feat: possibly done! Decrease simulator refresh rate

Dockerfile-gym-ros

@@ -74,10 +74,13 @@ RUN echo "source /opt/ros/foxy/setup.bash" >> ~/.bashrc && \
     mv f1tenth_racetracks /sim_ws/src/car_node/car_node/map/
 
 COPY model-gym-ros-env/car_node/setup.py /sim_ws/src/car_node/setup.py
-COPY model-gym-ros-env/car_node/car_node/main.py model-gym-ros-env/car_node/car_node/wrapper.py model-gym-ros-env/car_node/car_node/map_utility.py model-gym-ros-env/car_node/car_node/setup.py /sim_ws/src/car_node/car_node/
+COPY model-gym-ros-env/car_node/car_node/main.py model-gym-ros-env/car_node/car_node/setup.py /sim_ws/src/car_node/car_node/
+
+COPY model-gym-ros-env/f1tenth_gym_ros/config/sim.yaml /sim_ws/src/f1tenth_gym_ros/config/sim.yaml
+COPY model-gym-ros-env/f1tenth_gym_ros/f1tenth_gym_ros/gym_bridge.py /sim_ws/src/f1tenth_gym_ros/f1tenth_gym_ros/gym_bridge.py
+
 COPY train_test /sim_ws/src/car_node/car_node/train_test
 COPY models/* /sim_ws/src/car_node/car_node/models/
-COPY model-gym-ros-env/f1tenth_gym_ros/config/sim.yaml /sim_ws/src/f1tenth_gym_ros/config/sim.yaml
 
 RUN pip install -e /sim_ws/src/car_node/car_node && \
     source /opt/ros/foxy/setup.bash && \

model-gym-ros-env/car_node/car_node/main.py

@@ -8,23 +8,16 @@
 from sensor_msgs.msg import LaserScan
 from ackermann_msgs.msg import AckermannDriveStamped
 
-
-import gym
 from stable_baselines3 import PPO
-from car_node.wrapper import F110_Wrapped
-from f110_gym.envs.base_classes import Integrator
-from car_node.map_utility import get_map, get_formatted_map, map_ext
 from car_node.wrapper import convert_range
 
-timestep = 0.01
-tensorboard_path = './train_test/'
-map = "BrandsHatch"
-path = get_map(map)
-map_path = get_formatted_map(path)
 device = 'cpu'
 
-STEER_SCALE = 0.5
-SPEED_SCALE = 0.7
+STEERING_RANGE_MIN = -0.4189
+STEERING_RANGE_MAX = 0.4189
+SPEED_RANGE_MIN = -5
+SPEED_RANGE_MAX = 20
+MODEL_INTERVAL = [-1, 1]
 
 class PPOModelEvaluator(Node):
 
@@ -35,31 +28,25 @@ def __init__(self):
         lidarscan_topic = '/scan'
         drive_topic = '/drive'
 
-        # Model & Env
-        self.eval_env  = gym.make('f110_gym:f110-v0', map=map_path, map_ext=map_ext, num_agents=1, timestep=timestep, integrator=Integrator.RK4)
-        self.eval_env = F110_Wrapped(self.eval_env, random_map=False)
-        self.eval_env.set_map_path(path)
-        self.model = PPO.load("/sim_ws/src/car_node/car_node/train_test/best_global_model", self.eval_env, device=device)
-        self.vec_env = self.model.get_env()
+        self.model = PPO.load("/sim_ws/src/car_node/car_node/models/YasMarina_optimize_model.zip", device=device)
 
         # ROS 
         self.lidar_sub = self.create_subscription(LaserScan, lidarscan_topic, self.lidar_callback, 10)
         self.drive_pub = self.create_publisher(AckermannDriveStamped, drive_topic, 10)
 
     def lidar_callback(self, data):
         d = np.array(data.ranges, dtype=np.float64)
-        d = convert_range(d, [data.angle_min, data.angle_max], [-1, 1])
-
-        action, _states = self.model.predict(d, deterministic=True)
-        action = self.eval_env.un_normalise_actions(action)
+        d = convert_range(d, [data.range_min, data.range_max], MODEL_INTERVAL)
 
-        self.get_logger().info(f'{action[0], action[1]}')
+        action = self.model.predict(d, deterministic=True)[0]
+        steer = convert_range(action[0], MODEL_INTERVAL, [STEERING_RANGE_MIN, STEERING_RANGE_MAX])
+        speed = convert_range(action[1], MODEL_INTERVAL, [SPEED_RANGE_MIN, SPEED_RANGE_MAX])
 
         drive_msg = AckermannDriveStamped()
         drive_msg.header.stamp = self.get_clock().now().to_msg()
         drive_msg.header.frame_id = "laser"
-        drive_msg.drive.steering_angle = action[0] * STEER_SCALE
-        drive_msg.drive.speed = action[1] * SPEED_SCALE
+        drive_msg.drive.steering_angle = steer
+        drive_msg.drive.speed = speed
         self.drive_pub.publish(drive_msg)
 
 def main(args=None):