args = parser.parse_args()
gains = [2000, 2000, 2000, 1500, 1500, 1000, 1000] #joint impedances
# load the dmp weights
if not args.pose_dmp_weights_path:
args.pose_dmp_weights_path = './data/dmp/IROS2020_dmp_data_goal_position_weights.pkl'
pose_dmp_file = open(args.pose_dmp_weights_path, "rb")
pose_dmp_info = pickle.load(pose_dmp_file)
print('Starting robot')
fa = FrankaArm()
# Reset robot pose and joints
print('Opening Grippers')
fa.goto_gripper(0.08, grasp=False)
print('Reset with pose')
fa.reset_pose(duration=10)
print('Reset with joints')
fa.reset_joints()
# instantiate object for AR tag detection
frank = realpeginsert.Robot()
# get transforms
tag2worldTF = frank.detect_ar_world_pos(straighten=True,
shape_class=shapes.Circle,
goal=False)
print('Object Transform: (x,y) = {}'.format(tag2worldTF))
goal2worldTF = frank.detect_ar_world_pos(straighten=True,
shape_class=shapes.Circle,
current_position = fa.get_pose().position
current_data = magnetic_calibration.get_processed_data()
# print("My current data is: " + str(current_data[0]) + ", " + str(current_data[1]) + ", " + str(current_data[2]))
# print("My current position is: " + str(current_position[0]) + ", " + str(current_position[1]) + ", " + str(current_position[2]))
# print("My next position is: " + str(max_location[0]) + ", " + str(max_location[1]) + ", " + str(max_location[2]))
# input("Press enter to continue to command")
# franka_arm.move -relative dist m in x and y
next_position = RigidTransform(rotation=np.array([
[0, -1, 0],
[0, 0, 1],
[-1, 0, 0]
]), translation=np.array(max_location), # add x and z later
from_frame='franka_tool', to_frame='world')
fa.goto_pose_with_cartesian_control(next_position, 3)
#fa.close_gripper()
fa.goto_gripper(0.0, 0.04, 1)
relative_z_dist = RigidTransform(rotation=np.array([
[1, 0, 0],
[0, 1, 0],
[0, 0, 1]
]), translation=np.array([0, 0.0, 0.1]),
from_frame='franka_tool', to_frame='franka_tool')
fa.goto_pose_delta_with_cartesian_control(relative_z_dist, 5)
def run_main():
parser = argparse.ArgumentParser()
parser.add_argument('--filename', type=str, default=None)
args = parser.parse_args()
fa = FrankaArm()
fa.open_gripper()
# fa.reset_pose()
fa.reset_joints(10)
initial_magnet_position1 = RigidTransform(
rotation=np.array([[0, -1, 0], [0, 0, 1], [-1, 0, 0]]),
translation=np.array([0.38592997, 0.10820438, 0.08264024]),
from_frame='franka_tool',
to_frame='world')
initial_magnet_position2 = RigidTransform(
rotation=np.array([[0, -1, 0], [0, 0, 1], [-1, 0, 0]]),
translation=np.array([0.38592997, 0.20820438, 0.08264024]),
from_frame='franka_tool',
to_frame='world')
squeeze_position1 = RigidTransform(
rotation=np.array([[0, 1, 0], [0, 0, 1], [1, 0, 0]]),
translation=np.array([0.54900978, 0.20820438, 0.20654183]),
from_frame='franka_tool',
to_frame='world')
squeeze_position2 = RigidTransform(
rotation=np.array([[0, 1, 0], [0, 0, 1], [1, 0, 0]]),
translation=np.array([0.54900978, 0.20820438, 0.15654183]),
from_frame='franka_tool',
to_frame='world')
relative_pos_dist_z = RigidTransform(rotation=np.array([[1, 0,
0], [0, 1, 0],
[0, 0, 1]]),
translation=np.array([0.0, 0.0, 0.1]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_pos_dist_y = RigidTransform(rotation=np.array([[1, 0,
0], [0, 1, 0],
[0, 0, 1]]),
translation=np.array([0.0, 0.1, 0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_rotation_z = RigidTransform(rotation=np.array([[0, 1, 0],
[-1, 0, 0],
[0, 0, 1]]),
translation=np.array([0.0, 0.0, 0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_neg_rotation_z = RigidTransform(rotation=np.array([[0, -1, 0],
[1, 0, 0],
[0, 0, 1]]),
translation=np.array(
[0.0, 0.0, 0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_neg_dist_y = RigidTransform(rotation=np.array([[1, 0,
0], [0, 1, 0],
[0, 0, 1]]),
translation=np.array([0.0, -0.1,
0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_neg_dist_z = RigidTransform(rotation=np.array([[1, 0,
0], [0, 1, 0],
[0, 0, 1]]),
translation=np.array([0.0, 0.0,
-0.1]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_pos_dist_x = RigidTransform(
rotation=np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]),
translation=np.array([0.075, 0.0, 0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_neg_dist_x = RigidTransform(
rotation=np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]),
translation=np.array([-0.03, 0.0, 0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
fa.goto_pose_with_cartesian_control(initial_magnet_position1)
fa.goto_pose_with_cartesian_control(initial_magnet_position2)
magnetic_calibration = MagneticCalibration()
filename = '../calibration/2020-01-14 11-08 E1 2X Board Calibration.npz'
magnetic_calibration.load_calibration_file(filename)
# Close the gripper and save corresponding robot state, gripper state, and magnetic state data
magnetic_calibration.start_recording_data()
time.sleep(1)
# fa.goto_pose_delta_with_cartesian_control(relative_x_dist, 10)
# max width is about 0.080 m
gripper_step_size = 0.002 # in meters
num_samples = 30
noise_level = 13 # uT
force_threshold = 1.05
GRIPPER_CONTACT = False
min_contact = None
min_gripper_width = None
global_min = None
current_force_estimate = 1
while (GRIPPER_CONTACT == False):
current_width = magnetic_calibration.get_current_gripper_width()
print(current_width)
fa.goto_gripper(current_width - gripper_step_size)
#magnetic_calibration.get_last_magnetic_data()
mag_data = magnetic_calibration.get_previous_magnetic_samples(
num_samples) # grab last ten samples
xyz_mag_data = mag_data[:, 6]
print(xyz_mag_data)
#slope = np.diff(xyz_mag_data, axis=0)
#print(slope)
# asign = np.sign(slope)
# signchange = ((np.roll(asign, 1) - asign) != 0).astype(int)
# print(signchange)
# first make sure the signal changes are large enough to not just be noise jitter
# then see if there is a signal change in slope - this signifies a contact.
#if(np.any(abs(np.diff(mag_data)>noise_level))):
#if(abs(np.sum(np.sign(np.diff(mag_data)))<numSamples) & abs(np.diff(mag_data))>noise_level):
if global_min is None:
global_min = np.min(xyz_mag_data, axis=0)
elif global_min > np.min(xyz_mag_data, axis=0):
global_min = np.min(xyz_mag_data, axis=0)
if xyz_mag_data[-1] - global_min > noise_level:
GRIPPER_CONTACT = True
min_gripper_width = current_width - 2 * gripper_step_size
print(min_gripper_width)
print("Min Magnetic Values: ")
print(min_contact)
gripper_step_size -= 0.00003
# if (np.any(np.logical_and((abs(slope)>noise_level), (slope > 0)))):
# # if last value is negative, contact. if last value is positive, release.
# # save max value so we can compare current value and strength of grip
# GRIPPER_CONTACT = True
# min_contact = np.min(xyz_mag_data, axis=0)
# min_gripper_width = current_width-gripper_step_size
# print(min_gripper_width)
# print("Min Magnetic Values: ")
# print(min_contact)
#input("Press enter to continue to next step")
#magnetic_calibration.close_gripper_magnetic_feedback()
# current_width = min_gripper_width
# num_samples = 100
# while(current_force_estimate < force_threshold):
# current_width -= gripper_step_size
# print(current_width)
# fa.goto_gripper(current_width)
# mag_data = magnetic_calibration.get_previous_magnetic_samples(num_samples) # grab last ten samples
# z_mag_data = np.max(mag_data[:,6])
# print(z_mag_data)
# current_force_estimate = global_min / z_mag_data
# print(current_force_estimate)
fa.goto_pose_delta_with_cartesian_control(relative_pos_dist_z)
current_joints = fa.get_joints()
current_joints[6] -= math.pi
fa.goto_joints(list(current_joints))
current_position = fa.get_pose()
fa.goto_pose_with_cartesian_control(squeeze_position1)
fa.goto_pose_with_cartesian_control(squeeze_position2)
for i in range(3):
for j in range(i + 1):
fa.goto_gripper(0.0, force=20)
fa.goto_gripper(min_gripper_width)
if i < 2:
fa.goto_pose_delta_with_cartesian_control(relative_pos_dist_x)
fa.goto_pose_with_cartesian_control(current_position, 5)
current_joints = fa.get_joints()
current_joints[6] += math.pi
fa.goto_joints(list(current_joints))
fa.goto_pose_delta_with_cartesian_control(relative_neg_dist_z)
fa.open_gripper()
fa.goto_pose_with_cartesian_control(initial_magnet_position1)
#fa.goto_pose_delta_with_cartesian_control(relative_neg_dist_z)
magnetic_calibration.stop_recording_data()
#fa.open_gripper()
print(magnetic_calibration.magnetic_data[0, :])
if args.filename is not None:
magnetic_calibration.saveData(args.filename, min_contact,
min_gripper_width)
magnetic_calibration.plotData(magnetic_calibration.magnetic_data,
'Raw Data Over Time')
magnetic_calibration.plotGripperData(
magnetic_calibration.gripper_state_data, 'Raw Data Over Time')
magnetic_calibration.plotGripperData(magnetic_calibration.robot_state_data,
'Raw Data Over Time')
# read functions
T_ee_world = fa.get_pose()
print('Translation: {} | Rotation: {}'.format(T_ee_world.translation, T_ee_world.quaternion))
joints = fa.get_joints()
print('Joints: {}'.format(joints))
gripper_width = fa.get_gripper_width()
print('Gripper width: {}'.format(gripper_width))
# gripper controls
print('Closing gripper')
fa.close_gripper()
print('Opening gripper to a specified position')
fa.goto_gripper(0.02)
print('Opening gripper all the way')
fa.open_gripper()
# joint controls
print('Rotating last joint')
joints = fa.get_joints()
joints[6] += np.deg2rad(45)
fa.goto_joints(joints)
joints[6] -= np.deg2rad(45)
fa.goto_joints(joints)
# end-effector pose control
print('Translation')
T_ee_world = fa.get_pose()
def run_main():
parser = argparse.ArgumentParser()
parser.add_argument('--filename', type=str, default=None)
args = parser.parse_args()
fa = FrankaArm()
fa.open_gripper()
# fa.reset_pose()
fa.reset_joints(10)
pipette_rotation = np.array([[1, 0, 0], [0, -1, 0], [0, 0, -1]])
initial_magnet_position1 = RigidTransform(
rotation=pipette_rotation,
translation=np.array([0.45683638, 0.06513334, 0.20451204]),
from_frame='franka_tool',
to_frame='world')
initial_magnet_position2 = RigidTransform(
rotation=pipette_rotation,
translation=np.array([0.45683638, 0.06513334, 0.15451204]),
from_frame='franka_tool',
to_frame='world')
initial_magnet_position3 = RigidTransform(
rotation=pipette_rotation,
translation=np.array([0.45683638, 0.06513334, 0.33451204]),
from_frame='franka_tool',
to_frame='world')
beaker_position1 = RigidTransform(rotation=pipette_rotation,
translation=np.array(
[0.44724006, 0.2870516, 0.33210899]),
from_frame='franka_tool',
to_frame='world')
beaker_position2 = RigidTransform(rotation=pipette_rotation,
translation=np.array(
[0.44724006, 0.2870516, 0.16210899]),
from_frame='franka_tool',
to_frame='world')
test_tube_1 = RigidTransform(rotation=pipette_rotation,
translation=np.array(
[0.54359048, 0.17224207, 0.19106597]),
from_frame='franka_tool',
to_frame='world')
test_tube_2 = RigidTransform(rotation=pipette_rotation,
translation=np.array(
[0.56359048, 0.17224207, 0.19106597]),
from_frame='franka_tool',
to_frame='world')
test_tube_3 = RigidTransform(rotation=pipette_rotation,
translation=np.array(
[0.58359048, 0.17224207, 0.19106597]),
from_frame='franka_tool',
to_frame='world')
relative_pos_dist_z = RigidTransform(
rotation=np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]),
translation=np.array([0.0, 0.0, 0.175]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_pos_dist_y = RigidTransform(rotation=np.array([[1, 0,
0], [0, 1, 0],
[0, 0, 1]]),
translation=np.array([0.0, 0.02,
0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_rotation_z = RigidTransform(rotation=np.array([[0, 1, 0],
[-1, 0, 0],
[0, 0, 1]]),
translation=np.array([0.0, 0.0, 0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_neg_rotation_z = RigidTransform(rotation=np.array([[0, -1, 0],
[1, 0, 0],
[0, 0, 1]]),
translation=np.array(
[0.0, 0.0, 0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_neg_dist_y = RigidTransform(rotation=np.array([[1, 0,
0], [0, 1, 0],
[0, 0, 1]]),
translation=np.array([0.0, -0.1,
0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_neg_dist_z = RigidTransform(
rotation=np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]),
translation=np.array([0.0, 0.0, -0.175]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_pos_dist_x = RigidTransform(
rotation=np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]),
translation=np.array([0.075, 0.0, 0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
relative_neg_dist_x = RigidTransform(
rotation=np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]),
translation=np.array([-0.03, 0.0, 0.0]),
from_frame='franka_tool',
to_frame='franka_tool')
fa.goto_pose_with_cartesian_control(initial_magnet_position1)
fa.goto_pose_with_cartesian_control(initial_magnet_position2)
magnetic_calibration = MagneticCalibration()
filename = '../calibration/2020-01-14 11-08 E1 2X Board Calibration.npz'
magnetic_calibration.load_calibration_file(filename)
# Close the gripper and save corresponding robot state, gripper state, and magnetic state data
magnetic_calibration.start_recording_data()
time.sleep(1)
# fa.goto_pose_delta_with_cartesian_control(relative_x_dist, 10)
# max width is about 0.080 m
gripper_step_size = 0.005 # in meters
num_samples = 30
noise_level = 15 # uT
force_threshold = 1.05
GRIPPER_CONTACT = False
min_contact = None
min_gripper_width = None
global_max = None
current_force_estimate = 1
while (GRIPPER_CONTACT == False):
current_width = magnetic_calibration.get_current_gripper_width()
print(current_width)
fa.goto_gripper(current_width - gripper_step_size)
#magnetic_calibration.get_last_magnetic_data()
mag_data = magnetic_calibration.get_previous_magnetic_samples(
num_samples) # grab last ten samples
xyz_mag_data = mag_data[:, 6]
print(xyz_mag_data)
#slope = np.diff(xyz_mag_data, axis=0)
#print(slope)
# asign = np.sign(slope)
# signchange = ((np.roll(asign, 1) - asign) != 0).astype(int)
# print(signchange)
# first make sure the signal changes are large enough to not just be noise jitter
# then see if there is a signal change in slope - this signifies a contact.
#if(np.any(abs(np.diff(mag_data)>noise_level))):
#if(abs(np.sum(np.sign(np.diff(mag_data)))<numSamples) & abs(np.diff(mag_data))>noise_level):
if global_max is None:
global_max = np.max(xyz_mag_data, axis=0)
elif global_max < np.max(xyz_mag_data, axis=0):
global_max = np.max(xyz_mag_data, axis=0)
if global_max - xyz_mag_data[-1] > noise_level:
GRIPPER_CONTACT = True
min_gripper_width = current_width
fa.goto_gripper(min_gripper_width)
#min_contact = xyz_mag_data[-1]
print(min_gripper_width)
print("Global Max: ")
print(global_max)
gripper_step_size -= 0.0001
# if (np.any(np.logical_and((abs(slope)>noise_level), (slope > 0)))):
# # if last value is negative, contact. if last value is positive, release.
# # save max value so we can compare current value and strength of grip
# GRIPPER_CONTACT = True
# min_contact = np.min(xyz_mag_data, axis=0)
# min_gripper_width = current_width-gripper_step_size
# print(min_gripper_width)
# print("Min Magnetic Values: ")
# print(min_contact)
#input("Press enter to continue to next step")
#magnetic_calibration.close_gripper_magnetic_feedback()
# current_width = min_gripper_width
# num_samples = 100
# while(current_force_estimate < force_threshold):
# current_width -= gripper_step_size
# print(current_width)
# fa.goto_gripper(current_width)
# mag_data = magnetic_calibration.get_previous_magnetic_samples(num_samples) # grab last ten samples
# z_mag_data = np.max(mag_data[:,6])
# print(z_mag_data)
# current_force_estimate = global_min / z_mag_data
# print(current_force_estimate)
fa.goto_pose_delta_with_cartesian_control(relative_pos_dist_z)
for i in range(3):
fa.goto_pose_with_cartesian_control(beaker_position1)
fa.goto_pose_with_cartesian_control(beaker_position2)
fa.goto_gripper(0.0, force=20)
fa.goto_gripper(min_gripper_width)
fa.goto_pose_delta_with_cartesian_control(relative_pos_dist_z)
if i == 0:
force_value = 15
fa.goto_pose_with_cartesian_control(test_tube_1)
elif i == 1:
force_value = 30
fa.goto_pose_with_cartesian_control(test_tube_2)
elif i == 2:
force_value = 50
fa.goto_pose_with_cartesian_control(test_tube_3)
force_gripper_width = min_gripper_width
for j in range(5):
mag_data = magnetic_calibration.get_previous_magnetic_samples(
num_samples)
max_data = np.max(mag_data[:, 6], axis=0)
current_force_estimate = max_data - force_value
print("Force Threshold:")
print(current_force_estimate)
force_achieved = False
gripper_step_size = 0.0003
num_samples = 30
while (force_achieved == False):
force_gripper_width -= gripper_step_size
fa.goto_gripper(force_gripper_width)
#magnetic_calibration.get_last_magnetic_data()
mag_data = magnetic_calibration.get_previous_magnetic_samples(
num_samples) # grab last ten samples
print(np.mean(mag_data[:, 6]))
#slope = np.diff(xyz_mag_data, axis=0)
#print(slope)
# asign = np.sign(slope)
# signchange = ((np.roll(asign, 1) - asign) != 0).astype(int)
# print(signchange)
# first make sure the signal changes are large enough to not just be noise jitter
# then see if there is a signal change in slope - this signifies a contact.
#if(np.any(abs(np.diff(mag_data)>noise_level))):
#if(abs(np.sum(np.sign(np.diff(mag_data)))<numSamples) & abs(np.diff(mag_data))>noise_level):
if np.mean(mag_data[:, 6]) < current_force_estimate:
force_achieved = True
print(force_gripper_width)
if (j < 4):
fa.goto_pose_delta_with_cartesian_control(relative_pos_dist_y)
fa.goto_gripper(min_gripper_width)
fa.goto_pose_delta_with_cartesian_control(relative_pos_dist_z)
# for i in range(5):
# fa.goto_pose_with_cartesian_control(beaker_position1)
# fa.goto_pose_with_cartesian_control(beaker_position2)
# fa.goto_gripper(0.0, force = 20)
# fa.goto_gripper(min_gripper_width)
# fa.goto_pose_delta_with_cartesian_control(relative_pos_dist_z)
# #fa.goto_gripper(min_gripper_width)
# fa.goto_pose_with_cartesian_control(test_tube_1)
# fa.goto_gripper(force_gripper_width)
# fa.goto_gripper(min_gripper_width)
fa.goto_pose_with_cartesian_control(beaker_position1)
fa.goto_pose_with_cartesian_control(beaker_position2)
fa.goto_gripper(0.0, force=20)
fa.goto_pose_delta_with_cartesian_control(relative_pos_dist_z)
fa.goto_gripper(min_gripper_width)
fa.goto_pose_with_cartesian_control(initial_magnet_position3)
fa.goto_pose_with_cartesian_control(initial_magnet_position1)
fa.goto_pose_with_cartesian_control(initial_magnet_position2)
fa.open_gripper()
fa.goto_pose_with_cartesian_control(initial_magnet_position1)
# for i in range(3):
# for j in range(i+1):
# fa.goto_gripper(0.0, force = 20)
# fa.goto_gripper(min_gripper_width)
# if i < 2:
# fa.goto_pose_delta_with_cartesian_control(relative_pos_dist_x)
# fa.goto_pose_with_cartesian_control(current_position,5)
# current_joints = fa.get_joints()
# current_joints[6] += math.pi
# fa.goto_joints(list(current_joints))
# fa.goto_pose_delta_with_cartesian_control(relative_neg_dist_z)
# fa.open_gripper()
# fa.goto_pose_with_cartesian_control(initial_magnet_position1)
#fa.goto_pose_delta_with_cartesian_control(relative_neg_dist_z)
magnetic_calibration.stop_recording_data()
#fa.open_gripper()
print(magnetic_calibration.magnetic_data[0, :])
if args.filename is not None:
magnetic_calibration.saveData(args.filename, global_max,
min_gripper_width)
magnetic_calibration.plotData(magnetic_calibration.magnetic_data,
'Raw Data Over Time')
magnetic_calibration.plotGripperData(
magnetic_calibration.gripper_state_data, 'Raw Data Over Time')
magnetic_calibration.plotGripperData(magnetic_calibration.robot_state_data,
'Raw Data Over Time')
