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extends AIController3D
class_name RobotAIController
@onready var robot: Robot = get_parent()
@onready var sensors: Array[Node] = $"../Sensors".get_children()
@onready var level_manager = robot.level_manager
var closest_goal_position
func reset():
super.reset()
closest_goal_position = xz_distance(robot.global_position,
robot.current_goal_transform.origin)
func _physics_process(_delta):
n_steps += 1
if n_steps > reset_after:
needs_reset = true
done = true
reward -= 1
func get_obs() -> Dictionary:
var velocity: Vector3 = robot.get_real_velocity().limit_length(20.0) / 20.0
var current_goal_position: Vector3 = robot.current_goal_transform.origin
var local_goal_position = robot.to_local(current_goal_position).limit_length(40.0) / 40.0
var closest_coin = level_manager.get_closest_active_coin(robot.global_position, robot.current_level)
var closest_coin_position: Vector3 = Vector3.ZERO
if closest_coin:
closest_coin_position = robot.to_local(closest_coin.global_position)
if closest_coin_position.length() > 30.0:
closest_coin_position = Vector3.ZERO
var closest_enemy: Enemy = level_manager.get_closest_enemy(robot.global_position)
var closest_enemy_position: Vector3 = Vector3.ZERO
var closest_enemy_direction: float = 0.0
if closest_enemy:
closest_enemy_position = robot.to_local(closest_enemy.global_position)
closest_enemy_direction = float(closest_enemy.movement_direction)
if closest_enemy_position.length() > 30.0:
closest_enemy_position = Vector3.ZERO
closest_enemy_direction = 0.0
var observations: Array[float] = [
float(n_steps) / reset_after,
local_goal_position.x,
local_goal_position.y,
local_goal_position.z,
closest_coin_position.x,
closest_coin_position.y,
closest_coin_position.z,
closest_enemy_position.x,
closest_enemy_position.y,
closest_enemy_position.z,
closest_enemy_direction,
velocity.x,
velocity.y,
velocity.z,
float(robot.level_manager.check_all_coins_collected(robot.current_level))
]
observations.append_array(get_raycast_sensor_obs())
return {"obs": observations}
func xz_distance(vector1: Vector3, vector2: Vector3):
var vec1_xz := Vector2(vector1.x, vector1.z)
var vec2_xz := Vector2(vector2.x, vector2.z)
return vec1_xz.distance_to(vec2_xz)
func get_reward() -> float:
var current_goal_position = xz_distance(robot.global_position,
robot.current_goal_transform.origin)
if not closest_goal_position:
closest_goal_position = current_goal_position
if current_goal_position < closest_goal_position:
reward += (closest_goal_position - current_goal_position) / 10.0
closest_goal_position = current_goal_position
return reward
func get_action_space() -> Dictionary:
return {
"movement" : {
"size": 2,
"action_type": "continuous"
}
}
func set_action(action) -> void:
robot.requested_movement = Vector3(
clampf(action.movement[0], -1.0, 1.0),
0.0,
clampf(action.movement[1], -1.0, 1.0)).limit_length(1.0)
func get_raycast_sensor_obs():
var all_raycast_sensor_obs: Array[float] = []
for raycast_sensor in sensors:
all_raycast_sensor_obs.append_array(raycast_sensor.get_observation())
return all_raycast_sensor_obs
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