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updated data provider to use all collected data, changed sim ranges a…
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…nd updated hyperparams for model learning
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@sukhijab
sukhijab committed Dec 4, 2023
1 parent eecddcd commit 68e105c
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Showing 5 changed files with 67 additions and 47 deletions.
4 changes: 3 additions & 1 deletion experiments/data_provider.py
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Original file line number Diff line number Diff line change
Expand Up @@ -199,7 +199,9 @@ def get_rccar_recorded_data_new(encode_angle: bool = True, skip_first_n_points:
recordings_dir = [os.path.join(DATA_DIR, 'recordings_rc_car_v1')]
elif car_id == 2:
num_train_traj = 12
recordings_dir = [os.path.join(DATA_DIR, 'recordings_rc_car_v4')]
recordings_dir = [os.path.join(DATA_DIR, 'recordings_rc_car_v2'),
os.path.join(DATA_DIR, 'recordings_rc_car_v3'),
os.path.join(DATA_DIR, 'recordings_rc_car_v4')]
else:
raise ValueError(f"Unknown car id {car_id}")
files = [sorted(glob.glob(rd + '/*.pickle')) for rd in recordings_dir]
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2 changes: 1 addition & 1 deletion experiments/offline_rl_from_recorded_data/exp.py
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Expand Up @@ -217,7 +217,7 @@ def experiment(horizon_len: int,
if high_fidelity:
outputscales_racecar = [0.008, 0.008, 0.009, 0.009, 0.05, 0.05, 0.20]
else:
outputscales_racecar = [0.008, 0.008, 0.01, 0.01, 0.08, 0.08, 0.5]
outputscales_racecar = [0.008, 0.008, 0.01, 0.01, 0.1, 0.1, 0.5]
sim = AdditiveSim(base_sims=[sim,
GaussianProcessSim(sim.input_size, sim.output_size,
output_scale=outputscales_racecar,
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46 changes: 32 additions & 14 deletions experiments/offline_rl_from_recorded_data/launcher.py
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@@ -1,79 +1,97 @@
import exp
from experiments.util import generate_run_commands, generate_base_command, dict_permutations

PROJECT_NAME = 'OfflineRLRunsSimConsecutive'
PROJECT_NAME = 'OfflineRLRunsGreyBoxHWFinal'

_applicable_configs = {
'horizon_len': [200],
'seed': list(range(5)),
'project_name': [PROJECT_NAME],
'sac_num_env_steps': [2_000_000],
'sac_num_env_steps': [1_000_000],
'num_epochs': [50],
'max_train_steps': [100_000],
'min_train_steps': [40_000], # for HW 30_000 worked the best.
'min_train_steps': [40_000],
'learnable_likelihood_std': ['yes'],
'include_aleatoric_noise': [1],
'best_bnn_model': [1],
'best_policy': [1],
'margin_factor': [20.0],
'ctrl_cost_weight': [0.005],
'ctrl_diff_weight': [0.0],
'num_offline_collected_transitions': [20, 50, 100, 200, 400, 800, 1600, 2000, 2500, 10_000, 20_000],
'num_offline_collected_transitions': [20, 50, 100, 200, 400, 800, 1600, 2000, 2500, 5_000, 10_000, 20_000],
'test_data_ratio': [0.0],
'eval_on_all_offline_data': [1],
'eval_only_on_init_states': [1],
'share_of_x0s_in_sac_buffer': [0.5],
'bnn_batch_size': [32], # for HW 8 worked the best
'likelihood_exponent': [0.5],
'train_sac_only_from_init_states': [0],
'data_from_simulation': [1],
'data_from_simulation': [0],
'num_frame_stack': [3],
'bandwidth_svgd': [0.2],
'length_scale_aditive_sim_gp': [10.0],
'length_scale_aditive_sim_gp': [5.0],
'input_from_recorded_data': [1],
'obtain_consecutive_data': [0, 1],
'obtain_consecutive_data': [1],
'lr': [3e-4],
}

_applicable_configs_no_sim_prior = {'use_sim_prior': [0],
'use_grey_box': [0],
'use_sim_model': [0],
'high_fidelity': [0],
'predict_difference': [1],
'num_measurement_points': [8]
} | _applicable_configs
_applicable_configs_high_fidelity = {'use_sim_prior': [1],
'use_grey_box': [0],
'use_sim_model': [0],
'high_fidelity': [1],
'predict_difference': [1],
'num_measurement_points': [8]} | _applicable_configs
_applicable_configs_low_fidelity = {'use_sim_prior': [1],
'use_grey_box': [0],
'use_sim_model': [0],
'high_fidelity': [0],
'predict_difference': [1],
'num_measurement_points': [8]} | _applicable_configs

_applicable_configs_grey_box_low_fidelity = {'use_sim_prior': [0],
'high_fidelity': [0],
'use_grey_box': [1],
'predict_difference': [0],
'use_sim_model': [0],
'predict_difference': [1],
'num_measurement_points': [8]} | _applicable_configs

_applicable_configs_grey_box_high_fidelity = {'use_sim_prior': [0],
'high_fidelity': [1],
'use_grey_box': [1],
'predict_difference': [0],
'use_sim_model': [0],
'predict_difference': [1],
'num_measurement_points': [8]} | _applicable_configs

_applicable_configs_sim_model_high_fidelity = {'use_sim_prior': [0],
'high_fidelity': [1],
'use_grey_box': [0],
'use_sim_model': [1],
'predict_difference': [1],
'num_measurement_points': [8]} | _applicable_configs

_applicable_configs_sim_model_low_fidelity = {'use_sim_prior': [0],
'high_fidelity': [0],
'use_grey_box': [0],
'use_sim_model': [1],
'predict_difference': [1],
'num_measurement_points': [8]} | _applicable_configs

# all_flags_combinations = dict_permutations(_applicable_configs_no_sim_prior) + dict_permutations(
# _applicable_configs_high_fidelity) + dict_permutations(_applicable_configs_low_fidelity) + dict_permutations(
# _applicable_configs_grey_box)

all_flags_combinations = dict_permutations(_applicable_configs_no_sim_prior) + dict_permutations(
_applicable_configs_high_fidelity) + dict_permutations(_applicable_configs_low_fidelity) # + dict_permutations(

# _applicable_configs_grey_box)
_applicable_configs_high_fidelity) + dict_permutations(_applicable_configs_low_fidelity) + \
dict_permutations(_applicable_configs_grey_box_high_fidelity) + \
dict_permutations(_applicable_configs_sim_model_high_fidelity)

all_flags_combinations += dict_permutations(_applicable_configs_grey_box_low_fidelity) + dict_permutations(
_applicable_configs_grey_box_high_fidelity)


def main():
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2 changes: 1 addition & 1 deletion experiments/online_rl_hardware/online_rl_loop.py
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Original file line number Diff line number Diff line change
Expand Up @@ -150,7 +150,7 @@ class MainConfig(NamedTuple):
likelihood_exponent: float = 0.5
data_batch_size: int = 32
bandwidth_svgd: float = 0.2
length_scale_aditive_sim_gp: float = 10.0
length_scale_aditive_sim_gp: float = 5.0
num_f_samples: int = 512
num_measurement_points: int = 16
initial_state_fraction: float = 0.5
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60 changes: 30 additions & 30 deletions sim_transfer/sims/car_sim_config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -96,35 +96,35 @@
'm': 1.65,
'l_f': 0.13,
'l_r': 0.17,
'angle_offset': -0.05,
'angle_offset': 0.00,
'b_f': 2.58,
'b_r': 5.0,
'blend_ratio_lb': 0.01,
'blend_ratio_ub': 0.01,
'c_d': 0.0,
'c_f': 1.2,
'c_m_1': 7.0,
'c_m_2': 1.4,
'c_m_1': 8.0,
'c_m_2': 1.5,
'c_r': 1.27,
'd_f': 0.02,
'd_r': 0.017,
'i_com': 0.01,
'steering_limit': 0.25
'steering_limit': 0.3
}

BOUNDS_PARAMS_BICYCLE_CAR2: Dict = {
'use_blend': (0.0, 0.0),
'm': (1.6, 1.7),
'l_f': (0.11, 0.15),
'l_r': (0.15, 0.19),
'angle_offset': (-0.15, 0.0),
'b_f': (2.58, 2.58),
'angle_offset': (-0.15, 0.15),
'b_f': (2.4, 2.6),
'b_r': (2.0, 8.0),
'blend_ratio_lb': (0.4, 0.4),
'blend_ratio_ub': (0.5, 0.5),
'c_d': (0.01, 0.01),
'c_f': (1.2, 1.2),
'c_m_1': (6., 8.),
'c_m_1': (6., 10.),
'c_m_2': (1.0, 1.8),
'c_r': (1.27, 1.27),
'd_f': (0.02, 0.02),
Expand All @@ -138,39 +138,39 @@
'm': 1.65,
'l_f': 0.13,
'l_r': 0.17,
'angle_offset': -0.035,
'b_f': 3.0,
'b_r': 4.5,
'blend_ratio_lb': 0.01,
'blend_ratio_ub': 0.025,
'angle_offset': 0.0,
'b_f': 2.75,
'b_r': 5.0,
'blend_ratio_lb': 0.001,
'blend_ratio_ub': 0.017,
'c_d': 0.0,
'c_f': 1.68,
'c_m_1': 7.3,
'c_m_2': 1.11,
'c_r': 1.6,
'd_f': 0.36,
'd_r': 0.34,
'i_com': 0.08,
'steering_limit': 0.58,
'c_f': 1.45,
'c_m_1': 8.2,
'c_m_2': 1.25,
'c_r': 1.3,
'd_f': 0.4,
'd_r': 0.3,
'i_com': 0.06,
'steering_limit': 0.6,
}

BOUNDS_PARAMS_BLEND_CAR2 = {
'use_blend': (1.0, 1.0),
'm': (1.6, 1.7),
'l_f': (0.125, 0.135),
'l_r': (0.165, 0.175),
'angle_offset': (-0.05, 0.05),
'angle_offset': (-0.15, 0.15),
'b_f': (2.0, 4.0),
'b_r': (3.0, 8.0),
'blend_ratio_lb': (0.01, 0.1),
'blend_ratio_ub': (0.001, 0.2),
'b_r': (3.0, 10.0),
'blend_ratio_lb': (0.0001, 0.1),
'blend_ratio_ub': (0.0001, 0.2),
'c_d': (0.0, 0.0),
'c_f': (1.5, 2.0),
'c_m_1': (6.5, 9.0),
'c_m_2': (1.0, 1.4),
'c_r': (1.0, 2.0),
'c_f': (1.1, 2.0),
'c_m_1': (6.5, 10.0),
'c_m_2': (1.0, 1.5),
'c_r': (0.4, 2.0),
'd_f': (0.25, 0.6),
'd_r': (0.15, 0.45),
'i_com': (0.06, 0.18),
'steering_limit': (0.5, 0.65),
'i_com': (0.03, 0.18),
'steering_limit': (0.4, 0.75),
}

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