def main():
arg_fmt = argparse.RawDescriptionHelpFormatter
parser = argparse.ArgumentParser(formatter_class=arg_fmt,
description=main.__doc__)
required = parser.add_argument_group('required arguments')
required.add_argument('-c',
'--config',
dest='config',
required=True,
help='the file path of the demonstration ')
required.add_argument(
'-i',
'--input_directory',
dest='input_directory',
required=False,
help='the directory from which to input prior demonstration .json files'
)
required.add_argument(
'-o',
'--output_directory',
dest='output_directory',
required=False,
help='the directory to save the given subjects .json files data')
required.add_argument('-t',
'--task',
dest='task',
required=False,
help='the name of the task being demonstrated')
required.add_argument('-s',
'--subject',
dest='subject',
required=False,
help='the ID of the subject')
args = parser.parse_args(rospy.myargv()[1:])
############################
# ROS Node Initialization #
############################
print("Initializing node... ")
rospy.init_node("ar4lfd")
print("Getting robot state... ")
robot_state = intera_interface.RobotEnable(CHECK_VERSION)
print("Enabling robot... ")
robot_state.enable()
########################
# Import Configuration #
########################
config_filepath = args.config
configs = load_lfd_configuration(config_filepath)
#################################
# Configure the LFD class model #
#################################
model_settings = configs["settings"]["modeling_settings"]
moveit_interface = SawyerMoveitInterface()
moveit_interface.set_velocity_scaling(.35)
moveit_interface.set_acceleration_scaling(.25)
moveit_interface.set_planner(str(model_settings["planner"]))
acclfd = ACC_LFD(configs, model_settings, moveit_interface)
acclfd.build_environment()
#####################################
# Raw Demonstration Data Processors #
#####################################
# Build processors and process demonstrations to generate derivative data e.g. relative position.
rk_processor = RelativeKinematicsProcessor(
acclfd.environment.get_item_ids(), acclfd.environment.get_robot_id())
ic_processor = InContactProcessor(acclfd.environment.get_item_ids(),
acclfd.environment.get_robot_id(), .06,
.5)
soi_processor = SphereOfInfluenceProcessor(
acclfd.environment.get_item_ids(), acclfd.environment.get_robot_id())
rp_processor = RelativePositionProcessor(acclfd.environment.get_item_ids(),
acclfd.environment.get_robot_id())
wp_processor = WithinPerimeterProcessor(acclfd.environment.get_item_ids(),
acclfd.environment.get_robot_id())
processing_pipeline = DataProcessingPipeline([
rk_processor, ic_processor, soi_processor, rp_processor, wp_processor
])
###############################################
# Configure the Sawyer Demonstration Recorder #
###############################################
rec_settings = configs["settings"]["recording_settings"]
recorder = SawyerDemonstrationRecorder(rec_settings,
acclfd.environment,
processing_pipeline,
publish_constraint_validity=True)
rospy.on_shutdown(recorder.stop)
##########################################################
# Configure the Sawyer Demonstration Aligner and Labeler #
##########################################################
label_settings = configs["settings"]["labeling_settings"]
# Demonstration vectorizor that converts observations into state vector in desired space for DTW alignment.
demo_vectorizor = partial(vectorize_demonstration,
vectorizors=[get_observation_joint_vector])
alignment = DemonstrationAlignment(demo_vectorizor)
demo_labeler = SawyerDemonstrationLabeler(label_settings, alignment)
#########################
# Import Initial Demos #
#########################
if args.input_directory is not None:
prior_poor_demonstrations = load_json_files(args.input_directory +
"/*.json")
# Convert imported data into Demonstrations and Observations
demonstrations = []
for datum in prior_poor_demonstrations["data"]:
observations = []
for entry in datum:
observations.append(Observation(entry))
demonstrations.append(Demonstration(observations))
if len(demonstrations) == 0:
rospy.logwarn(
"No prior demonstration data to model!! You sure you're using the right experiment script?"
)
return 0
labeled_initial_demos = demo_labeler.label(demonstrations)
acclfd.build_keyframe_graph(labeled_initial_demos,
model_settings.get("bandwidth", .025))
acclfd.generate_autoconstraints(labeled_initial_demos)
acclfd.sample_keyframes(model_settings.get("number_of_samples", 50),
automate_threshold=True)
else:
labeled_initial_demos = []
acclfd.build_keyframe_graph(labeled_initial_demos,
model_settings.get("bandwidth", .025))
#######################################
# Set defaults for command line args #
#######################################
if args.task is None:
output_directory = ""
else:
output_directory = args.output_directory
if args.task is None:
task_name = "****"
else:
task_name = args.task
if args.subject is None:
subject = "####"
else:
subject = args.subject
#########################
# Run Study Controller #
#########################
study = ACCLfDController(acclfd, recorder, demo_labeler,
labeled_initial_demos, output_directory,
task_name, subject)
study.run()
def main():
arg_fmt = argparse.RawDescriptionHelpFormatter
parser = argparse.ArgumentParser(formatter_class=arg_fmt,
description=main.__doc__)
required = parser.add_argument_group('required arguments')
# required.add_argument(
# '-c', '--config', dest='config', required=True,
# help='the file path of the demonstration '
# )
required.add_argument(
'-i',
'--input',
dest='input_directory',
required=True,
help='the input directory to pull in raw demonstration .json files')
# required.add_argument(
# '-o', '--output', dest='output_directory', required=True,
# help='the output directory for saving relative distance labeled demonstration .json files'
# )
args = parser.parse_args(rospy.myargv()[1:])
print("Initializing node... ")
# rospy.init_node("intermediate_trajectories")
# print("Getting robot state... ")
# rs = intera_interface.RobotEnable(CHECK_VERSION)
# print("Enabling robot... ")
# rs.enable()
# config_filepath = args.config
# configs = load_lfd_configuration(config_filepath)
# items = ItemFactory(configs).generate_items()
# constraints = ConstraintFactory(configs["constraints"]).generate_constraints()
# # We only have just the one robot...for now.......
# environment = Environment(items=items['items'], robot=items['robots'][0], constraints=constraints)
# Import the data
rospy.loginfo("Importing demonstration .json files...")
raw_demonstrations = load_json_files(args.input_directory + "/*.json")
# Convert imported data into Demonstrations and Observations
demonstrations = []
for datum in raw_demonstrations["data"]:
observations = []
for entry in datum:
observations.append(Observation(entry))
demonstrations.append(
Demonstration(None, labeled_observations=observations))
args = parser.parse_args(rospy.myargv()[1:])
inter_trajectories = IntermediateTrajectories().get_trajectories(
demonstrations)
it_data = {
key: [[o.data for o in segment] for segment in group]
for key, group in inter_trajectories.iteritems()
}
with file('./intermediate_trajectories.json', "w") as f:
json.dump(it_data, f)