def main():
parser = OptionParser()
parser.add_option('-a', '--action_var', dest = 'action_var', default = 0.0,
action = 'store', help = "describes the movement relative to the start pose \
(e.g. opening angle in rad for a rotational articulation or distance in m \
for a prismatic one)")
parser.add_option('-i', '--model_id', dest = 'model_id', default = -1,
action = 'store', help = "ID of model according to which movement is executed")
parser.add_option('-d', '--database', dest = 'database', default = "",
action = 'store', help = "file name of database to load prior models from")
parser.add_option('-t', '--target_duration', dest = 'duration', default = 20.0,
action = 'store', help = "duration in seconds until movement should be finished")
(options, args) = parser.parse_args()
rospy.init_node('moveModelPrior_client')
client = actionlib.SimpleActionClient('move_model_prior', MoveModelPriorAction)
client.wait_for_server()
print "Server OK"
# set up goal
goal = MoveModelPriorGoal()
if options.database == "":
rospy.errlog("No database is given to load prior models from!")
rospy.signal_shutdown("Database is missing!")
goal.database = options.database
if options.model_id < 0:
rospy.errlog("No model ID is given according to which a movement could be executed!")
rospy.signal_shutdown("Model ID is missing!")
goal.model_id = int(options.model_id)
goal.action_variable = float(options.action_var)
goal.duration.secs = float(options.duration)
client.send_goal(goal, feedback_cb=print_feedback)
print client.get_state()
while client.get_state() == 0 or client.get_state() == 1:
client.wait_for_result(rospy.Duration.from_sec(1.0))
print "RESULT:"
print client.get_result()
def moveModelPriorActionCB(self, goal):
# set up and initialize action feedback and result
result_ = MoveModelPriorResult()
feedback_ = MoveModelPriorFeedback()
result_.success = False
feedback_.message = "Move model prior action started"
self.moveModelPrior_as.publish_feedback(feedback_)
# load prior models from database and set up model_learner_prior
self.models_prior_object.load_prior_from_database(goal.database)
print self.models_prior_object.print_prior_models()
feedback_.message = "Loaded prior models from database %s and set up model_learner_prior" % str(goal.database)
self.moveModelPrior_as.publish_feedback(feedback_)
# get model according to model_id
execute_model = ArticulationModelGoal()
execute_model.model = self.models_prior_object.get_prior_model_by_id(goal.model_id)
if execute_model.model == None:
err_msg = "No model found with ID %d" % goal.model_id
feedback_.message = err_msg
self.moveModelPrior_as.publish_feedback(feedback_)
rospy.errlog(err_msg)
rospy.signal_shutdown(err_msg)
print "Model, to be executed:"
self.models_prior_object.print_models_verbose([execute_model.model])
# add parameters to model
execute_model.model.params.append(ParamMsg("action", float(goal.action_variable), 1))
execute_model.target_duration = goal.duration
execute_model.model.id = int(goal.model_id)
execute_model.model_id = int(goal.model_id)
# start cartcollector
self.models_prior_object.cartcollector_start()
feedback_.message = "Started to record trajectory and calculating model for model update"
self.moveModelPrior_as.publish_feedback(feedback_)
# execute movement
print "Recording of the cartesain gripper coordinates for model update is now running"
print "Please wait until the trajectory execution has finished, watch out and stay tuned!"
feedback_.message = "Model movement has started"
self.moveModelPrior_as.publish_feedback(feedback_)
# start mm controller
mm_request = TriggerRequest()
mm_response = self.models_prior_object.start_mm(mm_request)
# send model to cob_cartesian_trajectories_PID's moveModel action
self.models_prior_object.moveModel_ac.send_goal(execute_model)
self.models_prior_object.moveModel_ac.wait_for_result(rospy.Duration.from_sec(goal.duration.secs + 0.5))
# stop cartcollector
learned_model = self.models_prior_object.cartcollector_stop()
"""# evaluate moveModel result
traj_gen_result = self.models_prior_object.moveModel_ac.get_result()
print "Traj_gen_result: "
print traj_gen_result
if traj_gen_result['exit_code'] == 0:
feedback_.message = "Succeesful trajectory generation"
elif traj_gen_result == 2:
feedback_.message = "Succeesful trajectory generation but stopped because a joint limit was almost reached"
else:
result_.error_message = "Trajectory generation didn't succeed"
result_.success = False
self.moveModelPrior_as.set_aborted(result_)
self.moveModelPrior_as.publish_feedback(feedback_)"""
# TODO evaluation
# check model id of collected cartesian model
if learned_model.model.id == -1:
print "Collected model id differs from executed model and doesn't fit any other prior model"
self.models_prior_object.print_models_verbose([learned_model.model])
if (
self.models_prior_object.query("Do you want to save the new prior model in a database", ["y", "n"])
== "y"
):
self.models_prior_object.store_model_to_prior(learned_model.model)
feedback_.message = "New model was stored with ID %d" % learned_model.model.id
else:
if learned_model.model.id != execute_model.model.id:
print "Collected model id differs from executed model"
self.models_prior_object.print_models_verbose([execute_model.model])
self.models_prior_object.print_models_verbose(
[self.models_prior_object.get_prior_model_by_id(learned_model.model.id), learned_model.model]
)
else:
self.models_prior_object.print_models_verbose([execute_model.model, learned_model.model])
if (
self.models_prior_object.query(
"Do you want to update the prior model %d" % learned_model.model.id, ["y", "n"]
)
== "y"
):
self.models_prior_object.store_model_to_prior(learned_model.model)
feedback_.message = "Model %d was updated" % execute_model.model.id
else:
# self.models_prior_object.store_model_to_prior(stored_model.model)
feedback_.message = (
"Model %d was not updated, because new model was not better" % execute_model.model.id
)
self.moveModelPrior_as.publish_feedback(feedback_)
# save prior to database
self.models_prior_object.save_prior_to_database(goal.database)
result_.error_message = "Model execution finished successfully"
result_.success = True
self.moveModelPrior_as.set_succeeded(result_)
