Dynamic Cover Selection via Spatial Queries

Students will build a tactical system that identifies the best defensive cover spots by analyzing proximity and incoming fire paths.

In this lesson, you will learn how to leverage the Environmental Query System (EQS) to dynamically identify and select the safest cover spot based on an AI's real-time surroundings.

The Logic of Tactical Positioning

Standard pathfinding only gets an AI to a coordinate; it doesn't understand "safety." To implement dynamic cover selection, we define a "Cover Point" not just as a location, but as a spatial score. We utilize an EQS query to sample the environment around the AI, filtering points that offer protection from incoming fire.

Combining Spatial Sampling and Trace Tests

To find a cover spot, we need two primary components:

The Generator: Use a Points: Grid or Points: Circles generator centered on the AI to sample potential locations.
The Tests: This is where we analyze the "safety" of those points.
- Trace Test: Run a line trace from the current enemy position to the potential cover spot. If the trace hits geometry (like a wall or crate), the point is considered "covered."
- Distance Test: We score the points based on proximity to the AI, ensuring the bot doesn't travel across the entire level for minor protection.

By setting the Scoring Equation to "Multiply" in your EQS test, you can combine these values. For instance, you might weight the Trace Test heavily to favor points with high obstruction (blocking enemy sightlines) while using the Distance Test to prefer points closer to the AI’s current position.

// Logic flow for selecting the optimal point:
// 1. Generate grid of points around AI.
// 2. Filter: Remove points where a Trace hits nothing (exposed).
// 3. Score: Rank remaining points by Distance (closer is better).
// 4. Return: The highest-scoring location to the Blackboard Key.

When you trigger this query via a Run EQS Query node in your Behavior Tree, the AI will dynamically pick the best defensive spot available at that exact moment. If the enemy moves, the next query will automatically adjust the scores, forcing the AI to relocate if its current cover becomes compromised.

Key Takeaway: Dynamic cover selection transforms static geometry into tactical intelligence by scoring points based on their ability to block enemy lines of sight while minimizing AI traversal distance.