From b245cff48c69c8f473f4d5dd6ce7a90c712a7fb0 Mon Sep 17 00:00:00 2001 From: laco Date: Fri, 3 May 2024 08:22:41 +0200 Subject: [PATCH] Update CNAME and internal links --- CNAME | 2 +- ...2014-01-07-a-new-year-a-new-website-a-new-movie.markdown | 2 +- _posts/2018-10-25-GSOC-Perception-Pipeline.markdown | 6 +++--- _posts/2018-10-25-gsoc-motion-planning-support.markdown | 2 +- _posts/2020-02-25-mtc.md | 4 ++-- _posts/2020-06-09-moveit2-robotic-application.md | 2 +- _posts/2020-08-04-moveit-melodic-release.md | 4 ++-- _posts/2020-09-10-ompl-constrained-planning-gsoc.md | 6 +++--- _posts/2020-09-28-grasp-deep-learning.md | 2 +- _posts/2020-11-18-bullet-collision.md | 2 +- _posts/2020-12-17-Pilz-Plugin-for-MoveIt.md | 2 +- about/distribution/index.markdown | 2 +- documentation/concepts/index.markdown | 2 +- documentation/contributing/future_projects/index.markdown | 2 +- install/docker/index.markdown | 2 +- install/index.markdown | 4 ++-- install/source/index.markdown | 2 +- 17 files changed, 24 insertions(+), 24 deletions(-) diff --git a/CNAME b/CNAME index b75d41b94..e74ef76c5 100644 --- a/CNAME +++ b/CNAME @@ -1 +1 @@ -moveit.ros.org +moveit.ai diff --git a/_posts/2014-01-07-a-new-year-a-new-website-a-new-movie.markdown b/_posts/2014-01-07-a-new-year-a-new-website-a-new-movie.markdown index fa4adfc02..00cf04307 100644 --- a/_posts/2014-01-07-a-new-year-a-new-website-a-new-movie.markdown +++ b/_posts/2014-01-07-a-new-year-a-new-website-a-new-movie.markdown @@ -40,7 +40,7 @@ We have listened to your feedback and added: * [New documentation](/) - * [New tutorials](https://ros-planning.github.io/moveit_tutorials/) - Sphinx-based tutorials living next to the code so they are easier to maintain + * [New tutorials](https://moveit.github.io/moveit_tutorials/) - Sphinx-based tutorials living next to the code so they are easier to maintain * [Robots using MoveIt!](/robots/) page diff --git a/_posts/2018-10-25-GSOC-Perception-Pipeline.markdown b/_posts/2018-10-25-GSOC-Perception-Pipeline.markdown index 77326219c..806e79396 100644 --- a/_posts/2018-10-25-GSOC-Perception-Pipeline.markdown +++ b/_posts/2018-10-25-GSOC-Perception-Pipeline.markdown @@ -17,11 +17,11 @@ Submitted by: Ridhwan Luthra, Cluster Innovation Centre Over the summer, Open Source Robotics Foundation (OSRF) and PickNik Robotics teamed up to mentor a Google Summer of Code (GSoC) student, Ridhwan Luthra, while he made meaningful contributions to MoveIt!. Ridhwan worked with Michael ‘v4hn’ Görner and Michael Lautman to produce two new tutorials demonstrating the perception and manipulation capabilities available in MoveIt!. -Ridhwan’s work focused on developing tutorials for [Perception Pipeline with Octomaps](https://ros-planning.github.io/moveit_tutorials/doc/perception_pipeline/perception_pipeline_tutorial.html) as well as the [Pick and Place Pipeline](https://ros-planning.github.io/moveit_tutorials/doc/pick_place/pick_place_tutorial.html). Ridhwan also made significant progress towards generalizing a grasp generation package to incorporate into a grasping tutorial. This work is still continuing outside the scope of GSOC. +Ridhwan’s work focused on developing tutorials for [Perception Pipeline with Octomaps](https://moveit.github.io/moveit_tutorials/doc/perception_pipeline/perception_pipeline_tutorial.html) as well as the [Pick and Place Pipeline](https://moveit.github.io/moveit_tutorials/doc/pick_place/pick_place_tutorial.html). Ridhwan also made significant progress towards generalizing a grasp generation package to incorporate into a grasping tutorial. This work is still continuing outside the scope of GSOC. ### Perception Pipeline with Octomaps -While developing the [perception pipeline tutorial](https://ros-planning.github.io/moveit_tutorials/doc/perception_pipeline/perception_pipeline_tutorial.html), Ridhwan identified and fixed a common race condition that was triggered by the way that MoveIt! was maintaining and updating octomaps. This was accomplished by adding a parameter that allows users to configure the maximum rate at which the octomap is updated. +While developing the [perception pipeline tutorial](https://moveit.github.io/moveit_tutorials/doc/perception_pipeline/perception_pipeline_tutorial.html), Ridhwan identified and fixed a common race condition that was triggered by the way that MoveIt! was maintaining and updating octomaps. This was accomplished by adding a parameter that allows users to configure the maximum rate at which the octomap is updated. The animation below shows MoveIt! using an octomap to perform collision avoidance. @@ -34,7 +34,7 @@ The next item Ridhwan worked on was building a pipeline to detect, segment, and []({{ site.url }}/assets/images/gsoc18/octomap.png) ### Pick and Place Pipeline Tutorial -After finding a collision object, the next task is to pick it up. There was previously no tutorial on how the 'pick and place' pipeline worked, so Ridhwan [created a tutorial](https://ros-planning.github.io/moveit_tutorials/doc/pick_place/pick_place_tutorial.html) to address this gap. +After finding a collision object, the next task is to pick it up. There was previously no tutorial on how the 'pick and place' pipeline worked, so Ridhwan [created a tutorial](https://moveit.github.io/moveit_tutorials/doc/pick_place/pick_place_tutorial.html) to address this gap. The animation below shows a cuboidal object being moved from one table to another using the pick and place pipeline. diff --git a/_posts/2018-10-25-gsoc-motion-planning-support.markdown b/_posts/2018-10-25-gsoc-motion-planning-support.markdown index 4f8c75c75..a11ce5d18 100644 --- a/_posts/2018-10-25-gsoc-motion-planning-support.markdown +++ b/_posts/2018-10-25-gsoc-motion-planning-support.markdown @@ -19,7 +19,7 @@ Submitted by: Raghavender Sahdev, York University One of this year's Google Summer of Code Projects (GSoC) was the project, “Adding motion planning support for motion planners in MoveIt!”. This project, with coordination with PickNik Consulting, Open Source Robotics Foundation (OSRF), Dave Coleman, and Mark Moll, has been developed for the purpose of improving and extending the currently existing planners in MoveIt!. An existing concept of planning adapters in MoveIt! was used to have a pipeline of two planners running sequentially to provide robust solutions. -Prior to summer 2018, MoveIt! only had a single stable motion planning library as its core motion planner, i.e. OMPL. As a part of this GSoC project, motion planning support was extended by making other motion planners (CHOMP) more stable and porting STOMP also to be a part of the MoveIt! motion planners family. The MoveIt! part of STOMP was ported from the [ros-industrial/industrial_moveit](https://github.com/ros-industrial/industrial_moveit) repository into the [moveit/motion planners](https://github.com/ros-planning/moveit/tree/kinetic-devel/moveit_planners). Furthermore, the benchmarking package was made to work with other motion planners in addition to OMPL and its [tutorials](https://ros-planning.github.io/moveit_tutorials/doc/benchmarking/benchmarking_tutorial.html) were added. This package provides user the option to visualize quantitatively different parameters (time taken, trajectory length, solved status, etc.) for different motion planners (OMPL, CHOMP, STOMP) in a common environment (with/without obstacles) and make a decision on which planner the user might want to use. +Prior to summer 2018, MoveIt! only had a single stable motion planning library as its core motion planner, i.e. OMPL. As a part of this GSoC project, motion planning support was extended by making other motion planners (CHOMP) more stable and porting STOMP also to be a part of the MoveIt! motion planners family. The MoveIt! part of STOMP was ported from the [ros-industrial/industrial_moveit](https://github.com/ros-industrial/industrial_moveit) repository into the [moveit/motion planners](https://github.com/ros-planning/moveit/tree/kinetic-devel/moveit_planners). Furthermore, the benchmarking package was made to work with other motion planners in addition to OMPL and its [tutorials](https://moveit.github.io/moveit_tutorials/doc/benchmarking/benchmarking_tutorial.html) were added. This package provides user the option to visualize quantitatively different parameters (time taken, trajectory length, solved status, etc.) for different motion planners (OMPL, CHOMP, STOMP) in a common environment (with/without obstacles) and make a decision on which planner the user might want to use. The concept of Planning Request Adapters was used to implement the usage of multiple planning algorithms to be used together in MoveIt. This enables the user to use motion planning algorithms in a pipeline to produce better trajectories in different situations. For instance the user could specify a start and a goal location in RViz and then 2 motion planners could be run in a sequence like OMPL followed by CHOMP implying the usage of a CHOMP Optimization planning adapter. So OMPL would produce an initial motion plan which is then used as an initial trajectory guess for CHOMP to further optimize. Likewise, other motion planning pipelines that are possible by using the Planning Request Adapters concept in MoveIt include: (i) CHOMP + STOMP, (ii) OMPL + STOMP; (iii) STOMP + CHOMP; (iv) OMPL + CHOMP. The first 2 of these involve using the STOMP Smoothing Planning Request Adapter and the later two use the CHOMP Optimization Adapter. The way these planning request adapters can be used is straightforward and is documented in the [Planning Request Adapters tutorials page](https://github.com/ros-planning/moveit_tutorials/blob/kinetic-devel/doc/planning_adapters/planning_adapters_tutorial.rst) in [moveit_tutorials](https://github.com/ros-planning/moveit_tutorials) repository. diff --git a/_posts/2020-02-25-mtc.md b/_posts/2020-02-25-mtc.md index bc2bdcd1e..7d5a7e4b3 100644 --- a/_posts/2020-02-25-mtc.md +++ b/_posts/2020-02-25-mtc.md @@ -16,7 +16,7 @@ categories: Since its introduction at ROSCon 2018 by Robert Haschke and Michael Görner, the MoveIt Task Constructor (MTC) has gained a lot of interest inside the MoveIt community and in industry. We’re happy to announce that MTC is ready for use and we present the official tutorial including a demo application. -The MoveIt Task Constructor (MTC) is a multi-stage planning framework for solving complex motion planning tasks like pick-and-place operations or other object manipulations. With MTC a task is an instance of a high-level planning problem composed of smaller subproblems that are solved by individual stages. These stages are arrangeable components that compute simple steps like moving the robot between two intermediate states or attaching an object to the gripper. Stages can be freely arranged in sequence or in hierarchical order and even allow arbitrary control flows including alternative and fall-back solutions. The MTC package provides a set of primitive default stages which can already be used to integrate a generic pick-and-place pipeline. Check out the new tutorial for more information and an example implementation. +The MoveIt Task Constructor (MTC) is a multi-stage planning framework for solving complex motion planning tasks like pick-and-place operations or other object manipulations. With MTC a task is an instance of a high-level planning problem composed of smaller subproblems that are solved by individual stages. These stages are arrangeable components that compute simple steps like moving the robot between two intermediate states or attaching an object to the gripper. Stages can be freely arranged in sequence or in hierarchical order and even allow arbitrary control flows including alternative and fall-back solutions. The MTC package provides a set of primitive default stages which can already be used to integrate a generic pick-and-place pipeline. Check out the new tutorial for more information and an example implementation. Using MTC for motion planning offers several advantages over conventional approaches. The modular architecture allows for easy replacement and rearrangement of tasks and stages while maintaining a readable and functional implementation. Also, the source code always follows a well-defined structure, which makes components more portable, testable, and reusable. This goes hand-in-hand with better debugging and introspection capabilities. For instance, individual stage solutions can be run and visualized with RViz in using the MTC panel. Lastly, MTC can optimize for the total cost over all stages, finding good solutions in its defined solution graph. @@ -32,7 +32,7 @@ With MTC there is a lot to look out for in the future. Not only will there be mo ### Useful Links -* MoveIt tutorial +* MoveIt tutorial * Github repository * ICRA 2019 publication * Demonstration Video diff --git a/_posts/2020-06-09-moveit2-robotic-application.md b/_posts/2020-06-09-moveit2-robotic-application.md index 097ed6473..7d963d060 100644 --- a/_posts/2020-06-09-moveit2-robotic-application.md +++ b/_posts/2020-06-09-moveit2-robotic-application.md @@ -21,6 +21,6 @@ My ROS2 setup involved building the MoveIt2 repository from source as described The C++ integration was very straight forward and only needed the use of two new classes, MoveItCpp and PlanningComponent. In this architecture, MoveItCpp is used to load the robot model, configure the planning pipeline from ROS2 parameters and initialize defaults; then there's the PlanningComponent class which is associated to a planning group and is used to setup the motion plan request and call the low level planner. Furthermore, the PlanningComponent class has a similar interface to the familiar MoveGroupInterface class from MoveIt; however one of the big changes here is that the methods in the PlanningComponent class aren't just wrappers to various services and actions provided by the [move_group](/documentation/concepts/) node but they instead make direct function calls to the various motion planning capabilities. I think this is a welcomed changed since this architecture will allow creating MoveIt2 planning configuration on the fly that can adapt to varying planning situations that may arise in an application. -On the other hand, the launch/yaml integration wasn't as clean as many ROS2 concepts are still relatively new to me. In order to properly configure MoveIt2, it is necessary to load a URDF file as well as a number of parameters residing in several yaml files into your MoveIt2 application. Fortunately, most of the yaml files generated by the MoveIt Setup Assistant from the original MoveIt can be used with just minor modifications and so I ran the Setup Assistant in ROS1 and generated the needed config files. Furthermore, the ability to assemble ROS2 launch files in python really came in handy here as it allowed me to instantiate a python dictionary from a YAML file and pass its elements as parameters for my ROS2 application. Beyond learning about MoveIt2, going through this exercise showed me how to reuse the same yaml file for initializing parameters in different applications which I thought was a feature that was no longer available in ROS2. +On the other hand, the launch/yaml integration wasn't as clean as many ROS2 concepts are still relatively new to me. In order to properly configure MoveIt2, it is necessary to load a URDF file as well as a number of parameters residing in several yaml files into your MoveIt2 application. Fortunately, most of the yaml files generated by the MoveIt Setup Assistant from the original MoveIt can be used with just minor modifications and so I ran the Setup Assistant in ROS1 and generated the needed config files. Furthermore, the ability to assemble ROS2 launch files in python really came in handy here as it allowed me to instantiate a python dictionary from a YAML file and pass its elements as parameters for my ROS2 application. Beyond learning about MoveIt2, going through this exercise showed me how to reuse the same yaml file for initializing parameters in different applications which I thought was a feature that was no longer available in ROS2. My overall impression of MoveIt2 was very positive and I feel that the architectural changes aren't at all disruptive to existing MoveIt developers and furthermore it'll lead to new interesting ways in which the framework gets used; I sure look forward to the porting of other very useful MoveIt components. The branch of project that integrates MoveIt2 can be found here and below is a short clip of the planning that I was able to do with it. In this application, the robot has to move the camera to three scan position and so MoveIt2 is used to plan collision-free motions to those positions. diff --git a/_posts/2020-08-04-moveit-melodic-release.md b/_posts/2020-08-04-moveit-melodic-release.md index 8ec328df5..d6b520b98 100644 --- a/_posts/2020-08-04-moveit-melodic-release.md +++ b/_posts/2020-08-04-moveit-melodic-release.md @@ -19,10 +19,10 @@ Real-time robot arm control. [So cool, we even got a smile from a famous person ![thank_you_servo](/assets/images/blog_posts/2020_08_01_servo.gif) -[Here is an tutorial for getting started with it. ](https://ros-planning.github.io/moveit_tutorials/doc/realtime_servo/realtime_servo_tutorial.html) +[Here is an tutorial for getting started with it. ](https://moveit.github.io/moveit_tutorials/doc/realtime_servo/realtime_servo_tutorial.html) ### moveit_cpp -There is a new high level API for users who want convenient access to MoveIt's functionality via C++ classes. [Here is the tutorial for using it.](https://ros-planning.github.io/moveit_tutorials/doc/moveit_cpp/moveitcpp_tutorial.html) +There is a new high level API for users who want convenient access to MoveIt's functionality via C++ classes. [Here is the tutorial for using it.](https://moveit.github.io/moveit_tutorials/doc/moveit_cpp/moveitcpp_tutorial.html) ## Additional features * Allow parameterization of input trajectory density of Time Optimal trajectory generation (#2185) diff --git a/_posts/2020-09-10-ompl-constrained-planning-gsoc.md b/_posts/2020-09-10-ompl-constrained-planning-gsoc.md index dd7f07caa..22a9216c8 100644 --- a/_posts/2020-09-10-ompl-constrained-planning-gsoc.md +++ b/_posts/2020-09-10-ompl-constrained-planning-gsoc.md @@ -17,14 +17,14 @@ The Open Motion Planning Library (OMPL) is the main library used by MoveIt to pl ## New features -A new option `enforce_constrained_planning` can be set to `true` in [ompl_planning.yaml](https://ros-planning.github.io/moveit_tutorials/doc/ompl_interface/ompl_interface_tutorial.html) to use the new projection-based sampling approach. The [current implementation](https://github.com/ros-planning/moveit/pull/2273) supports box constraints and equality position constraints (planes and lines). A [second pull request](https://github.com/JeroenDM/moveit/pull/6) will add support for orientation constraints in the future. +A new option `enforce_constrained_planning` can be set to `true` in [ompl_planning.yaml](https://moveit.github.io/moveit_tutorials/doc/ompl_interface/ompl_interface_tutorial.html) to use the new projection-based sampling approach. The [current implementation](https://github.com/ros-planning/moveit/pull/2273) supports box constraints and equality position constraints (planes and lines). A [second pull request](https://github.com/JeroenDM/moveit/pull/6) will add support for orientation constraints in the future. -The most interesting aspect of this new planning approach is shown below. Planning with end-effector constraints sometimes results in large joint space jumps, making the path unusable on a real robot (shown on the left). The new planner solves the same problem without these joint space jumps in the solution (shown on the right). For constraints such as equality position constraints, the existing way to avoid joint space jumps, using the [enforce_joint_model_state_space](https://ros-planning.github.io/moveit_tutorials/doc/ompl_interface/ompl_interface_tutorial.html#enforce-planning-in-joint-space) option, does not work. +The most interesting aspect of this new planning approach is shown below. Planning with end-effector constraints sometimes results in large joint space jumps, making the path unusable on a real robot (shown on the left). The new planner solves the same problem without these joint space jumps in the solution (shown on the right). For constraints such as equality position constraints, the existing way to avoid joint space jumps, using the [enforce_joint_model_state_space](https://moveit.github.io/moveit_tutorials/doc/ompl_interface/ompl_interface_tutorial.html#enforce-planning-in-joint-space) option, does not work. drawing drawing -A [new tutorial](https://github.com/ros-planning/moveit_tutorials/pull/518) explains how to configure and use this new planning option, using simple but instructive examples with the Panda robot. These are implemented using MoveIt’s [Python interface](https://ros-planning.github.io/moveit_tutorials/doc/move_group_python_interface/move_group_python_interface_tutorial.html), making it extremely convenient to try out the new planner and quickly experiment with different planning problems. +A [new tutorial](https://github.com/ros-planning/moveit_tutorials/pull/518) explains how to configure and use this new planning option, using simple but instructive examples with the Panda robot. These are implemented using MoveIt’s [Python interface](https://moveit.github.io/moveit_tutorials/doc/move_group_python_interface/move_group_python_interface_tutorial.html), making it extremely convenient to try out the new planner and quickly experiment with different planning problems. drawing drawing diff --git a/_posts/2020-09-28-grasp-deep-learning.md b/_posts/2020-09-28-grasp-deep-learning.md index 7afa7afcb..58a14b8e7 100644 --- a/_posts/2020-09-28-grasp-deep-learning.md +++ b/_posts/2020-09-28-grasp-deep-learning.md @@ -35,4 +35,4 @@ The animation below shows the capabilities of deep learning for grasp pose gener | | | | | | -To learn more about how to use GPD and Dex-Net within MoveIt see the [Deep Grasp Tutorial](https://ros-planning.github.io/moveit_tutorials/doc/moveit_deep_grasps/moveit_deep_grasps_tutorial.html) and the [Deep Grasp Demo](https://github.com/PickNikRobotics/deep_grasp_demo). The demo contains detailed instructions for acquiring data by simulating depth sensors and executing motion plans in Gazebo. +To learn more about how to use GPD and Dex-Net within MoveIt see the [Deep Grasp Tutorial](https://moveit.github.io/moveit_tutorials/doc/moveit_deep_grasps/moveit_deep_grasps_tutorial.html) and the [Deep Grasp Demo](https://github.com/PickNikRobotics/deep_grasp_demo). The demo contains detailed instructions for acquiring data by simulating depth sensors and executing motion plans in Gazebo. diff --git a/_posts/2020-11-18-bullet-collision.md b/_posts/2020-11-18-bullet-collision.md index 5532eb541..7f32fd663 100644 --- a/_posts/2020-11-18-bullet-collision.md +++ b/_posts/2020-11-18-bullet-collision.md @@ -27,7 +27,7 @@ I started with a full fork of Tesseract in the MoveIt workspace. Then, step-by-s This finally led to the decision to restructure major parts of MoveIt's collision checking. To make this change happen, I had to unify all existing collision detectors which included FCL. Furthermore, many changes in the planning scene were necessary which in turn then required changes throughout the codebase because the planning scene is such a central class. -To demonstrate the new collision checking capabilities, I added a [new tutorial](https://ros-planning.github.io/moveit_tutorials/doc/bullet_collision_checker/bullet_collision_checker.html). In an interactive environment, Bullet can be tested with a demo object and the Panda robot. The CCD capabilities are demonstrated in the second part of the tutorial. Try it out yourself! +To demonstrate the new collision checking capabilities, I added a [new tutorial](https://moveit.github.io/moveit_tutorials/doc/bullet_collision_checker/bullet_collision_checker.html). In an interactive environment, Bullet can be tested with a demo object and the Panda robot. The CCD capabilities are demonstrated in the second part of the tutorial. Try it out yourself! A detailed overview of the work done including discussions is available in the [Github issue](https://github.com/ros-planning/moveit/issues/1427). For a better understanding of the collision detection process, I created several flowcharts shown in the [Developer Concepts page](https://moveit.ros.org/documentation/concepts/developer_concepts/). diff --git a/_posts/2020-12-17-Pilz-Plugin-for-MoveIt.md b/_posts/2020-12-17-Pilz-Plugin-for-MoveIt.md index 01cd0b54d..cac354d30 100644 --- a/_posts/2020-12-17-Pilz-Plugin-for-MoveIt.md +++ b/_posts/2020-12-17-Pilz-Plugin-for-MoveIt.md @@ -12,7 +12,7 @@ categories: - Pilz - Motion Planner --- -MoveIt’s default planners are really great at finding collision-free paths in complex environments but the resulting motions can be very unpredictable. Sometimes you just want a simple motion for a simple planning problem. The now available [Pilz industrial motion planner](https://ros-planning.github.io/moveit_tutorials/doc/pilz_industrial_motion_planner/pilz_industrial_motion_planner.html) supports solving for circular or linear motions in a rapid and predictable way. Additionally, it supports blending multiple motion segments together with a new MoveIt capability! The MoveIt Maintainers are excited to announce that with this new motion planner MoveIt finally supports basic industrial motions out of the box. The motion planning plug in was presented at the MoveIt Workshop in Macau in November 2019. Designed by Pilz Automation, one of Germany’s leading automation technology companies, this new MoveIt feature is designed to bring more industrial robot functionality to MoveIt. +MoveIt’s default planners are really great at finding collision-free paths in complex environments but the resulting motions can be very unpredictable. Sometimes you just want a simple motion for a simple planning problem. The now available [Pilz industrial motion planner](https://moveit.github.io/moveit_tutorials/doc/pilz_industrial_motion_planner/pilz_industrial_motion_planner.html) supports solving for circular or linear motions in a rapid and predictable way. Additionally, it supports blending multiple motion segments together with a new MoveIt capability! The MoveIt Maintainers are excited to announce that with this new motion planner MoveIt finally supports basic industrial motions out of the box. The motion planning plug in was presented at the MoveIt Workshop in Macau in November 2019. Designed by Pilz Automation, one of Germany’s leading automation technology companies, this new MoveIt feature is designed to bring more industrial robot functionality to MoveIt. “MoveIt is a very powerful tool to control your robots in all sorts of complex shapes. But we think that industrial applications often also demand simple things like just moving in a straight line. So we made a plugin for that.” diff --git a/about/distribution/index.markdown b/about/distribution/index.markdown index 3e6c20978..57567e752 100644 --- a/about/distribution/index.markdown +++ b/about/distribution/index.markdown @@ -44,7 +44,7 @@ title: Distribution May 2027 - MoveIt 1 Noetic + MoveIt 1 Noetic October 13th, 2020 MoveIt 1 Noetic May 2025 diff --git a/documentation/concepts/index.markdown b/documentation/concepts/index.markdown index 241289d9c..6fabf1b9e 100644 --- a/documentation/concepts/index.markdown +++ b/documentation/concepts/index.markdown @@ -177,7 +177,7 @@ MoveIt uses a plugin infrastructure, especially targeted towards allowing users ### **IKFast Plugin** -Often, users may choose to implement their own kinematics solvers, e.g. the PR2 has its own kinematics solvers. A popular approach to implementing such a solver is using the [IKFast package](https://ros-planning.github.io/moveit_tutorials/doc/ikfast/ikfast_tutorial.html) to generate the C++ code needed to work with your particular robot. +Often, users may choose to implement their own kinematics solvers, e.g. the PR2 has its own kinematics solvers. A popular approach to implementing such a solver is using the [IKFast package](https://moveit.github.io/moveit_tutorials/doc/ikfast/ikfast_tutorial.html) to generate the C++ code needed to work with your particular robot. --- diff --git a/documentation/contributing/future_projects/index.markdown b/documentation/contributing/future_projects/index.markdown index 3f387e792..903119ada 100644 --- a/documentation/contributing/future_projects/index.markdown +++ b/documentation/contributing/future_projects/index.markdown @@ -66,7 +66,7 @@ Feel free to contact [PickNik Robotics](https://picknik.ai/connect/) for further - **Programming skills**: C++, Python - **Difficulty**: Medium - **Potential mentors**: Mark Moll -- **Description**: Improve grasp pose synthesis within MoveIt and the MoveIt Task constructor. Current grasp synthesis algorithms pair deep neural networks and sampling point clouds, see [GPD](https://github.com/atenpas/gpd) and [Dex-Net](https://berkeleyautomation.github.io/dex-net/). An initial effort using the previous grasping methods includes a [demo](https://github.com/PickNikRobotics/deep_grasp_demo) and a [tutorial](https://ros-planning.github.io/moveit_tutorials/doc/moveit_deep_grasps/moveit_deep_grasps_tutorial.html). Further work is required to harden this implementation, see [PR 196](https://github.com/ros-planning/moveit_task_constructor/pull/196). +- **Description**: Improve grasp pose synthesis within MoveIt and the MoveIt Task constructor. Current grasp synthesis algorithms pair deep neural networks and sampling point clouds, see [GPD](https://github.com/atenpas/gpd) and [Dex-Net](https://berkeleyautomation.github.io/dex-net/). An initial effort using the previous grasping methods includes a [demo](https://github.com/PickNikRobotics/deep_grasp_demo) and a [tutorial](https://moveit.github.io/moveit_tutorials/doc/moveit_deep_grasps/moveit_deep_grasps_tutorial.html). Further work is required to harden this implementation, see [PR 196](https://github.com/ros-planning/moveit_task_constructor/pull/196). - **Related Github issues**: [188](https://github.com/ros-planning/moveit_task_constructor/issues/188) diff --git a/install/docker/index.markdown b/install/docker/index.markdown index fd29294d1..451af3435 100644 --- a/install/docker/index.markdown +++ b/install/docker/index.markdown @@ -80,7 +80,7 @@ title: MoveIt 1 Docker Install

Start planning in Rviz with:

- + MoveIt Getting Started Tutorial diff --git a/install/index.markdown b/install/index.markdown index 5df343490..c082cdea9 100644 --- a/install/index.markdown +++ b/install/index.markdown @@ -104,7 +104,7 @@ title: MoveIt 1 Binary Install

Start planning in Rviz with:

- + MoveIt Getting Started Tutorial @@ -250,7 +250,7 @@ title: MoveIt 1 Binary Install

MoveIt Quickstart in RViz

Now you are ready to start planning in Rviz with:

- + MoveIt Getting Started Tutorial diff --git a/install/source/index.markdown b/install/source/index.markdown index 85ef866b8..e5eb6b2b3 100644 --- a/install/source/index.markdown +++ b/install/source/index.markdown @@ -133,7 +133,7 @@ title: MoveIt 1 Source Build - Linux

Start planning in Rviz with:

- + MoveIt Getting Started Tutorial