Merge branch 'ros-planning:main' into main

.github/workflows/deploy.yml

@@ -146,7 +146,7 @@ jobs:
         cp -f api.html build/html/main/doc/api/python_api/ # restore artifact html
 
     - name: Upload pages artifact
-      uses: actions/upload-pages-artifact@v2
+      uses: actions/upload-pages-artifact@v3
       if: github.repository_owner == 'ros-planning'
       with:
         path: build/html
@@ -161,4 +161,4 @@ jobs:
     steps:
       - name: Deploy to GitHub Pages
         id: deployment
-        uses: actions/deploy-pages@v3
+        uses: actions/deploy-pages@v4

.pre-commit-config.yaml

@@ -34,6 +34,12 @@ repos:
 
   - repo: local
     hooks:
+      - id: misspelled-moveit
+        name: misspelled-moveit
+        description: MoveIt should be spelled exactly as MoveIt
+        language: pygrep
+        entry: Moveit\W|MoveIt!|Moveit2|MoveIt2
+        exclude: .pre-commit-config.yaml
       - id: clang-format
         name: clang-format
         description: Format files with ClangFormat.

CMakeLists.txt

@@ -38,7 +38,7 @@ endforeach()
 include_directories(${THIS_PACKAGE_INCLUDE_DIRS})
 
 # add_subdirectory(doc/examples/bullet_collision_checker)
-# add_subdirectory(doc/examples/collision_environments)
+add_subdirectory(doc/examples/collision_environments)
 # add_subdirectory(doc/examples/controller_configuration)
 # add_subdirectory(doc/examples/creating_moveit_plugins/lerp_motion_planner)
 # add_subdirectory(doc/examples/interactivity)

doc/examples/controller_configuration/controller_configuration_tutorial.rst

@@ -6,7 +6,7 @@ MoveIt typically publishes manipulator motion commands to a `JointTrajectoryCont
 
 #. A launch file. This launch file must load the :code:`moveit_controllers` yaml file and specify the :code:`moveit_simple_controller_manager/MoveItSimpleControllerManager`. After these yaml files are loaded, they are passed as parameters to the Move Group node. `Example Move Group launch file <https://github.com/ros-planning/moveit_resources/blob/ros2/panda_moveit_config/launch/demo.launch.py>`_.
 
-#. Launch the corresponding :code:`ros2_control` JointTrajectoryControllers. This is separate from the MoveIt2 ecosystem. `Example ros2_control launching <https://github.com/ros-controls/ros2_control_demos>`_. Each JointTrajectoryController provides an action interface. Given the yaml file above, MoveIt automatically connects to this action interface.
+#. Launch the corresponding :code:`ros2_control` JointTrajectoryControllers. This is separate from the MoveIt 2 ecosystem. `Example ros2_control launching <https://github.com/ros-controls/ros2_control_demos>`_. Each JointTrajectoryController provides an action interface. Given the yaml file above, MoveIt automatically connects to this action interface.
 
 #. Note: it is not required to use :code:`ros2_control` for your robot. You could write a proprietary action interface. In practice, 99% of users choose :code:`ros2_control`.
 

doc/examples/creating_moveit_plugins/lerp_motion_planner/src/lerp_example.cpp

@@ -40,7 +40,7 @@
 
 #include <pluginlib/class_loader.h>
 
-// MoveIt!
+// MoveIt
 #include <moveit/robot_model_loader/robot_model_loader.h>
 #include <moveit/planning_interface/planning_interface.h>
 #include <moveit/planning_scene/planning_scene.h>

doc/examples/dual_arms/dual_arms_tutorial.rst

@@ -3,7 +3,7 @@ Dual Arms with MoveIt
 
 There are quite a few configuration steps to control two or more manipulators with MoveIt. Luckily it has gotten easier over time. Here, an example is provided and we list all the changes needed to go from 1 robot to X robots.
 
-The launch and configuration files in this example are available :codedir:`here. <examples/dual_arms>`
+The launch and configuration files in this example are available :moveit_resources_codedir:`here. <dual_arm_panda_moveit_config>`
 
 Running the Demo
 ----------------

doc/examples/hybrid_planning/hybrid_planning_tutorial.rst

@@ -1,7 +1,7 @@
 Hybrid Planning
 ===============
 
-In this section, you will learn how to use  Moveit 2's *Hybrid Planning* feature.
+In this section, you will learn how to use MoveIt 2's *Hybrid Planning* feature.
 
 Hybrid Planning enables you to (re)plan and execute robot motions online with MoveIt 2 and to add more planning logic into your robot's motion planning pipeline.
 
@@ -90,7 +90,7 @@ To include the Hybrid Planning Architecture into you project you need to add a *
 
 Customizing the Hybrid Planning Architecture
 --------------------------------------------
-As the rest of Moveit 2, the *Hybrid Planning Architecture* is designed to be highly customizable while also offering the possibility to easily re-use existing solutions. Each of the architecture's components is a ROS 2 node and can be completely replaced by your own custom ROS 2 node as long as it offers the API required by the other nodes. Each component's runtime behavior is defined by plugins. This section focuses on the customization of the *Hybrid Planning Architecture* by implementing your own plugins.
+As the rest of MoveIt 2, the *Hybrid Planning Architecture* is designed to be highly customizable while also offering the possibility to easily re-use existing solutions. Each of the architecture's components is a ROS 2 node and can be completely replaced by your own custom ROS 2 node as long as it offers the API required by the other nodes. Each component's runtime behavior is defined by plugins. This section focuses on the customization of the *Hybrid Planning Architecture* by implementing your own plugins.
 
 Global and Local Motion Planning
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

doc/examples/jupyter_notebook_prototyping/jupyter_notebook_prototyping_tutorial.rst

@@ -16,7 +16,7 @@ The code for this tutorial can be found `here <https://github.com/peterdavidfaga
 
 Getting Started
 ---------------
-To complete this tutorial, you must have set up a colcon workspace that includes MoveIt2 and its corresponding tutorials. An excellent outline on how to set up such a workspace is provided in the :doc:`Getting Started Guide </doc/tutorials/getting_started/getting_started>`.
+To complete this tutorial, you must have set up a colcon workspace that includes MoveIt 2 and its corresponding tutorials. An excellent outline on how to set up such a workspace is provided in the :doc:`Getting Started Guide </doc/tutorials/getting_started/getting_started>`.
 
 Once you have set up your workspace, you can execute the code for this tutorial by running the following command (the servo section of this tutorial requires a PS4 Dualshock, if you don't have one consider setting this parameter to false): ::
 
@@ -140,7 +140,10 @@ Once our MoveIt configuration is defined we start the following set of nodes:
         ros2_control_node = Node(
                 package="controller_manager",
                 executable="ros2_control_node",
-                parameters=[moveit_config.robot_description, ros2_controllers_path],
+                parameters=[ros2_controllers_path],
+                remappings=[
+                        ("/controller_manager/robot_description", "/robot_description"),
+                ],
                 output="both",
         )
 

doc/examples/jupyter_notebook_prototyping/launch/jupyter_notebook_prototyping.launch.py

@@ -88,7 +88,10 @@ def generate_launch_description():
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="both",
     )
 

doc/examples/jupyter_notebook_prototyping/src/moveit_notebook_tutorial.ipynb

@@ -7,7 +7,7 @@
    "source": [
     "# Introduction\n",
     "\n",
-    "Welcome to this tutorial on using jupyter notebooks with Moveit 2. A great benefit of being able to interact with MoveIt via a Python notebook is the ability to rapidly prototype code. We hope you find this interface intuitive and that you gain value from using MoveIt via Python notebooks.\n",
+    "Welcome to this tutorial on using jupyter notebooks with MoveIt 2. A great benefit of being able to interact with MoveIt via a Python notebook is the ability to rapidly prototype code. We hope you find this interface intuitive and that you gain value from using MoveIt via Python notebooks.\n",
     "\n",
     "In this tutorial we will cover the following: \n",
     "\n",

doc/examples/motion_planning_python_api/launch/motion_planning_python_api_tutorial.launch.py

@@ -80,7 +80,10 @@ def generate_launch_description():
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="log",
     )
 

doc/examples/move_group_interface/launch/move_group.launch.py

@@ -67,7 +67,10 @@ def generate_launch_description():
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="both",
     )
 

doc/examples/moveit_cpp/launch/moveit_cpp_tutorial.launch.py

@@ -71,7 +71,10 @@ def generate_launch_description():
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="both",
     )
 

doc/examples/realtime_servo/launch/pose_tracking_tutorial.launch.py

@@ -56,7 +56,10 @@ def generate_launch_description():
     ros2_control_node = launch_ros.actions.Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="screen",
     )
 

doc/examples/realtime_servo/realtime_servo_tutorial.rst

@@ -27,7 +27,7 @@ If you haven't already done so, make sure you've completed the steps in :doc:`Ge
 Design overview
 ---------------
 
-Moveit Servo consists of two main parts: The core implementation ``Servo`` which provides a C++ interface, and the ``ServoNode`` which
+MoveIt Servo consists of two main parts: The core implementation ``Servo`` which provides a C++ interface, and the ``ServoNode`` which
 wraps the C++ interface and provides a ROS interface.The configuration of Servo is done through ROS parameters specified in :moveit_codedir:`servo_parameters.yaml <moveit_ros/moveit_servo/config/servo_parameters.yaml>`
 
 In addition to the servoing capability, MoveIt Servo has some convenient features such as:

doc/examples/time_parameterization/time_parameterization_tutorial.rst

@@ -20,7 +20,7 @@ MoveIt can support different algorithms for post-processing a kinematic trajecto
 
 * :moveit_codedir:`Time-optimal Trajectory Generation<moveit_core/trajectory_processing/src/time_optimal_trajectory_generation.cpp>`
 
-Time-optimal Trajectory Generation (TOTG) was introduced in PRs `#809 <https://github.com/ros-planning/moveit/pull/809>`_ and `#1365 <https://github.com/ros-planning/moveit/pull/1365>`_. It produces trajectories with very smooth and continuous velocity profiles. The method is based on fitting path segments to the original trajectory and then sampling new waypoints from the optimized path. This is different from strict time parameterization methods as resulting waypoints may divert from the original trajectory within a certain tolerance. As a consequence, additional collision checks might be required when using this method. It is the default everywhere in MoveIt2.
+Time-optimal Trajectory Generation (TOTG) was introduced in PRs `#809 <https://github.com/ros-planning/moveit/pull/809>`_ and `#1365 <https://github.com/ros-planning/moveit/pull/1365>`_. It produces trajectories with very smooth and continuous velocity profiles. The method is based on fitting path segments to the original trajectory and then sampling new waypoints from the optimized path. This is different from strict time parameterization methods as resulting waypoints may divert from the original trajectory within a certain tolerance. As a consequence, additional collision checks might be required when using this method. It is the default everywhere in MoveIt 2.
 
 Usage of a time parameterization algorithm as a Planning Request Adapter is documented in `this tutorial <../motion_planning_pipeline/motion_planning_pipeline_tutorial.html#using-a-planning-request-adapter>`_.
 

doc/how_to_guides/chomp_planner/launch/chomp_demo.launch.py

@@ -100,7 +100,10 @@ def generate_launch_description():
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="screen",
     )
 

doc/how_to_guides/controller_teleoperation/controller_teleoperation.rst

@@ -21,7 +21,7 @@ Requirements
 Steps
 -----
 
-1. Build the MoveIt2 workspace
+1. Build the MoveIt 2 workspace
 
   First, ``cd`` to the root directory of the moveit2 workspace. (if you followed the :doc:`Getting Started </doc/tutorials/getting_started/getting_started>` tutorial, this will be ``~/ws_moveit/``).
 

doc/how_to_guides/isaac_panda/.docker/ros_entrypoint.sh

@@ -1,6 +1,6 @@
 #!/bin/bash
 
-# Source ROS and the MoveIt2 workspace
+# Source ROS and the MoveIt 2 workspace
 source /opt/ros/humble/setup.bash
 source /root/ws_moveit/install/setup.bash
 echo "Sourced ROS & MoveIt Humble"

doc/how_to_guides/isaac_panda/isaac_panda_tutorial.rst

@@ -1,12 +1,13 @@
 How To Command Simulated Isaac Robot
 ====================================
 
-This tutorial requires a machine with ``Isaac Sim 2022.2.0`` or ``Isaac Sim 2022.2.1`` installed.
+This tutorial requires a machine with ``Isaac Sim 2023.1.x`` (recommended) or ``Isaac Sim 2022.2.x`` installed.
 For Isaac Sim requirements and installation please see the `Omniverse documentation <https://docs.omniverse.nvidia.com/isaacsim/latest/index.html>`_.
+To configure Isaac Sim to work with ROS 2 please see `this guide <https://docs.omniverse.nvidia.com/isaacsim/latest/installation/install_ros.html#running-native-ros>`_.
 
 This tutorial has the following assumptions on system configuration:
 
-1. NVIDIA Isaac Sim 2022.2.0 or 2022.2.1 is installed on a Ubuntu 20.04 host in the default location.
+1. NVIDIA Isaac Sim is installed in the default location. Docker based installations of Isaac sim are also supported but it is up to the user to configure the system.
 2. Docker is installed.
    If you plan to use your GPU with MoveIt, you will need to install `nvidia-docker <https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#installing-on-ubuntu-and-debian>`_.
 3. You clone this repo so that you can build a Ubuntu 22.04 Humble based Docker image that can communicate with Isaac and run this tutorial.
@@ -70,7 +71,7 @@ Computer Setup
 
 1. Install `Isaac Sim <https://docs.omniverse.nvidia.com/isaacsim/latest/installation/install_workstation.html>`_.
 
-2. Perform a shallow clone of the MoveIt2 Tutorials repo.
+2. Perform a shallow clone of the MoveIt 2 Tutorials repo.
 
 .. code-block:: bash
 
@@ -118,7 +119,7 @@ Running the MoveIt Interactive Marker Demo with Isaac Sim
 
 2. Then run the following command to load the Panda Robot pre-configured to work with this tutorial.
 
-.. note:: This step assumes Isaac Sim version 2022.2.0 or 2022.2.1 is installed on the host in the ``$HOME/.local/share/ov/pkg/" directory``.
+.. note:: This step assumes that a compatible version of Isaac Sim is installed on the host in the ``$HOME/.local/share/ov/pkg/" directory``.
   This step also takes a few minutes to download the assets and setup Isaac Sim so please be
   patient and don't click the ``Force Quit`` dialog that pops up while the simulator starts.
 

doc/how_to_guides/isaac_panda/launch/isaac_demo.launch.py

@@ -108,7 +108,10 @@ def generate_launch_description():
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="screen",
     )
 

doc/how_to_guides/isaac_panda/launch/python.sh

@@ -13,7 +13,7 @@ ISAAC_SCRIPT_DIRS=()
 for ISAAC_SCRIPT_DIR in $(ls -d -- $OV_PKG_DIR/isaac_sim-*);
 do
     ISAAC_VER=${ISAAC_SCRIPT_DIR//$OV_PKG_DIR\/isaac_sim-/};
-    if [[ "$ISAAC_VER" =~ ^(2022.2.0|2022.2.1)$ ]]; then
+    if [[ "$ISAAC_VER" =~ ^(2022.2.0|2022.2.1|2023.1.0|2023.1.1)$ ]]; then
         ISAAC_SCRIPT_DIRS+=($ISAAC_SCRIPT_DIR)
     fi
 done

doc/how_to_guides/kinematics_cost_function/src/kinematics_cost_function_tutorial.cpp

@@ -217,7 +217,7 @@ int main(int argc, char** argv)
   std::vector<moveit::core::RobotStatePtr> traj;
   moveit::core::MaxEEFStep max_eef_step(0.01, 0.1);
   // Here, we're effectively disabling the jump threshold for joints. This is not recommended on real hardware.
-  moveit::core::JumpThreshold jump_thresh(0.0);
+  const auto jump_thresh = moveit::core::JumpThreshold::disabled();
 
   // The trajectory, traj, passed to computeCartesianPath will contain several waypoints toward
   // the goal pose, target. For each of these waypoints, the IK solver is queried with the given cost function.

doc/how_to_guides/moveit_launch_files/moveit_launch_files_tutorial.rst

@@ -158,7 +158,10 @@ In our example, we have:
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="both",
     )
 

doc/how_to_guides/parallel_planning/launch/parallel_planning_example.launch.py

@@ -157,7 +157,10 @@ def launch_setup(context, *args, **kwargs):
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="both",
     )
 

doc/how_to_guides/persistent_scenes_and_states/launch/persistent_scenes_demo.launch.py

@@ -101,7 +101,10 @@ def generate_launch_description():
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="both",
     )
 

doc/how_to_guides/pick_ik/launch/demo_pick_ik.launch.py

@@ -104,7 +104,10 @@ def launch_setup(context, *args, **kwargs):
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="both",
     )
 

doc/how_to_guides/using_ompl_constrained_planning/launch/ompl_constrained_planning.launch.py

@@ -93,7 +93,10 @@ def generate_launch_description():
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.robot_description, ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="both",
     )
 

doc/tutorials/getting_started/getting_started.rst

@@ -89,7 +89,7 @@ This build command will likely take a long time (20+ minutes) depending on your
 .. warning::
   Some of the packages built with this command require up to 16Gb of RAM to build. By default, ``colcon``  tries to build as many packages as possible at the same time.
   If you are low on computer memory, or if the build is generally having trouble completing on your computer,
-  you can try appending ``--executor sequential`` to the ``colcon`` command above to build only one package at a time, or ``-parallel-workers <X>`` to limit the number of simultaneous builds.
+  you can try appending ``--executor sequential`` to the ``colcon`` command above to build only one package at a time, or ``--parallel-workers <X>`` to limit the number of simultaneous builds.
 
 If everything goes well, you should see the message "Summary: X packages finished" where X might be 50. If you have problems, try re-checking your `ROS Installation <https://docs.ros.org/en/rolling/Installation.html>`_.
 

doc/tutorials/pick_and_place_with_moveit_task_constructor/launch/mtc_demo.launch.py

@@ -80,7 +80,10 @@ def generate_launch_description():
     ros2_control_node = Node(
         package="controller_manager",
         executable="ros2_control_node",
-        parameters=[moveit_config.to_dict(), ros2_controllers_path],
+        parameters=[ros2_controllers_path],
+        remappings=[
+            ("/controller_manager/robot_description", "/robot_description"),
+        ],
         output="both",
     )