Getting Started

This guide will get you started using the tool with a complete AI agent example written in GDScript.

The steering toolkit being a framework, you need to use GDScript code to design and control AI agents.

In the steering toolkit repository, you will find many demos that showcase the steering toolkit in action, including path follow, blended movement, and group behaviors.

The goal of this class is to show how an agent can chase a player and predict where the player will be while also maintaining a distance from them, with some complex behaviors:

  • When the agent’s health becomes low, it flees the player.
  • The agent keeps facing the player while it’s chasing them, but it looks where it’s going while it’s fleeing.
  • The agent smoothly blends between its behaviors.

Our game is in 2D and assumed to be a top-down spaceship game.

You can see this example demo in action by running the Demos/QuickStart/QuickStartDemo.tscn scene in Godot or selecting the QuickStart demo in the demo selector scene.

extends KinematicBody2D

# Maximum possible linear velocity
export var speed_max := 450.0
# Maximum change in linear velocity
export var acceleration_max := 50.0
# Maximum rotation velocity represented in degrees
export var angular_speed_max := 240
# Maximum change in rotation velocity represented in degrees
export var angular_acceleration_max := 40

export var health_max := 100
export var flee_health_threshold := 20

var velocity := Vector2.ZERO
var angular_velocity := 0.0
var linear_drag := 0.1
var angular_drag := 0.1

# Holds the linear and angular components calculated by our steering behaviors.
var acceleration := GSAITargetAcceleration.new()

onready var current_health := health_max

# GSAISteeringAgent holds our agent's position, orientation, maximum speed and acceleration.
onready var agent := GSAISteeringAgent.new()

onready var player: Node = get_tree().get_nodes_in_group("Player")[0]
# This assumes that our player class will keep its own agent updated.
onready var player_agent: GSAISteeringAgent = player.agent

# Proximities represent an area with which an agent can identify where neighbors in its relevant
# group are. In our case, the group will feature the player, which will be used to avoid a
# collision with them. We use a radius proximity so the player is only relevant inside 100 pixels.
onready var proximity := GSAIRadiusProximity.new(agent, [player_agent], 100)

# GSAIBlend combines behaviors together, calculating all of their acceleration together and adding
# them together, multiplied by a strength. We will have one for fleeing, and one for pursuing,
# toggling them depending on the agent's health. Since we want the agent to rotate AND move, then
# we aim to blend them together.
onready var flee_blend := GSAIBlend.new(agent)
onready var pursue_blend := GSAIBlend.new(agent)

# GSAIPriority will be the main steering behavior we use. It holds sub-behaviors and will pick the
# first one that returns non-zero acceleration, ignoring any afterwards.
onready var priority := GSAIPriority.new(agent)


func _ready() -> void:
	# ---------- Configuration for our agent ----------
	agent.linear_speed_max = speed_max
	agent.linear_acceleration_max = acceleration_max
	agent.angular_speed_max = deg2rad(angular_speed_max)
	agent.angular_acceleration_max = deg2rad(angular_acceleration_max)
	agent.bounding_radius = calculate_radius($CollisionPolygon2D.polygon)
	update_agent()

	# ---------- Configuration for our behaviors ----------
	# Pursue will happen while the agent is in good health. It produces acceleration that takes
	# the agent on an intercept course with the target, predicting its position in the future.
	var pursue := GSAIPursue.new(agent, player_agent)
	pursue.predict_time_max = 1.5

	# Flee will happen while the agent is in bad health, so will start disabled. It produces
	# acceleration that takes the agent directly away from the target with no prediction.
	var flee := GSAIFlee.new(agent, player_agent)

	# AvoidCollision tries to keep the agent from running into any of the neighbors found in its
	# proximity group. In our case, this will be the player, if they are close enough.
	var avoid := GSAIAvoidCollisions.new(agent, proximity)

	# Face turns the agent to keep looking towards its target. It will be enabled while the agent
	# is not fleeing due to low health. It tries to arrive 'on alignment' with 0 remaining velocity.
	var face := GSAIFace.new(agent, player_agent)

	# We use deg2rad because the math in the toolkit assumes radians.
	# How close for the agent to be 'aligned', if not exact.
	face.alignment_tolerance = deg2rad(5)
	# When to start slowing down
	face.deceleration_radius = deg2rad(60)

	# LookWhereYouGo turns the agent to keep looking towards its direction of travel. It will only
	# be enabled while the agent is at low health.
	var look := GSAILookWhereYouGo.new(agent)
	# How close for the agent to be 'aligned', if not exact
	look.alignment_tolerance = deg2rad(5)
	# When to start slowing down.
	look.deceleration_radius = deg2rad(60)

	# Behaviors that are not enabled produce 0 acceleration.
	# Adding our fleeing behaviors to a blend. The order does not matter.
	flee_blend.is_enabled = false
	flee_blend.add(look, 1)
	flee_blend.add(flee, 1)

	# Adding our pursuit behaviors to a blend. The order does not matter.
	pursue_blend.add(face, 1)
	pursue_blend.add(pursue, 1)

	# Adding our final behaviors to the main priority behavior. The order does matter here.
	# We want to avoid collision with the player first, flee from the player second when enabled,
	# and pursue the player last when enabled.
	priority.add(avoid)
	priority.add(flee_blend)
	priority.add(pursue_blend)


func _physics_process(delta: float) -> void:
	# Make sure any change in position and speed has been recorded.
	update_agent()

	if current_health <= flee_health_threshold:
		pursue_blend.is_enabled = false
		flee_blend.is_enabled = true

	# Calculate the desired acceleration.
	priority.calculate_steering(acceleration)

	# We add the discovered acceleration to our linear velocity. The toolkit does not limit
	# velocity, just acceleration, so we clamp the result ourselves here.
	velocity = (velocity + Vector2(acceleration.linear.x, acceleration.linear.y) * delta).clamped(
		agent.linear_speed_max
	)

	# This applies drag on the agent's motion, helping it to slow down naturally.
	velocity = velocity.linear_interpolate(Vector2.ZERO, linear_drag)

	# And since we're using a KinematicBody2D, we use Godot's excellent move_and_slide to actually
	# apply the final movement, and record any change in velocity the physics engine discovered.
	velocity = move_and_slide(velocity)

	# We then do something similar to apply our agent's rotational speed.
	angular_velocity = clamp(
		angular_velocity + acceleration.angular * delta, -agent.angular_speed_max, agent.angular_speed_max
	)
	# This applies drag on the agent's rotation, helping it slow down naturally.
	angular_velocity = lerp(angular_velocity, 0, angular_drag)
	rotation += angular_velocity * delta


# In order to support both 2D and 3D, the toolkit uses Vector3, so the conversion is required
# when using 2D nodes. The Z component can be left to 0 safely.
func update_agent() -> void:
	agent.position.x = global_position.x
	agent.position.y = global_position.y
	agent.orientation = rotation
	agent.linear_velocity.x = velocity.x
	agent.linear_velocity.y = velocity.y
	agent.angular_velocity = angular_velocity


# We calculate the radius from the collision shape - this will approximate the agent's size in the
# game world, to avoid collisions with the player.
func calculate_radius(polygon: PoolVector2Array) -> float:
	var furthest_point := Vector2(-INF, -INF)
	for p in polygon:
		if abs(p.x) > furthest_point.x:
			furthest_point.x = p.x
		if abs(p.y) > furthest_point.y:
			furthest_point.y = p.y
	return furthest_point.length()


func damage(amount: int) -> void:
	current_health -= amount
	if current_health <= 0:
		queue_free()