Building a Path Network for AI Navigation in Unity: A Step-by-Step Guide

Introduction to Path Network Navigation in Games

Path planning is a cornerstone of artificial intelligence in modern video games. Whether you're playing a battle royale title like Fortnite, an open-world RPG like Elden Ring, or a stealth-based game like Metal Gear Solid, AI agents need to navigate complex environments without bumping into walls or obstacles. While grid-based navigation (like tile maps) works for simple 2D games, many 3D games require a more continuous representation of space. Enter the path network: a set of nodes and edges that discretizes the environment into a small, efficient graph. In this tutorial, you'll learn how to implement a path network in Unity, inspired by assignments like Cs7632 homework 2. We'll cover edge validation, obstacle intersection checks, and even the optional Points of Visibility (PoV) algorithm. By the end, you'll have a solid foundation for building AI navigation systems used in professional game development.

What Is a Path Network?

A path network consists of path nodes (points in space) and edges (connections between nodes). Unlike a grid, the agent does not need to be exactly at a node; it can be anywhere in the terrain. When the agent needs to move, it first moves to the nearest accessible node, then follows the path network to a node near the destination, and finally moves directly to the target. This approach reduces the number of transitions and allows smoother movement around obstacles.

Key Properties of a Valid Edge

For an edge to exist between two nodes, three conditions must hold:

• No obstacle or boundary wall lies between the two nodes.
• Sufficient clearance exists on both sides of the edge so that an agent of a given radius can traverse without collision.
• Both nodes are inside the boundary and outside any obstacles.

Edges must be bidirectional and unique: if node A connects to node B, node B must also connect to node A, and the edge should appear only once in each node's edge list. No self-loops are allowed. Even if two nodes are arbitrarily close (or at the same location), they should still be connected.

Setting Up the Unity Project

Before writing code, ensure you have the Unity project set up with the provided scene. Open Assets/Scripts/GameAIStudentWork/PathNetwork/CreatePathNetwork.cs. The Create() method is where you'll implement your logic. It receives parameters like canvasOrigin, canvasWidth, canvasHeight, a list of obstacles (polygons), agentRadius, and a reference list of pathNodes. The output is a list of pathEdges. There are two modes: Predefined (nodes are provided) and PointsOfVisibility (nodes are generated using the PoV algorithm). We'll focus on the Predefined mode first.

Implementing Edge Generation for Predefined Nodes

Your task is to iterate over all pairs of nodes and determine if a valid edge exists. Here's a step-by-step approach:

Step 1: Validate Node Positions

First, ensure each node is inside the canvas boundary and not inside any obstacle. Use the provided utility functions like IsInsideBoundary() and IsInsideObstacle(). Remove any invalid nodes from consideration (or simply skip them).

Step 2: Check Line-of-Sight

For each pair of valid nodes (i, j) with i < j, check if the straight line between them intersects any obstacle. Use the polygon's getPoints() method to get vertices and implement a segment intersection test. If the line segment intersects any obstacle edge, skip this pair.

Step 3: Check Clearance

Even if the line doesn't intersect an obstacle, the agent might still collide if the path passes too close to an obstacle. For each obstacle, compute the distance from the line segment to the obstacle's edges. If the minimum distance is less than agentRadius, the edge is invalid. Use the DistanceToLineSegment() function provided.

Step 4: Add Valid Edges

If both checks pass, add the edge to both nodes' lists. Ensure no duplicates by checking if the edge already exists.

Handling Edge Cases

Think about scenarios like:

• No nodes: Return an empty edge list.
• Single node: No edges possible.
• Nodes at identical positions: They should still be connected (edge length zero).
• Nodes near boundaries: Ensure they are considered inside the canvas.

Test your code with different obstacle configurations using the provided test scene. Press buttons 1,2,3 to load preset layouts. Click on obstacles to drag them and see how your network adapts.

Introduction to Points of Visibility (PoV)

If you want to go beyond the basic requirement, implement the Points of Visibility algorithm. This generates path nodes automatically from obstacle vertices. The idea is to place nodes at obstacle vertices and then connect them if they are mutually visible. The algorithm uses parameters minPoVDist and maxPoVDist to limit how far a node can be from the vertex. This is similar to how AI in games like Counter-Strike might navigate around corners.

PoV Algorithm Steps

1. For each obstacle vertex, generate candidate points along the angle bisector at distances between minPoVDist and maxPoVDist.
2. Filter out points that are inside obstacles or outside the boundary.
3. Add these points to the pathNodes list.
4. Then run the same edge generation logic as before to connect them.

This approach can create a more natural path network that covers the navigable space efficiently.

Testing and Debugging

Unity's scene view is your best friend. After implementing, hit Play and observe the edges drawn between nodes. If edges are missing, check your intersection and clearance logic. Use Debug.DrawLine to visualize candidate edges. The provided PathNetworkTest file contains unit tests; you should add your own to cover edge cases like overlapping obstacles or zero-radius agents.

Real-World Applications and Trends

Path network navigation isn't just for games. In 2026, AI-powered autonomous drones use similar techniques for delivery routing. The same principles apply to robotic vacuum cleaners navigating around furniture. Even in the metaverse, avatars need to walk without phasing through walls. Understanding these algorithms gives you a skill that's in high demand across AI, robotics, and game development.

Conclusion

You've now learned how to build a path network for AI agents in Unity. By implementing edge validation with obstacle and clearance checks, you've created a robust navigation system. If you tackled the PoV extension, you've automated node generation as well. These techniques are used in AAA games and simulations. Keep experimenting with different obstacle layouts and agent radii to see how the network adapts. Happy coding!

Pro tip: Always test with edge cases like extremely small agent radii or large obstacles to ensure your code handles all scenarios gracefully.