#!/usr/bin/python
from run_trial import *
# Note that this is 0 to 16 as range does [start, stop), thus we get 0:1:15 in Matlab speak
adaptive_range = range(0, 16, 1)
# Run the single model baseline
for adaptive_exponent in adaptive_range:
adaptive_model_learning_rate = 10.0**(-adaptive_exponent)
run_trial(experiment="cloth_table",
logging_enabled="true",
test_id="550_paper_trials/"
+ "single_model_baseline/"
+ "adaptive_1e-" + str(adaptive_exponent),
planning_horizon=1,
multi_model="false",
use_adaptive_model="true",
adaptive_model_learning_rate=adaptive_model_learning_rate)
# Note that this is 0 to 25 as range does [start, stop), thus we get 0:2:24 in Matlab speak
deform_range = range(0, 25, 2)
# Run the single model baseline
for translational_deform in deform_range:
# for rotational_deform in deform_range:
rotational_deform=translational_deform
run_trial(experiment="cloth_table",
logging_enabled="true",
test_id="550_paper_trials/"
#!/usr/bin/python
from run_trial import *
# Note that this is 10 to 19 as range does [start, stop)
deform_range = range(10, 19, 4)
planning_horizion = 1
for translational_deform in deform_range:
for rotational_deform in deform_range:
run_trial(experiment="cloth_table",
logging_enabled="true",
test_id="presentation_trials_baseline_rigidity" + "trans_" +
str(translational_deform) + "_rot_" + str(rotational_deform),
planning_horizon=planning_horizion,
multi_model="false",
deformability_override="true",
translational_deformability=translational_deform,
rotational_deformability=rotational_deform)
# deformability_override="true",
# translational_deformability=translational_deform,
# rotational_deformability=rotational_deform)
# Run the multi model trials
for process_noise_factor in process_noise_factor_range:
if process_noise_factor == process_noise_factor_range[0]:
observation_noise_factor_range = \
[process_noise_factor, process_noise_factor * 10.0, process_noise_factor_range[-1]]
elif process_noise_factor == process_noise_factor_range[-1]:
observation_noise_factor_range = \
[process_noise_factor_range[0], process_noise_factor / 10.0, process_noise_factor]
else:
observation_noise_factor_range = \
[process_noise_factor / 10.0, process_noise_factor, process_noise_factor * 10.0]
for observation_noise_factor in observation_noise_factor_range:
run_trial(experiment="cloth_cylinder",
logging_enabled="true",
test_id=str(planning_horizion) +
"_step_simulator_noise_vs_kalman_parameters/" +
"feedback_covariance_" + str(feedback_covariance) + "/" +
"process_" + str(process_noise_factor) +
"_observation_" + str(observation_noise_factor),
planning_horizon=planning_horizion,
multi_model="true",
kalman_parameters_override="true",
process_noise_factor=process_noise_factor,
observation_noise_factor=observation_noise_factor)
#!/usr/bin/python
from run_trial import *
for correlation_strength_factor in [0.01, 0.1, 0.5, 0.9, 0.99]:
run_trial(
experiment="cloth_table",
start_bullet_viewer='true',
screenshots_enabled='true',
logging_enabled='true',
test_id='correlation_strength_factor_trials/KFMANDB_factor_' + str(correlation_strength_factor),
optimization_enabled='true',
bandit_algorithm='KFMANDB',
multi_model='true',
calculate_regret='true',
use_random_seed='false',
correlation_strength_factor=correlation_strength_factor)
for correlation_strength_factor in [0.01, 0.1, 0.5, 0.9, 0.99]:
run_trial(
experiment="rope_cylinder",
start_bullet_viewer='true',
screenshots_enabled='true',
logging_enabled='true',
test_id='correlation_strength_factor_trials/KFMANDB_factor_' + str(correlation_strength_factor),
optimization_enabled='true',
bandit_algorithm='KFMANDB',
multi_model='true',
calculate_regret='true',
use_random_seed='false',
correlation_strength_factor=correlation_strength_factor)
]
planning_horizion = 1
for feedback_covariance in feedback_covariance_range:
# Run the single model baseline
for translational_deform in deform_range:
for rotational_deform in deform_range:
run_trial(experiment="rope_cylinder",
logging_enabled="true",
test_id=str(planning_horizion) +
"_step_simulator_noise_vs_kalman_parameters/" +
"feedback_covariance_" + str(feedback_covariance) + "/" +
"single_model_baseline/" + "trans_" +
str(translational_deform) + "_rot_" +
str(rotational_deform),
planning_horizon=planning_horizion,
multi_model="false",
deformability_override="true",
translational_deformability=translational_deform,
rotational_deformability=rotational_deform)
# Run the multi model trials
for process_noise_factor in process_noise_factor_range:
if process_noise_factor == process_noise_factor_range[0]:
observation_noise_factor_range = \
[process_noise_factor, process_noise_factor * 10.0, process_noise_factor_range[-1]]
elif process_noise_factor == process_noise_factor_range[-1]:
observation_noise_factor_range = \