Made quadrotor gymnasium env compatible with Gymnasium 1.0.0 (Issue #11)

examples/gymnasium_basic_usage.py

@@ -48,7 +48,7 @@ env = gym.make("Quadrotor-v0",
 # Now reset the quadrotor.
 # Setting initial_state to 'random' will randomly place the vehicle in the map near the origin.
 # But you can also set the environment resetting to be deterministic. 
-observation, info = env.reset(initial_state='random')
+observation, info = env.reset(options={'initial_state': 'random'})
 
 # Number of timesteps
 T = 300

examples/ppo_hover_train.py

@@ -59,7 +59,7 @@ env = gym.make("Quadrotor-v0",
 # check_env(env, warn=True)  # you can check the environment using built-in tools
 
 # Reset the environment
-observation, info = env.reset(initial_state='random', options={'pos_bound': 2, 'vel_bound': 0})
+observation, info = env.reset(options={'initial_state': 'random', 'pos_bound': 2, 'vel_bound': 0})
 
 # Create a new model
 model = PPO(MlpPolicy, env, verbose=1, ent_coef=0.01, tensorboard_log=log_dir)