num_drones=ARGS.num_drones,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=ARGS.obs,
act=ARGS.act))
elif ARGS.env == 'meetup':
register_env(
temp_env_name, lambda _: MeetupAviary(
num_drones=ARGS.num_drones,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=ARGS.obs,
act=ARGS.act))
elif ARGS.env == 'payloadcoop':
register_env(
temp_env_name, lambda _: PayloadCoop(
num_drones=ARGS.num_drones,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=ARGS.obs,
act=ARGS.act))
else:
print("[ERROR] environment not yet implemented")
exit()
#### Unused env to extract the act and obs spaces ##########
if ARGS.env == 'flock':
temp_env = FlockAviary(
num_drones=ARGS.num_drones,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=ARGS.obs,
act=ARGS.act)
elif ARGS.env == 'leaderfollower':
#### Parameters to recreate the environment ################
NUM_DRONES =shared_constants.NUM_DRONES
ACT = ActionType(shared_constants.ACT)
OBS = ObservationType(shared_constants.OBS)
#### Initialize Ray Tune ###################################
ray.shutdown()
ray.init(ignore_reinit_error=True, include_dashboard=True)
#### Register the environment ##############################
temp_env_name = "this-aviary-v0"
register_env(temp_env_name, lambda _: PayloadCoop(num_drones=NUM_DRONES,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=OBS,
act=ACT
))
temp_env = PayloadCoop(num_drones=NUM_DRONES,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=OBS,
act=ACT,
)
action_space = temp_env.action_space[0]
observation_space = temp_env.observation_space[0]
obs_space_dict = {
"agent_1": observation_space,
"agent_2": observation_space,
}
act_space_dict = {
num_drones=NUM_DRONES,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=OBS,
act=ACT))
elif ARGS.exp.split("-")[1] == 'meetup':
register_env(
temp_env_name, lambda _: MeetupAviary(
num_drones=NUM_DRONES,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=OBS,
act=ACT))
elif ARGS.exp.split("-")[1] == 'payloadcoop':
register_env(
temp_env_name, lambda _: PayloadCoop(
num_drones=NUM_DRONES,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=OBS,
act=ACT))
else:
print("[ERROR] environment not yet implemented")
exit()
#### Unused env to extract the act and obs spaces ##########
if ARGS.exp.split("-")[1] == 'flock':
temp_env = FlockAviary(
num_drones=NUM_DRONES,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=OBS,
act=ACT)
elif ARGS.exp.split("-")[1] == 'leaderfollower':
temp_env = LeaderFollowerAviary(
#### Parameters to recreate the environment ################
NUM_DRONES = shared_constants.NUM_DRONES
ACT = ActionType(shared_constants.ACT)
OBS = ObservationType(shared_constants.OBS)
#### Initialize Ray Tune ###################################
ray.shutdown()
ray.init(ignore_reinit_error=True, include_dashboard=True)
#### Register the environment ##############################
temp_env_name = "this-aviary-v0"
register_env(
temp_env_name, lambda _: PayloadCoop(num_drones=ARGS.num_drones,
aggregate_phy_steps=
shared_constants.AGGR_PHY_STEPS,
obs=ARGS.obs,
act=ARGS.act))
temp_env = PayloadCoop(
num_drones=ARGS.num_drones,
aggregate_phy_steps=shared_constants.AGGR_PHY_STEPS,
obs=ARGS.obs,
act=ARGS.act,
)
observer_space = Dict({
"own_obs": temp_env.observation_space[0],
"opponent_obs": temp_env.observation_space[0],
"opponent_action": temp_env.action_space[0],
})
action_space = temp_env.action_space[0]
OWN_OBS_VEC_SIZE = observer_space["own_obs"].shape[0]
#### Initialize the simulation #############################
# R = 0.3
# INIT_XYZS = np.array([[-0.2, 0, 0.5], [0.2, 0, 0.5]])
# INIT_XYZS = np.array([[R*np.cos((i/6)*2*np.pi+np.pi/2), R*np.sin((i/6)*2*np.pi+np.pi/2)-R, 0.5] for i in range(ARGS.num_drones)])
INIT_XYZS = None
INIT_RPYS = np.array([[0, 0, i * (np.pi / 2) / ARGS.num_drones]
for i in range(ARGS.num_drones)])
AGGR_PHY_STEPS = int(ARGS.simulation_freq_hz /
ARGS.control_freq_hz) if ARGS.aggregate else 1
env = PayloadCoop(dest_point=shared_constants.DEST_POINT,
drone_model=ARGS.drone,
num_drones=ARGS.num_drones,
initial_xyzs=INIT_XYZS,
initial_rpys=INIT_RPYS,
physics=ARGS.physics,
neighbourhood_radius=10,
freq=ARGS.simulation_freq_hz,
aggregate_phy_steps=AGGR_PHY_STEPS,
gui=ARGS.gui,
episode_len_sec=ARGS.duration_sec)
#### Obtain the PyBullet Client ID from the environment ####
PYB_CLIENT = env.getPyBulletClient()
#### Initialize the logger #################################
logger = Logger(logging_freq_hz=int(ARGS.simulation_freq_hz /
AGGR_PHY_STEPS),
num_drones=ARGS.num_drones)
#### Run the simulation ####################################