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