class Robot_Interface(object):
"""For usage with the Fetch robot."""
def __init__(self, simulation=True):
"""Initializes various aspects of the Fetch.
TODOs: get things working, also use `simulation` flag to change ROS
topic names if necessary (especially for the cameras!). UPDATE: actually
I don't think this is necessary now, they have the same topic names.
"""
rospy.init_node("fetch")
self.arm = Arm()
self.arm_joints = ArmJoints()
self.base = Base()
self.camera = RGBD()
self.head = Head()
self.gripper = Gripper(self.camera)
self.torso = Torso()
self.joint_reader = JointStateReader()
# Tucked arm starting joint angle configuration
self.names = ArmJoints().names()
self.tucked = [1.3200, 1.3999, -0.1998, 1.7199, 0.0, 1.6600, 0.0]
self.tucked_list = [(x, y) for (x, y) in zip(self.names, self.tucked)]
# Initial (x,y,yaw) position of the robot wrt map origin. We keep this
# fixed so that we can reset to this position as needed. The HSR's
# `omni_base.pose` (i.e., the start pose) returns (x,y,yaw) where yaw is
# the rotation about that axis (intuitively, the z axis). For the base,
# `base.odom` supplies both `position` and `orientation` attributes.
start = copy.deepcopy(self.base.odom.position)
yaw = Base._yaw_from_quaternion(self.base.odom.orientation)
self.start_pose = np.array([start.x, start.y, yaw])
self.TURN_SPEED = 0.3
self.num_restarts = 0
def body_start_pose(self,
start_height=0.10,
end_height=0.10,
velocity_factor=None):
"""Sets the robot's body to some initial configuration.
The HSR uses `whole_body.move_to_go()` which initializes an appropriate
posture so that the hand doesn't collide with movement. For the Fetch,
we should probably make the torso extend, so the arms can extend more
easily without collisions. Use `move_to_joint_goal` since that uses
motion planning. Do NOT directly set the joints without planning!!
"""
self.torso.set_height(start_height)
self.arm.move_to_joint_goal(self.tucked_list,
velocity_factor=velocity_factor)
self.torso.set_height(end_height)
# Specific to the siemens challenge (actually a lot of this stuff is ...)
if self.num_restarts == 0:
self.base.turn(angular_distance=45 * DEG_TO_RAD)
self.num_restarts += 1
def head_start_pose(self):
"""Hard-coded starting pose for the robot's head.
These values are from the HSR. The Fetch needs a different pan and tilt.
Positive pan means rotating counterclockwise when looking at robot from
an aerial view.
"""
self.head.pan_tilt(pan=0.0, tilt=0.8)
def position_start_pose(self, offsets=None, do_something=False):
"""Assigns the robot's base to some starting pose.
Mainly to "reset" the robot to the original starting position (and also,
rotation about base axis) after it has moved, usually w/no offsets.
Ugly workaround: we have target (x,y), and compute the distance to the
point and the angle. We turn the Fetch according to that angle, and go
forward. Finally, we do a second turn which corresponds to the target
yaw at the end. This turns w.r.t. the current angle, so we undo the
effect of the first turn. See `examples/test_position_start_pose.py`
for tests.
Args:
offsets: a list of length 3, indicating offsets in the x, y, and
yaws, respectively, to be added onto the starting pose.
"""
# Causing problems during my tests of the Siemens demo.
if not do_something:
return
current_pos = copy.deepcopy(self.base.odom.position)
current_theta = Base._yaw_from_quaternion(
self.base.odom.orientation) # [-pi, pi]
ss = np.array([current_pos.x, current_pos.y, current_theta])
# Absolute target position and orientation specified with `pp`.
pp = np.copy(self.start_pose)
if offsets:
pp += np.array(offsets)
# Get distance to travel, critically assumes `pp` is starting position.
dist = np.sqrt((ss[0] - pp[0])**2 + (ss[1] - pp[1])**2)
rel_x = ss[0] - pp[0]
rel_y = ss[1] - pp[1]
assert -1 <= rel_x / dist <= 1
assert -1 <= rel_y / dist <= 1
# But we also need to be *facing* the correct direction, w/input [-1,1].
# First, get the opposite view (facing "outwards"), then flip by 180.
desired_facing = np.arctan2(rel_y, rel_x) # [-pi, pi], facing outward
desired_theta = math.pi + desired_facing # [0, 2*pi], flip by 180
if desired_theta > math.pi:
desired_theta -= 2 * math.pi # [-pi, pi]
# Reconcile with the current theta. Got this by basically trial/error
angle = desired_theta - current_theta # [-2*pi, 2*pi]
if angle > math.pi:
angle -= 2 * math.pi
elif angle < -math.pi:
angle += 2 * math.pi
self.base.turn(angular_distance=angle, speed=self.TURN_SPEED)
self.base.go_forward(distance=dist, speed=0.2)
# Back at the start x, y, but now need to consider the _second_ turn.
# The robot is facing at `desired_theta` rads, but wants `pp[2]` rads.
final_angle = pp[2] - desired_theta
if final_angle > math.pi:
final_angle -= 2 * math.pi
elif final_angle < -math.pi:
final_angle += 2 * math.pi
self.base.turn(angular_distance=final_angle, speed=self.TURN_SPEED)
def get_img_data(self):
"""Obtain camera and depth image.
Returns:
Tuple containing RGB camera image and corresponding depth image.
"""
c_img = self.camera.read_color_data()
d_img = self.camera.read_depth_data()
return (c_img, d_img)
def get_depth(self, point, d_img):
"""Compute mean depth near grasp point.
NOTE: assumes that we have a simlar `cfg.ZRANGE` as with the HSR. I'm
not sure where exactly this comes from.
"""
y, x = int(point[0]), int(point[1])
# z_box = d_img[y-ZRANGE:y+ZRANGE, x-ZRANGE:x+ZRANGE]
z_box = d_img[y - 20:y + 20, x - 20:x + 20]
indx = np.nonzero(z_box)
z = np.mean(z_box[indx])
return z
# y, x = int(point[0]), int(point[1])
# # z_box = d_img[y-ZRANGE:y+ZRANGE, x-ZRANGE:x+ZRANGE]
# z_box = d_img[y-10:y + 10, x - 10:x + 10]
# indx = np.nonzero(z_box)
# z = np.mean(z_box[indx])
# return z
def get_rot(self, direction):
"""Compute rotation of gripper such that given vector is grasped.
Currently this directly follows the HSR code as there's nothing
Fetch-dependent.
"""
dy, dx = direction[0], direction[1]
dx *= -1
if dy < 0:
dx *= -1
dy *= -1
rot = np.arctan2(dy, dx)
rot = np.pi - rot
return rot
def create_grasp_pose(self, x, y, z, rot):
""" If `intuitive=True` then x,y,z,rot interpreted wrt some link in the
world, e.g., 'odom' for the Fetch. It's False by default to maintain
backwards compatibility w/Siemens-based code.
"""
pose_name = self.gripper.create_grasp_pose(x, y, z, rot)
return pose_name
def open_gripper(self):
self.gripper.open()
def close_gripper(self):
self.gripper.close()
def move_to_pose(self, pose_name, z_offset, velocity_factor=None):
"""Moves to a pose.
In the HSR, moved the `hand_palm_link` to the frame named `pose_name` at
the correct pose. For the Fetch we should be able to extract the pose
from `pose_name` and then call the Arm's `move_to_pose` method.
Args:
pose_name: A string name for the pose to go
z_offset: Scalar offset in z-direction, offset is wrt the pose
specified by `pose_name`.
velocity_factor: controls the speed, closer to 0 means slower,
closer to 1 means faster. (If 0.0, then it turns into 1.0 for
some reason.) Values greater than 1.0 are cut to 1.0.
"""
# See:
# http://wiki.ros.org/tf/Tutorials/Writing%20a%20tf%20listener%20%28Python%29
# https://answers.ros.org/question/256354/does-tftransformlistenerlookuptransform-return-quaternion-position-or-translation-and-rotation/
# First frame should be the reference frame, use `base_link`, not `odom`.
point, quat = self.gripper.tl.lookupTransform('base_link', pose_name,
rospy.Time(0))
z_point = point[2] + z_offset
# See:
# https://github.com/cse481wi18/cse481wi18/blob/indigo-devel/applications/scripts/cart_arm_demo.py
# https://github.com/cse481wi18/cse481wi18/wiki/Lab-19%3A-Cartesian-space-manipulation
ps = PoseStamped()
ps.header.frame_id = 'base_link'
ps.pose = Pose(Point(point[0], point[1], z_point),
Quaternion(quat[0], quat[1], quat[2], quat[3]))
# See `arm.py` written by Justin Huang
error = self.arm.move_to_pose(pose_stamped=ps,
velocity_factor=velocity_factor)
if error is not None:
rospy.logerr(error)
def find_ar(self, ar_number, velocity_factor=None):
try:
ar_name = 'ar_marker/' + str(ar_number)
# HSR code, with two hard-coded offsets?
#self.whole_body.move_end_effector_pose(geometry.pose(y=0.08, z=-0.3), ar_name)
# Fetch 'translation'. Note the `ar_name` for pose name.
point, quat = self.gripper.tl.lookupTransform(
'base_link', ar_name, rospy.Time(0))
y_point = point[1] + 0.08
z_point = point[2] - 0.3
ps = PoseStamped()
ps.header.frame_id = 'base_link'
ps.pose = Pose(Point(point[0], y_point, z_point),
Quaternion(quat[0], quat[1], quat[2], quat[3]))
error = self.arm.move_to_pose(pose_stamped=ps,
velocity_factor=velocity_factor)
if error is not None:
rospy.logerr(error)
return True
except:
return False
def pan_head(self, tilt):
"""Adjusts tilt of the robot, AND set pan at zero.
Args:
tilt: Value in radians, positive means looking downwards.
"""
self.head.pan_tilt(pan=0, tilt=tilt)
class Robot_Skeleton(object):
"""Basic bare-bones solution for the Fetch robot interface.
We recommend extending this class with additional convenience methods based
on your application needs.
"""
def __init__(self, simulation=True):
"""Initializes various aspects of the Fetch."""
rospy.init_node("fetch")
rospy.loginfo("initializing the Fetch...")
self.arm = Arm()
self.arm_joints = ArmJoints()
self.base = Base()
self.camera = RGBD()
self.head = Head()
self.gripper = Gripper(self.camera)
self.torso = Torso()
self.joint_reader = JointStateReader()
# Tucked arm starting joint angle configuration
self.names = ArmJoints().names()
self.tucked = [1.3200, 1.3999, -0.1998, 1.7199, 0.0, 1.6600, 0.0]
self.tucked_list = [(x,y) for (x,y) in zip(self.names, self.tucked)]
# Initial (x,y,yaw) position of the robot wrt map origin. We keep this
# fixed so that we can reset to this position as needed. The HSR's
# `omni_base.pose` (i.e., the start pose) returns (x,y,yaw) where yaw is
# the rotation about that axis (intuitively, the z axis). For the base,
# `base.odom` supplies both `position` and `orientation` attributes.
start = copy.deepcopy(self.base.odom.position)
yaw = Base._yaw_from_quaternion(self.base.odom.orientation)
self.start_pose = np.array([start.x, start.y, yaw])
rospy.loginfo("...finished initialization!")
def body_start_pose(self, start_height=0.10, end_height=0.10, velocity_factor=0.5):
"""Sets the robot's body to some initial configuration.
Tucks the arm using motion planning. NEVER directly set joints as that
often leads to collisions.
Args:
start_height: Height in meters for Fetch before arm-tuck.
end_height: Height in meters for Fetch after arm-tuck.
velocity_factor: controls the speed, closer to 0 means slower,
closer to 1 means faster. (If 0.0, then it turns into 1.0 for
some reason.) Values greater than 1.0 are cut to 1.0.
"""
self.torso.set_height(start_height)
self.arm.move_to_joint_goal(self.tucked_list, velocity_factor=velocity_factor)
self.torso.set_height(end_height)
def head_start_pose(self, pan=0.0, tilt=0.0):
"""Sets the robot's head to some initial configuration.
Args:
pan: Value in radians for head sideways rotation, counterclockwise
when looking at robot from an aerial view.
tilt: Value in radians for head up/down movement, positive means
looking downwards.
"""
self.head.pan_tilt(pan=pan, tilt=tilt)
def get_img_data(self):
"""Obtain camera and depth image.
Returns:
Tuple containing RGB camera image and corresponding depth image.
"""
c_img = self.camera.read_color_data()
d_img = self.camera.read_depth_data()
return (c_img, d_img)
def create_grasp_pose(self, x, y, z, rot_x, rot_y, rot_z):
"""Creates a pose in the world for the robot's end-effect to go to.
Args:
x, y, z, rot_x, rot_y, rot_z: A 6-D pose description.
"""
pose_name = self.gripper.create_grasp_pose_intuitive(
x, y, z, rot_x, rot_y, rot_z)
return pose_name
def move_to_pose(self, pose_name, velocity_factor=None):
"""Moves to a pose.
In the HSR, moved the `hand_palm_link` to the frame named `pose_name` at
the correct pose. For the Fetch we should be able to extract the pose
from `pose_name` and then call the Arm's `move_to_pose` method.
Args:
pose_name: A string name for the pose to go
velocity_factor: controls the speed, closer to 0 means slower,
closer to 1 means faster. (If 0.0, then it turns into 1.0 for
some reason.) Values greater than 1.0 are cut to 1.0.
"""
# See:
# http://wiki.ros.org/tf/Tutorials/Writing%20a%20tf%20listener%20%28Python%29
# https://answers.ros.org/question/256354/does-tftransformlistenerlookuptransform-return-quaternion-position-or-translation-and-rotation/
# First frame should be the reference frame, use `base_link`, not `odom`.
point, quat = self.gripper.tl.lookupTransform('base_link', pose_name, rospy.Time(0))
# See:
# https://github.com/cse481wi18/cse481wi18/blob/indigo-devel/applications/scripts/cart_arm_demo.py
# https://github.com/cse481wi18/cse481wi18/wiki/Lab-19%3A-Cartesian-space-manipulation
ps = PoseStamped()
ps.header.frame_id = 'base_link'
ps.pose = Pose(
Point(point[0], point[1], point[2]),
Quaternion(quat[0], quat[1], quat[2], quat[3])
)
# See `arm.py` written by Justin Huang
error = self.arm.move_to_pose(pose_stamped=ps, velocity_factor=velocity_factor)
if error is not None:
rospy.logerr(error)
def open_gripper(self):
self.gripper.open()
def close_gripper(self, width=0.0, max_effort=100):
self.gripper.close(width=width, max_effort=max_effort)
for k, v in zip(names, arm_vals):
print '{}\t{:.4f}'.format(k, v)
print("")
# Move and then read the joints again to be clear
pose = [0, 0, 0, 0, 0, 0, 0]
pose[1] = DEGS_TO_RADS * -70
arm.move_to_joints(ArmJoints.from_list(pose))
arm_vals = reader.get_joints(names)
for k, v in zip(names, arm_vals):
print '{}\t{:.4f}'.format(k, v)
print("")
if __name__ == "__main__":
rospy.init_node('arm_demo')
wait_for_time()
# Set things up
torso = Torso()
torso.set_height(Torso.MAX_HEIGHT)
arm = Arm()
reader = JointStateReader()
rospy.sleep(0.5)
rospy.loginfo("created torso, arm, and reader")
#test_shoulders(arm, torso)
#test_poses(arm, torso)
test_reader(arm, reader)