def test_arm_carry_command():
command = RobotCommandBuilder.arm_ready_command()
_test_has_synchronized(command)
_test_has_arm(command.synchronized_command)
assert (command.synchronized_command.arm_command.WhichOneof("command") ==
'named_arm_position_command')
# with a build_on_command
mobility_command = RobotCommandBuilder.synchro_sit_command()
command = RobotCommandBuilder.arm_carry_command(build_on_command=mobility_command)
_test_has_synchronized(command)
_test_has_mobility(command.synchronized_command)
_test_has_arm(command.synchronized_command)
def main(argv):
parser = argparse.ArgumentParser()
bosdyn.client.util.add_common_arguments(parser)
parser.add_argument(
'-s',
'--ml-service',
help='Service name of external machine learning server.',
required=True)
parser.add_argument('-m',
'--model',
help='Model name running on the external server.',
required=True)
parser.add_argument(
'-p',
'--person-model',
help='Person detection model name running on the external server.')
parser.add_argument(
'-c',
'--confidence-dogtoy',
help=
'Minimum confidence to return an object for the dogoy (0.0 to 1.0)',
default=0.5,
type=float)
parser.add_argument(
'-e',
'--confidence-person',
help='Minimum confidence for person detection (0.0 to 1.0)',
default=0.6,
type=float)
options = parser.parse_args(argv)
cv2.namedWindow("Fetch")
cv2.waitKey(500)
sdk = bosdyn.client.create_standard_sdk('SpotFetchClient')
sdk.register_service_client(NetworkComputeBridgeClient)
robot = sdk.create_robot(options.hostname)
robot.authenticate(options.username, options.password)
# Time sync is necessary so that time-based filter requests can be converted
robot.time_sync.wait_for_sync()
network_compute_client = robot.ensure_client(
NetworkComputeBridgeClient.default_service_name)
robot_state_client = robot.ensure_client(
RobotStateClient.default_service_name)
command_client = robot.ensure_client(
RobotCommandClient.default_service_name)
lease_client = robot.ensure_client(LeaseClient.default_service_name)
manipulation_api_client = robot.ensure_client(
ManipulationApiClient.default_service_name)
# This script assumes the robot is already standing via the tablet. We'll take over from the
# tablet.
lease = lease_client.take()
lk = bosdyn.client.lease.LeaseKeepAlive(lease_client)
# Store the position of the hand at the last toy drop point.
vision_tform_hand_at_drop = None
while True:
holding_toy = False
while not holding_toy:
# Capture an image and run ML on it.
dogtoy, image, vision_tform_dogtoy = get_obj_and_img(
network_compute_client, options.ml_service, options.model,
options.confidence_dogtoy, kImageSources, 'dogtoy')
if dogtoy is None:
# Didn't find anything, keep searching.
continue
# If we have already dropped the toy off, make sure it has moved a sufficient amount before
# picking it up again
if vision_tform_hand_at_drop is not None and pose_dist(
vision_tform_hand_at_drop, vision_tform_dogtoy) < 0.5:
print('Found dogtoy, but it hasn\'t moved. Waiting...')
time.sleep(1)
continue
print('Found dogtoy...')
# Got a dogtoy. Request pick up.
# Stow the arm in case it is deployed
stow_cmd = RobotCommandBuilder.arm_stow_command()
command_client.robot_command(stow_cmd)
# Walk to the object.
walk_rt_vision, heading_rt_vision = compute_stand_location_and_yaw(
vision_tform_dogtoy, robot_state_client, distance_margin=1.0)
move_cmd = RobotCommandBuilder.trajectory_command(
goal_x=walk_rt_vision[0],
goal_y=walk_rt_vision[1],
goal_heading=heading_rt_vision,
frame_name=frame_helpers.VISION_FRAME_NAME,
params=get_walking_params(0.5, 0.5))
end_time = 5.0
cmd_id = command_client.robot_command(command=move_cmd,
end_time_secs=time.time() +
end_time)
# Wait until the robot reports that it is at the goal.
block_for_trajectory_cmd(command_client,
cmd_id,
timeout_sec=5,
verbose=True)
# The ML result is a bounding box. Find the center.
(center_px_x,
center_px_y) = find_center_px(dogtoy.image_properties.coordinates)
# Request Pick Up on that pixel.
pick_vec = geometry_pb2.Vec2(x=center_px_x, y=center_px_y)
grasp = manipulation_api_pb2.PickObjectInImage(
pixel_xy=pick_vec,
transforms_snapshot_for_camera=image.shot.transforms_snapshot,
frame_name_image_sensor=image.shot.frame_name_image_sensor,
camera_model=image.source.pinhole)
# We can specify where in the gripper we want to grasp. About halfway is generally good for
# small objects like this. For a bigger object like a shoe, 0 is better (use the entire
# gripper)
grasp.grasp_params.grasp_palm_to_fingertip = 0.6
# Tell the grasping system that we want a top-down grasp.
# Add a constraint that requests that the x-axis of the gripper is pointing in the
# negative-z direction in the vision frame.
# The axis on the gripper is the x-axis.
axis_on_gripper_ewrt_gripper = geometry_pb2.Vec3(x=1, y=0, z=0)
# The axis in the vision frame is the negative z-axis
axis_to_align_with_ewrt_vision = geometry_pb2.Vec3(x=0, y=0, z=-1)
# Add the vector constraint to our proto.
constraint = grasp.grasp_params.allowable_orientation.add()
constraint.vector_alignment_with_tolerance.axis_on_gripper_ewrt_gripper.CopyFrom(
axis_on_gripper_ewrt_gripper)
constraint.vector_alignment_with_tolerance.axis_to_align_with_ewrt_frame.CopyFrom(
axis_to_align_with_ewrt_vision)
# We'll take anything within about 15 degrees for top-down or horizontal grasps.
constraint.vector_alignment_with_tolerance.threshold_radians = 0.25
# Specify the frame we're using.
grasp.grasp_params.grasp_params_frame_name = frame_helpers.VISION_FRAME_NAME
# Build the proto
grasp_request = manipulation_api_pb2.ManipulationApiRequest(
pick_object_in_image=grasp)
# Send the request
print('Sending grasp request...')
cmd_response = manipulation_api_client.manipulation_api_command(
manipulation_api_request=grasp_request)
# Wait for the grasp to finish
grasp_done = False
failed = False
time_start = time.time()
while not grasp_done:
feedback_request = manipulation_api_pb2.ManipulationApiFeedbackRequest(
manipulation_cmd_id=cmd_response.manipulation_cmd_id)
# Send a request for feedback
response = manipulation_api_client.manipulation_api_feedback_command(
manipulation_api_feedback_request=feedback_request)
current_state = response.current_state
current_time = time.time() - time_start
print('Current state ({time:.1f} sec): {state}'.format(
time=current_time,
state=manipulation_api_pb2.ManipulationFeedbackState.Name(
current_state)),
end=' \r')
sys.stdout.flush()
failed_states = [
manipulation_api_pb2.MANIP_STATE_GRASP_FAILED,
manipulation_api_pb2.
MANIP_STATE_GRASP_PLANNING_NO_SOLUTION,
manipulation_api_pb2.
MANIP_STATE_GRASP_FAILED_TO_RAYCAST_INTO_MAP,
manipulation_api_pb2.
MANIP_STATE_GRASP_PLANNING_WAITING_DATA_AT_EDGE
]
failed = current_state in failed_states
grasp_done = current_state == manipulation_api_pb2.MANIP_STATE_GRASP_SUCCEEDED or failed
time.sleep(0.1)
holding_toy = not failed
# Move the arm to a carry position.
print('')
print('Grasp finished, search for a person...')
carry_cmd = RobotCommandBuilder.arm_carry_command()
command_client.robot_command(carry_cmd)
# Wait for the carry command to finish
time.sleep(0.75)
person = None
while person is None:
# Find a person to deliver the toy to
person, image, vision_tform_person = get_obj_and_img(
network_compute_client, options.ml_service,
options.person_model, options.confidence_person, kImageSources,
'person')
# We now have found a person to drop the toy off near.
drop_position_rt_vision, heading_rt_vision = compute_stand_location_and_yaw(
vision_tform_person, robot_state_client, distance_margin=2.0)
wait_position_rt_vision, wait_heading_rt_vision = compute_stand_location_and_yaw(
vision_tform_person, robot_state_client, distance_margin=3.0)
# Tell the robot to go there
# Limit the speed so we don't charge at the person.
move_cmd = RobotCommandBuilder.trajectory_command(
goal_x=drop_position_rt_vision[0],
goal_y=drop_position_rt_vision[1],
goal_heading=heading_rt_vision,
frame_name=frame_helpers.VISION_FRAME_NAME,
params=get_walking_params(0.5, 0.5))
end_time = 5.0
cmd_id = command_client.robot_command(command=move_cmd,
end_time_secs=time.time() +
end_time)
# Wait until the robot reports that it is at the goal.
block_for_trajectory_cmd(command_client,
cmd_id,
timeout_sec=5,
verbose=True)
print('Arrived at goal, dropping object...')
# Do an arm-move to gently put the object down.
# Build a position to move the arm to (in meters, relative to and expressed in the gravity aligned body frame).
x = 0.75
y = 0
z = -0.25
hand_ewrt_flat_body = geometry_pb2.Vec3(x=x, y=y, z=z)
# Point the hand straight down with a quaternion.
qw = 0.707
qx = 0
qy = 0.707
qz = 0
flat_body_Q_hand = geometry_pb2.Quaternion(w=qw, x=qx, y=qy, z=qz)
flat_body_tform_hand = geometry_pb2.SE3Pose(
position=hand_ewrt_flat_body, rotation=flat_body_Q_hand)
robot_state = robot_state_client.get_robot_state()
vision_tform_flat_body = frame_helpers.get_a_tform_b(
robot_state.kinematic_state.transforms_snapshot,
frame_helpers.VISION_FRAME_NAME,
frame_helpers.GRAV_ALIGNED_BODY_FRAME_NAME)
vision_tform_hand_at_drop = vision_tform_flat_body * math_helpers.SE3Pose.from_obj(
flat_body_tform_hand)
# duration in seconds
seconds = 1
arm_command = RobotCommandBuilder.arm_pose_command(
vision_tform_hand_at_drop.x, vision_tform_hand_at_drop.y,
vision_tform_hand_at_drop.z, vision_tform_hand_at_drop.rot.w,
vision_tform_hand_at_drop.rot.x, vision_tform_hand_at_drop.rot.y,
vision_tform_hand_at_drop.rot.z, frame_helpers.VISION_FRAME_NAME,
seconds)
# Keep the gripper closed.
gripper_command = RobotCommandBuilder.claw_gripper_open_fraction_command(
0.0)
# Combine the arm and gripper commands into one RobotCommand
command = RobotCommandBuilder.build_synchro_command(
gripper_command, arm_command)
# Send the request
cmd_id = command_client.robot_command(command)
# Wait until the arm arrives at the goal.
block_until_arm_arrives(command_client, cmd_id)
# Open the gripper
gripper_command = RobotCommandBuilder.claw_gripper_open_fraction_command(
1.0)
command = RobotCommandBuilder.build_synchro_command(gripper_command)
cmd_id = command_client.robot_command(command)
# Wait for the dogtoy to fall out
time.sleep(1.5)
# Stow the arm.
stow_cmd = RobotCommandBuilder.arm_stow_command()
command_client.robot_command(stow_cmd)
time.sleep(1)
print('Backing up and waiting...')
# Back up one meter and wait for the person to throw the object again.
move_cmd = RobotCommandBuilder.trajectory_command(
goal_x=wait_position_rt_vision[0],
goal_y=wait_position_rt_vision[1],
goal_heading=wait_heading_rt_vision,
frame_name=frame_helpers.VISION_FRAME_NAME,
params=get_walking_params(0.5, 0.5))
end_time = 5.0
cmd_id = command_client.robot_command(command=move_cmd,
end_time_secs=time.time() +
end_time)
# Wait until the robot reports that it is at the goal.
block_for_trajectory_cmd(command_client,
cmd_id,
timeout_sec=5,
verbose=True)
lease_client.return_lease(lease)
