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_themes/sphinx_rtd_theme/layout.html

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<div class="wy-nav-content">
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<div class="header-override">
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<p>
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<a href="http://moveit.ros.org">MoveIt! Website</a><br/>
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<a href="http://moveit.ros.org">MoveIt Website</a><br/>
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</p>
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</div>
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<div class="rst-content">

doc/benchmarking/benchmarking_tutorial.rst

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Example
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-------
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An example is provided in the ``examples`` folder. The launch file requires a MoveIt! configuration package
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An example is provided in the ``examples`` folder. The launch file requires a MoveIt configuration package
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for the Panda robot arm available from `here <https://github.com/ros-planning/panda_moveit_config>`_.
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To run:

doc/chomp_planner/chomp_planner_tutorial.rst

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.. image:: chomp.png
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:width: 700px
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Covariant Hamiltonian optimization for motion planning (CHOMP) is a gradient-based trajectory optimization procedure that makes many everyday motion planning problems both simple and trainable (Ratliff et al., 2009c). While most high-dimensional motion planners separate trajectory generation into distinct planning and optimization stages, this algorithm capitalizes on covariant gradient and functional gradient approaches to the optimization stage to design a motion planning algorithm based entirely on trajectory optimization. Given an infeasible naive trajectory, CHOMP reacts to the surrounding environment to quickly pull the trajectory out of collision while simultaneously optimizing dynamical quantities such as joint velocities and accelerations. It rapidly converges to a smooth collision-free trajectory that can be executed efficiently on the robot. Integration into latest version of MoveIt! is `work in progress <https://github.com/ros-planning/moveit/issues/702>`_. `More info <http://www.nathanratliff.com/thesis-research/chomp>`_
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Covariant Hamiltonian optimization for motion planning (CHOMP) is a gradient-based trajectory optimization procedure that makes many everyday motion planning problems both simple and trainable (Ratliff et al., 2009c). While most high-dimensional motion planners separate trajectory generation into distinct planning and optimization stages, this algorithm capitalizes on covariant gradient and functional gradient approaches to the optimization stage to design a motion planning algorithm based entirely on trajectory optimization. Given an infeasible naive trajectory, CHOMP reacts to the surrounding environment to quickly pull the trajectory out of collision while simultaneously optimizing dynamical quantities such as joint velocities and accelerations. It rapidly converges to a smooth collision-free trajectory that can be executed efficiently on the robot. Integration into latest version of MoveIt is `work in progress <https://github.com/ros-planning/moveit/issues/702>`_. `More info <http://www.nathanratliff.com/thesis-research/chomp>`_
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Getting Started
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---------------
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If you haven't already done so, make sure you've completed the steps in `Getting Started <../getting_started/getting_started.html>`_.
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You should also have gone through the steps in `Visualization with MoveIt! RViz Plugin <../quickstart_in_rviz/quickstart_in_rviz_tutorial.html>`_
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You should also have gone through the steps in `Visualization with MoveIt RViz Plugin <../quickstart_in_rviz/quickstart_in_rviz_tutorial.html>`_
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Prerequisites
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--------------
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#. On ROS Melodic you do not need to build MoveIt! from source, but for older versions of MoveIt! you do (see previous tutorial versions).
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#. To use CHOMP with your robot you must already have a MoveIt! configuration package for your robot already. For example, if you have a Panda robot, it's called ``panda_moveit_config``. This is typically configured using the `MoveIt! Setup Assistant <../setup_assistant/setup_assistant_tutorial.html>`_.
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#. On ROS Melodic you do not need to build MoveIt from source, but for older versions of MoveIt you do (see previous tutorial versions).
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#. To use CHOMP with your robot you must already have a MoveIt configuration package for your robot already. For example, if you have a Panda robot, it's called ``panda_moveit_config``. This is typically configured using the `MoveIt Setup Assistant <../setup_assistant/setup_assistant_tutorial.html>`_.
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Using CHOMP with Your Robot
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---------------------------
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**Note:** if you are following this demo using the ``panda_moveit_config`` from the `ros-planning/panda_moveit_config <https://github.com/ros-planning/panda_moveit_config>`_ repository, these steps are already done for you and you can skip this section.
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#. Simply download :panda_codedir:`chomp_planning_pipeline.launch.xml<launch/chomp_planning_pipeline.launch.xml>` file into the launch directory of your MoveIt! config package. In our case, we will save this file in the ``panda_moveit_config/launch`` directory.
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#. Adjust the line ``<rosparam command="load" file="$(find panda_moveit_config)/config/chomp_planning.yaml" />`` to ``<rosparam command="load" file="$(find <robot_moveit_config>)/config/chomp_planning.yaml" />`` replacing ``<robot_moveit_config>`` with the name of your MoveIt! configuration package.
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#. Download :panda_codedir:`chomp_planning.yaml <config/chomp_planning.yaml>` file into the config directory of your MoveIt! config package. In our case, we will save this file in the ``panda_moveit_config/config`` directory.
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#. Simply download :panda_codedir:`chomp_planning_pipeline.launch.xml<launch/chomp_planning_pipeline.launch.xml>` file into the launch directory of your MoveIt config package. In our case, we will save this file in the ``panda_moveit_config/launch`` directory.
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#. Adjust the line ``<rosparam command="load" file="$(find panda_moveit_config)/config/chomp_planning.yaml" />`` to ``<rosparam command="load" file="$(find <robot_moveit_config>)/config/chomp_planning.yaml" />`` replacing ``<robot_moveit_config>`` with the name of your MoveIt configuration package.
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#. Download :panda_codedir:`chomp_planning.yaml <config/chomp_planning.yaml>` file into the config directory of your MoveIt config package. In our case, we will save this file in the ``panda_moveit_config/config`` directory.
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#. Open ``chomp_planning.yaml`` in your favorite editor and change ``animate_endeffector_segment: "panda_rightfinger"`` to the appropriate link for your robot.
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#. Copy the ``demo.launch`` file to ``demo_chomp.launch``. Note that this file is also in the launch directory of your MoveIt! config package. In our case, the ``panda_moveit_config/launch`` directory.
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#. Copy the ``demo.launch`` file to ``demo_chomp.launch``. Note that this file is also in the launch directory of your MoveIt config package. In our case, the ``panda_moveit_config/launch`` directory.
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#. Find the lines where ``move_group.launch`` is included and change it to: ::
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<!-- Replace <robot_moveit_config> with the name of your MoveIt! configuration package -->
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<!-- Replace <robot_moveit_config> with the name of your MoveIt configuration package -->
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<include file="$(find <robot_moveit_config>)/launch/move_group.launch">
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<arg name="allow_trajectory_execution" value="true"/>
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<arg name="fake_execution" value="true"/>
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---------------------------------------------------
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Optimizing planners optimize a cost function that may sometimes lead to surprising results: moving through a thin obstacle might be lower cost than a long, winding trajectory that avoids all collisions. In this section we make a distinction between paths obtained from CHOMP and contrast it to those obtained from OMPL.
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OMPL is a open source library for sampling based / randomized motion planning algorithms. Sampling based algorithms are probabilistically complete: a solution would be eventually found if one exists, however non-existence of a solution cannot be reported. These algorithms are efficient and usually find a solution quickly. OMPL does not contain any code related to collision checking or visualization as the designers of OMPL did not want to tie it to a any particular collision checker or visualization front end. The library is designed so it can be easily integrated into systems that provide the additional components. MoveIt! integrates directly with OMPL and uses the motion planners from OMPL as its default set of planners. The planners in OMPL are abstract; i.e. OMPL has no concept of a robot. Instead, MoveIt! configures OMPL and provides the back-end for OMPL to work with problems in Robotics.
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OMPL is a open source library for sampling based / randomized motion planning algorithms. Sampling based algorithms are probabilistically complete: a solution would be eventually found if one exists, however non-existence of a solution cannot be reported. These algorithms are efficient and usually find a solution quickly. OMPL does not contain any code related to collision checking or visualization as the designers of OMPL did not want to tie it to a any particular collision checker or visualization front end. The library is designed so it can be easily integrated into systems that provide the additional components. MoveIt integrates directly with OMPL and uses the motion planners from OMPL as its default set of planners. The planners in OMPL are abstract; i.e. OMPL has no concept of a robot. Instead, MoveIt configures OMPL and provides the back-end for OMPL to work with problems in Robotics.
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CHOMP: While most high-dimensional motion planners separate trajectory generation into distinct planning and optimization stages, CHOMP capitalizes on covariant gradient and functional gradient approaches to the optimization stage to design a motion planning algorithm based entirely on trajectory optimization. Given an infeasible naive trajectory, CHOMP reacts to the surrounding environment to quickly pull the trajectory out of collision while simultaneously optimizing dynamical quantities such as joint velocities and accelerations. It rapidly converges to a smooth collision-free trajectory that can be executed efficiently on the robot. A covariant update rule ensures that CHOMP quickly converges to a locally optimal trajectory.
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doc/controller_configuration/controller_configuration_tutorial.rst

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Low Level Controllers
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=====================
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In this section, we will walk through configuring MoveIt! with the controllers on your robot. We will assume that your robot offers a ``FollowJointTrajectory`` action service for the arms on your robot and (optionally) a ``GripperCommand`` service for your gripper. If your robot does not offer this we recommend the `ROS control <http://wiki.ros.org/ros_control>`_ framework for easily adding this functionality around your hardware communication layer.
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In this section, we will walk through configuring MoveIt with the controllers on your robot. We will assume that your robot offers a ``FollowJointTrajectory`` action service for the arms on your robot and (optionally) a ``GripperCommand`` service for your gripper. If your robot does not offer this we recommend the `ROS control <http://wiki.ros.org/ros_control>`_ framework for easily adding this functionality around your hardware communication layer.
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YAML Configuration
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------------------
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The first file to create is a YAML configuration file (call it ``controllers.yaml`` and place it in the ``robot_moveit_config/config`` directory of your MoveIt! robot config package). This will specify the controller configuration for your robot. Here's an example file for configuring a ``FollowJointTrajectory`` action controller for the ``panda_arm`` and a ``GripperCommand`` gripper controller for its ``hand``: ::
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The first file to create is a YAML configuration file (call it ``controllers.yaml`` and place it in the ``robot_moveit_config/config`` directory of your MoveIt robot config package). This will specify the controller configuration for your robot. Here's an example file for configuring a ``FollowJointTrajectory`` action controller for the ``panda_arm`` and a ``GripperCommand`` gripper controller for its ``hand``: ::
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controller_list:
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* *name*: The name of the controller. (See debugging information below for important notes).
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* *type*: The type of action being used (here FollowJointTrajectory).
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* *default*: The default controller is the primary controller chosen by MoveIt! for communicating with a particular set of joints.
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* *default*: The default controller is the primary controller chosen by MoveIt for communicating with a particular set of joints.
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* *default*: The default controller is the primary controller chosen by MoveIt for communicating with a particular set of joints.
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Now, create the controller launch file (call it ``robot_moveit_controller_manager.launch.xml`` where ``robot`` is the name of your robot as specified when you created your MoveIt! robot config package).
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Now, create the controller launch file (call it ``robot_moveit_controller_manager.launch.xml`` where ``robot`` is the name of your robot as specified when you created your MoveIt robot config package).
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MAKE SURE to replace ``robot_moveit_config`` with the correct name of your MoveIt robot config package.
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Now, you should be ready to have MoveIt talk to your robot.
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When you run a `move group node <../move_group_interface/move_group_interface_tutorial.html>`_, you may need to remap the topic /joint_states to /robot/joint_states, otherwise MoveIt won't have feedback from the joints. To do this remapping you could make a simple launch file for your node as follows: ::
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There are several options for tuning the behavior and safety checks of the execution pipeline in MoveIt!. In your ``moveit_config`` package edit the ``trajectory_execution.launch.xml`` file to change the following parameters:
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There are several options for tuning the behavior and safety checks of the execution pipeline in MoveIt. In your ``moveit_config`` package edit the ``trajectory_execution.launch.xml`` file to change the following parameters:
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doc/custom_constraint_samplers/custom_constraint_samplers_tutorial.rst

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Some planning problems require more complex or custom constraint
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samplers for more difficult planning problems. This document explains
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with MoveIt.
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doc/fake_controller_manager/fake_controller_manager_tutorial.rst

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Fake Controller Manager
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=================================
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MoveIt! comes with a series of fake trajectory controllers to be used in simulation.
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MoveIt comes with a series of fake trajectory controllers to be used in simulation.
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For example, the ``demo.launch`` generated by MoveIt's setup assistant, employs fake controllers for nice visualization in RViz.
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doc/getting_started/getting_started.rst

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The simplest way to install MoveIt is from pre-built binaries (Debian): ::
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Advanced users might want to `install MoveIt from source <http://moveit.ros.org/install/source/>`_.
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.. note:: For now we will use a pre-generated ``panda_moveit_config`` package but later we will learn how to make our own in the `MoveIt Setup Assistant tutorial <../setup_assistant/setup_assistant_tutorial.html>`_.
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^^^^^^^^^^^^^^^^^^^^^^^^^^^

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