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Env.
Ubuntu 18.04 amd x64, ROS Melodic desktop full
문제
moveit으로 manipulator를 제어함에 있어서
아래의 ref 소스 코드를 나의 로봇의 환경에 맞게 수정하여
테스트를 진행하였다.
go_to_joint_state와 go_to_pose_goal은 동작하는데
plan_cartesian_path를 실행하고 excute_plan을 실행하면 아래와 같은 오류가 발생하였다.
[ERROR] [1663909634.190423432]: Controller is taking too long to execute trajectory (the expected upper bound for the trajectory execution was 6.684279 seconds). Stopping trajectory.
원인
아래의 ref 소스 코드의 waypoints는
현재의 pose를 포함하지않고 cartesian_path를 계산하는데
코드를 수정하다가
내 실수로 인해 현재 pose를 포함하였더니
rviz상에서는 path plan을 보여주나,
실제 로봇이 움직이지는 못했다.
해결 방법
- cartesian_path를 계산하는데 waypoints에 경로가 현재 좌표를 제외한 하나만 존재한다면, 현재의 pose 좌표를 포함해서는 안됨
- cartesian_path를 계산하는데 waypoints에 경로가 여러 개 존재한다면, 현재의 pose 좌표를 포함해도 작동은 함
ref.
GitHub - ros-planning/moveit_tutorials: A sphinx-based centralized documentation repo for MoveIt
A sphinx-based centralized documentation repo for MoveIt - GitHub - ros-planning/moveit_tutorials: A sphinx-based centralized documentation repo for MoveIt
github.com
#!/usr/bin/env python
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#
# Copyright (c) 2013, SRI International
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# from this software without specific prior written permission.
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# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
# Author: Acorn Pooley, Mike Lautman
## BEGIN_SUB_TUTORIAL imports
##
## To use the Python MoveIt interfaces, we will import the `moveit_commander`_ namespace.
## This namespace provides us with a `MoveGroupCommander`_ class, a `PlanningSceneInterface`_ class,
## and a `RobotCommander`_ class. More on these below. We also import `rospy`_ and some messages that we will use:
##
# Python 2/3 compatibility imports
from __future__ import print_function
from six.moves import input
import sys
import copy
import rospy
import moveit_commander
import moveit_msgs.msg
import geometry_msgs.msg
try:
from math import pi, tau, dist, fabs, cos
except: # For Python 2 compatibility
from math import pi, fabs, cos, sqrt
tau = 2.0 * pi
def dist(p, q):
return sqrt(sum((p_i - q_i) ** 2.0 for p_i, q_i in zip(p, q)))
from std_msgs.msg import String
from moveit_commander.conversions import pose_to_list
## END_SUB_TUTORIAL
def all_close(goal, actual, tolerance):
"""
Convenience method for testing if the values in two lists are within a tolerance of each other.
For Pose and PoseStamped inputs, the angle between the two quaternions is compared (the angle
between the identical orientations q and -q is calculated correctly).
@param: goal A list of floats, a Pose or a PoseStamped
@param: actual A list of floats, a Pose or a PoseStamped
@param: tolerance A float
@returns: bool
"""
if type(goal) is list:
for index in range(len(goal)):
if abs(actual[index] - goal[index]) > tolerance:
return False
elif type(goal) is geometry_msgs.msg.PoseStamped:
return all_close(goal.pose, actual.pose, tolerance)
elif type(goal) is geometry_msgs.msg.Pose:
x0, y0, z0, qx0, qy0, qz0, qw0 = pose_to_list(actual)
x1, y1, z1, qx1, qy1, qz1, qw1 = pose_to_list(goal)
# Euclidean distance
d = dist((x1, y1, z1), (x0, y0, z0))
# phi = angle between orientations
cos_phi_half = fabs(qx0 * qx1 + qy0 * qy1 + qz0 * qz1 + qw0 * qw1)
return d <= tolerance and cos_phi_half >= cos(tolerance / 2.0)
return True
class MoveGroupPythonInterfaceTutorial(object):
"""MoveGroupPythonInterfaceTutorial"""
def __init__(self):
super(MoveGroupPythonInterfaceTutorial, self).__init__()
## BEGIN_SUB_TUTORIAL setup
##
## First initialize `moveit_commander`_ and a `rospy`_ node:
moveit_commander.roscpp_initialize(sys.argv)
rospy.init_node("move_group_python_interface_tutorial", anonymous=True)
## Instantiate a `RobotCommander`_ object. Provides information such as the robot's
## kinematic model and the robot's current joint states
robot = moveit_commander.RobotCommander()
## Instantiate a `PlanningSceneInterface`_ object. This provides a remote interface
## for getting, setting, and updating the robot's internal understanding of the
## surrounding world:
scene = moveit_commander.PlanningSceneInterface()
## Instantiate a `MoveGroupCommander`_ object. This object is an interface
## to a planning group (group of joints). In this tutorial the group is the primary
## arm joints in the Panda robot, so we set the group's name to "panda_arm".
## If you are using a different robot, change this value to the name of your robot
## arm planning group.
## This interface can be used to plan and execute motions:
group_name = "panda_arm"
move_group = moveit_commander.MoveGroupCommander(group_name)
## Create a `DisplayTrajectory`_ ROS publisher which is used to display
## trajectories in Rviz:
display_trajectory_publisher = rospy.Publisher(
"/move_group/display_planned_path",
moveit_msgs.msg.DisplayTrajectory,
queue_size=20,
)
## END_SUB_TUTORIAL
## BEGIN_SUB_TUTORIAL basic_info
##
## Getting Basic Information
## ^^^^^^^^^^^^^^^^^^^^^^^^^
# We can get the name of the reference frame for this robot:
planning_frame = move_group.get_planning_frame()
print("============ Planning frame: %s" % planning_frame)
# We can also print the name of the end-effector link for this group:
eef_link = move_group.get_end_effector_link()
print("============ End effector link: %s" % eef_link)
# We can get a list of all the groups in the robot:
group_names = robot.get_group_names()
print("============ Available Planning Groups:", robot.get_group_names())
# Sometimes for debugging it is useful to print the entire state of the
# robot:
print("============ Printing robot state")
print(robot.get_current_state())
print("")
## END_SUB_TUTORIAL
# Misc variables
self.box_name = ""
self.robot = robot
self.scene = scene
self.move_group = move_group
self.display_trajectory_publisher = display_trajectory_publisher
self.planning_frame = planning_frame
self.eef_link = eef_link
self.group_names = group_names
def go_to_joint_state(self):
# Copy class variables to local variables to make the web tutorials more clear.
# In practice, you should use the class variables directly unless you have a good
# reason not to.
move_group = self.move_group
## BEGIN_SUB_TUTORIAL plan_to_joint_state
##
## Planning to a Joint Goal
## ^^^^^^^^^^^^^^^^^^^^^^^^
## The Panda's zero configuration is at a `singularity <https://www.quora.com/Robotics-What-is-meant-by-kinematic-singularity>`_, so the first
## thing we want to do is move it to a slightly better configuration.
## We use the constant `tau = 2*pi <https://en.wikipedia.org/wiki/Turn_(angle)#Tau_proposals>`_ for convenience:
# We get the joint values from the group and change some of the values:
joint_goal = move_group.get_current_joint_values()
joint_goal[0] = 0
joint_goal[1] = -tau / 8
joint_goal[2] = 0
joint_goal[3] = -tau / 4
joint_goal[4] = 0
joint_goal[5] = tau / 6 # 1/6 of a turn
joint_goal[6] = 0
# The go command can be called with joint values, poses, or without any
# parameters if you have already set the pose or joint target for the group
move_group.go(joint_goal, wait=True)
# Calling ``stop()`` ensures that there is no residual movement
move_group.stop()
## END_SUB_TUTORIAL
# For testing:
current_joints = move_group.get_current_joint_values()
return all_close(joint_goal, current_joints, 0.01)
def go_to_pose_goal(self):
# Copy class variables to local variables to make the web tutorials more clear.
# In practice, you should use the class variables directly unless you have a good
# reason not to.
move_group = self.move_group
## BEGIN_SUB_TUTORIAL plan_to_pose
##
## Planning to a Pose Goal
## ^^^^^^^^^^^^^^^^^^^^^^^
## We can plan a motion for this group to a desired pose for the
## end-effector:
pose_goal = geometry_msgs.msg.Pose()
pose_goal.orientation.w = 1.0
pose_goal.position.x = 0.4
pose_goal.position.y = 0.1
pose_goal.position.z = 0.4
move_group.set_pose_target(pose_goal)
## Now, we call the planner to compute the plan and execute it.
# `go()` returns a boolean indicating whether the planning and execution was successful.
success = move_group.go(wait=True)
# Calling `stop()` ensures that there is no residual movement
move_group.stop()
# It is always good to clear your targets after planning with poses.
# Note: there is no equivalent function for clear_joint_value_targets().
move_group.clear_pose_targets()
## END_SUB_TUTORIAL
# For testing:
# Note that since this section of code will not be included in the tutorials
# we use the class variable rather than the copied state variable
current_pose = self.move_group.get_current_pose().pose
return all_close(pose_goal, current_pose, 0.01)
def plan_cartesian_path(self, scale=1):
# Copy class variables to local variables to make the web tutorials more clear.
# In practice, you should use the class variables directly unless you have a good
# reason not to.
move_group = self.move_group
## BEGIN_SUB_TUTORIAL plan_cartesian_path
##
## Cartesian Paths
## ^^^^^^^^^^^^^^^
## You can plan a Cartesian path directly by specifying a list of waypoints
## for the end-effector to go through. If executing interactively in a
## Python shell, set scale = 1.0.
##
waypoints = []
wpose = move_group.get_current_pose().pose
wpose.position.z -= scale * 0.1 # First move up (z)
wpose.position.y += scale * 0.2 # and sideways (y)
waypoints.append(copy.deepcopy(wpose))
wpose.position.x += scale * 0.1 # Second move forward/backwards in (x)
waypoints.append(copy.deepcopy(wpose))
wpose.position.y -= scale * 0.1 # Third move sideways (y)
waypoints.append(copy.deepcopy(wpose))
# We want the Cartesian path to be interpolated at a resolution of 1 cm
# which is why we will specify 0.01 as the eef_step in Cartesian
# translation. We will disable the jump threshold by setting it to 0.0,
# ignoring the check for infeasible jumps in joint space, which is sufficient
# for this tutorial.
(plan, fraction) = move_group.compute_cartesian_path(
waypoints, 0.01, 0.0 # waypoints to follow # eef_step
) # jump_threshold
# Note: We are just planning, not asking move_group to actually move the robot yet:
return plan, fraction
## END_SUB_TUTORIAL
def display_trajectory(self, plan):
# Copy class variables to local variables to make the web tutorials more clear.
# In practice, you should use the class variables directly unless you have a good
# reason not to.
robot = self.robot
display_trajectory_publisher = self.display_trajectory_publisher
## BEGIN_SUB_TUTORIAL display_trajectory
##
## Displaying a Trajectory
## ^^^^^^^^^^^^^^^^^^^^^^^
## You can ask RViz to visualize a plan (aka trajectory) for you. But the
## group.plan() method does this automatically so this is not that useful
## here (it just displays the same trajectory again):
##
## A `DisplayTrajectory`_ msg has two primary fields, trajectory_start and trajectory.
## We populate the trajectory_start with our current robot state to copy over
## any AttachedCollisionObjects and add our plan to the trajectory.
display_trajectory = moveit_msgs.msg.DisplayTrajectory()
display_trajectory.trajectory_start = robot.get_current_state()
display_trajectory.trajectory.append(plan)
# Publish
display_trajectory_publisher.publish(display_trajectory)
## END_SUB_TUTORIAL
def execute_plan(self, plan):
# Copy class variables to local variables to make the web tutorials more clear.
# In practice, you should use the class variables directly unless you have a good
# reason not to.
move_group = self.move_group
## BEGIN_SUB_TUTORIAL execute_plan
##
## Executing a Plan
## ^^^^^^^^^^^^^^^^
## Use execute if you would like the robot to follow
## the plan that has already been computed:
move_group.execute(plan, wait=True)
## **Note:** The robot's current joint state must be within some tolerance of the
## first waypoint in the `RobotTrajectory`_ or ``execute()`` will fail
## END_SUB_TUTORIAL
def wait_for_state_update(
self, box_is_known=False, box_is_attached=False, timeout=4
):
# Copy class variables to local variables to make the web tutorials more clear.
# In practice, you should use the class variables directly unless you have a good
# reason not to.
box_name = self.box_name
scene = self.scene
## BEGIN_SUB_TUTORIAL wait_for_scene_update
##
## Ensuring Collision Updates Are Received
## ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
## If the Python node was just created (https://github.com/ros/ros_comm/issues/176),
## or dies before actually publishing the scene update message, the message
## could get lost and the box will not appear. To ensure that the updates are
## made, we wait until we see the changes reflected in the
## ``get_attached_objects()`` and ``get_known_object_names()`` lists.
## For the purpose of this tutorial, we call this function after adding,
## removing, attaching or detaching an object in the planning scene. We then wait
## until the updates have been made or ``timeout`` seconds have passed.
## To avoid waiting for scene updates like this at all, initialize the
## planning scene interface with ``synchronous = True``.
start = rospy.get_time()
seconds = rospy.get_time()
while (seconds - start < timeout) and not rospy.is_shutdown():
# Test if the box is in attached objects
attached_objects = scene.get_attached_objects([box_name])
is_attached = len(attached_objects.keys()) > 0
# Test if the box is in the scene.
# Note that attaching the box will remove it from known_objects
is_known = box_name in scene.get_known_object_names()
# Test if we are in the expected state
if (box_is_attached == is_attached) and (box_is_known == is_known):
return True
# Sleep so that we give other threads time on the processor
rospy.sleep(0.1)
seconds = rospy.get_time()
# If we exited the while loop without returning then we timed out
return False
## END_SUB_TUTORIAL
def add_box(self, timeout=4):
# Copy class variables to local variables to make the web tutorials more clear.
# In practice, you should use the class variables directly unless you have a good
# reason not to.
box_name = self.box_name
scene = self.scene
## BEGIN_SUB_TUTORIAL add_box
##
## Adding Objects to the Planning Scene
## ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
## First, we will create a box in the planning scene between the fingers:
box_pose = geometry_msgs.msg.PoseStamped()
box_pose.header.frame_id = "panda_hand"
box_pose.pose.orientation.w = 1.0
box_pose.pose.position.z = 0.11 # above the panda_hand frame
box_name = "box"
scene.add_box(box_name, box_pose, size=(0.075, 0.075, 0.075))
## END_SUB_TUTORIAL
# Copy local variables back to class variables. In practice, you should use the class
# variables directly unless you have a good reason not to.
self.box_name = box_name
return self.wait_for_state_update(box_is_known=True, timeout=timeout)
def attach_box(self, timeout=4):
# Copy class variables to local variables to make the web tutorials more clear.
# In practice, you should use the class variables directly unless you have a good
# reason not to.
box_name = self.box_name
robot = self.robot
scene = self.scene
eef_link = self.eef_link
group_names = self.group_names
## BEGIN_SUB_TUTORIAL attach_object
##
## Attaching Objects to the Robot
## ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
## Next, we will attach the box to the Panda wrist. Manipulating objects requires the
## robot be able to touch them without the planning scene reporting the contact as a
## collision. By adding link names to the ``touch_links`` array, we are telling the
## planning scene to ignore collisions between those links and the box. For the Panda
## robot, we set ``grasping_group = 'hand'``. If you are using a different robot,
## you should change this value to the name of your end effector group name.
grasping_group = "hand"
touch_links = robot.get_link_names(group=grasping_group)
scene.attach_box(eef_link, box_name, touch_links=touch_links)
## END_SUB_TUTORIAL
# We wait for the planning scene to update.
return self.wait_for_state_update(
box_is_attached=True, box_is_known=False, timeout=timeout
)
def detach_box(self, timeout=4):
# Copy class variables to local variables to make the web tutorials more clear.
# In practice, you should use the class variables directly unless you have a good
# reason not to.
box_name = self.box_name
scene = self.scene
eef_link = self.eef_link
## BEGIN_SUB_TUTORIAL detach_object
##
## Detaching Objects from the Robot
## ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
## We can also detach and remove the object from the planning scene:
scene.remove_attached_object(eef_link, name=box_name)
## END_SUB_TUTORIAL
# We wait for the planning scene to update.
return self.wait_for_state_update(
box_is_known=True, box_is_attached=False, timeout=timeout
)
def remove_box(self, timeout=4):
# Copy class variables to local variables to make the web tutorials more clear.
# In practice, you should use the class variables directly unless you have a good
# reason not to.
box_name = self.box_name
scene = self.scene
## BEGIN_SUB_TUTORIAL remove_object
##
## Removing Objects from the Planning Scene
## ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
## We can remove the box from the world.
scene.remove_world_object(box_name)
## **Note:** The object must be detached before we can remove it from the world
## END_SUB_TUTORIAL
# We wait for the planning scene to update.
return self.wait_for_state_update(
box_is_attached=False, box_is_known=False, timeout=timeout
)
def main():
try:
print("")
print("----------------------------------------------------------")
print("Welcome to the MoveIt MoveGroup Python Interface Tutorial")
print("----------------------------------------------------------")
print("Press Ctrl-D to exit at any time")
print("")
input(
"============ Press `Enter` to begin the tutorial by setting up the moveit_commander ..."
)
tutorial = MoveGroupPythonInterfaceTutorial()
input(
"============ Press `Enter` to execute a movement using a joint state goal ..."
)
tutorial.go_to_joint_state()
input("============ Press `Enter` to execute a movement using a pose goal ...")
tutorial.go_to_pose_goal()
input("============ Press `Enter` to plan and display a Cartesian path ...")
cartesian_plan, fraction = tutorial.plan_cartesian_path()
input(
"============ Press `Enter` to display a saved trajectory (this will replay the Cartesian path) ..."
)
tutorial.display_trajectory(cartesian_plan)
input("============ Press `Enter` to execute a saved path ...")
tutorial.execute_plan(cartesian_plan)
input("============ Press `Enter` to add a box to the planning scene ...")
tutorial.add_box()
input("============ Press `Enter` to attach a Box to the Panda robot ...")
tutorial.attach_box()
input(
"============ Press `Enter` to plan and execute a path with an attached collision object ..."
)
cartesian_plan, fraction = tutorial.plan_cartesian_path(scale=-1)
tutorial.execute_plan(cartesian_plan)
input("============ Press `Enter` to detach the box from the Panda robot ...")
tutorial.detach_box()
input(
"============ Press `Enter` to remove the box from the planning scene ..."
)
tutorial.remove_box()
print("============ Python tutorial demo complete!")
except rospy.ROSInterruptException:
return
except KeyboardInterrupt:
return
if __name__ == "__main__":
main()반응형