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--- gazebo:manipulation:basics [2018/10/12 17:00] – [Modules/Adventures] typos
+++ gazebo:manipulation:basics [2023/03/06 10:31] (current) – external edit 127.0.0.1
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 === Module Set 3: Modifying for Project Use ===
-  - Identify an alternative robot, usually one that is simply a fixed-base robotic arm.  Replace the PR2 robot with your chosen robotic arm. You can find ROS-related packages in Github for some commercial robot arms i.e. Kinova or use our customized robot arm named Handy from the [[https://github.com/ivaROS/ivaHandy | ivaHandy]] github site.
+  - Identify an alternative robot, usually one that is simply a fixed-base robotic arm.  Replace the PR2 robot with your chosen robotic arm. You can find ROS-related packages in Github for some commercial robot arms i.e. Kinova or use our customized robot arms from our [[https://github.com/ivaROS | github site]]:  Handy from  [[https://github.com/ivaROS/ivaHandy | ivaHandy]] or Edy from [[https://github.com/ivaROS/ivaEdy| ivaEdy]].
   - The rest part is for the group that needs ForageRRT planner and Manipulation State Space. Otherwise, you can keep using the default MoveIt! and Ompl code.
   - Install our custom code from the [[https://github.com/ivaROS | IVALab ROS]] public github site.  The two main repositories are [[https://github.com/ivaROS/ivaOmplCore | ivaOmplCore]] and [[https://github.com/ivaROS/ivaMoveitCore| ivaMoveItCore]].  The above codes are tested on ubuntu 14.04 with ROS indigo. On our lab computers, these should be installed already.
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   - To use it on Kinect via ROS, simply import tf (tensorflow) in your python node, and modify the provided demo.py to load the pretrained model for your own purposes.
   - (Optional) If you would like to finetune on specific object for grasping, this [[https://github.com/ivalab/grasp_annotation_tool|annotation tool]] provide a GUI interface for annotating grasps easily to generate training data!
+  - To figure out the transformation between robot base and camera, you can start with [[https://docs.opencv.org/3.1.0/d5/dae/tutorial_aruco_detection.html|ARUCO tag]]. [[https://github.com/ivalab/aruco_tag_saver|Here]] is the github repository in IVAlab for using kinect to use ARUCO. ARUCO is a standalone library implemented in C++ and wrapped in Python. It is also incorporated into OpenCV after 3.0.0. The ARUCO library provides tools to generate tags and detect printed tags. Can you generate tags and draw the pose for them?