normalIndex];
            vertices.push_back(vertex);
        }
    }
    

This way, you can create a single VBO (Vertex Buffer Object) from your vertex array and a single EBO that uses the vertex indices. When binding your vertex data with a VAO (Vertex Array Object), just make sure to set the attributes correctly:

    glVertexAttribPointer(0, 3, GL_FLOAT, GL_FALSE, sizeof(Vertex), (GLvoid*)offsetof(Vertex, position));
    glVertexAttribPointer(1, 2, GL_FLOAT, GL_FALSE, sizeof(Vertex), (GLvoid*)offsetof(Vertex, texCoord));
    glVertexAttribPointer(2, 3, GL_FLOAT, GL_FALSE, sizeof(Vertex), (GLvoid*)offsetof(Vertex, normal));
    

In this way, you are effectively mapping each vertex to its attributes in one unified structure, making it easier to work with and potentially more efficient for rendering.

Ultimately, this combination approach can simplify the management of your meshes while ensuring that you can still use texture and normal mapping effectively. Good luck with your OBJ parser!