b-it-bots / mas_industrial_robotics Goto Github PK

Describe the bug

mir_refbox_parser uses MoveBaseSafe action server object instead of the new GenericExecute action server objects

Need to implement a e_stop button which can kill ethercat such that the arm and base stops moving.

Is your feature request related to a problem? Please describe.
Google coral sicks can be used to do Deep learning tasks .
Here we have to folow coral tutorials to do :

Describe the solution you'd like
https://colab.sandbox.google.com/github/google-coral/tutorials/blob/master/retrain_classification_ptq_tf1.ipynb

Describe alternatives you've considered
https://tvm.apache.org/docs/tutorials/relay_quick_start.html#sphx-glr-tutorials-relay-quick-start-py

Fix PyLint errors in "mir_perception/mir_perceive_aruco_cube" package seen at https://gist.github.com/iswariyam/9e04916f92124e1ce50b56b377b60a77. Issues is part of #148

During BNT, there is a chance that the robot does not reach the waypoint within 60 seconds (this is the timeout specified in our SM).
If it does not, the next waypoint goal preempts the current (failed) waypoint goal, preempting the actionlib server. This preemption is not handled correctly, resulting in the second waypoint being skipped too.

@mhwasil can you attach the log from BNT?

@abhishek098 @DjoleMNE
when you have time, please take a look

• ros-kinetic-brics-actuator
• orocos_kdl
• ros-kinetic-bfl
• libsvm-dev
• ros-kinetic-tf2-bullet
• ros-kinetic-mongodb-store
• flex

Use ROSPlan's planning pipeline as much as possible instead of the custom developed one.

Possible advantages

• better support
• beginner friendly (because of ROSPlan's tutorial)
• removal of repeated code
• following "universal" standards

Most of the python code in the repo is not linted as per PEP8 guidelines. The average rating given by pylint for the various modules is around 3/10. The list of pylint errors can be found here
The errors need to be fixed manually.

Can we automatically push the built docs into b-it-bots wiki? @Sushant-Chavan

related to #78

Aruco perception is used currently for picking ARUCO_CUBE from the drawer. This needs to be replaced with real perception whenever it is ready.

Additional context
#99 (comment)

In the .pylintrc the indentation is set to 4, which is different from cpp indentation which is 2.

1. Adding default parameters
2. Makes sure roslint passes
3. refactor the test cases
4. Fix readme

• Decide on speakers
• Decide on the format
• Decide on content

location will be here https://github.com/b-it-bots/competition-documents

Is your feature request related to a problem? Please describe.
PPT recognition code needs to be updated

Describe the solution you'd like
Based on point cloud only

• Find plane
• Finding missing points on plane
• Match shape of the missing points

@HAndradi please correct below

Describe alternatives you've considered
The current deep learning based dsnt scale better

Migrated and tested

• youbot_description
• brics_actuator
• youbot_driver
• youbot_driver_ros_interface
• mir_teleop
• bringup

Migrated

• mir_object_recognition based on the SDP project here (except for 3D recognition)
• mir_gripper_controller

In progress

• youbot_gazebo_control

  • ros2_control has been refactored, so we need to update the steered_wheel_base_controller plugin or write a new one. See here for examples.

• Navigation

  • initial tests with the slam_toolbox for creating a map resulted in overlapping maps
  • slam_gmapping and openslam_gmapping have been ported and tested on the real robot for use in ROS 2
  • mir_direct_base_controller is still in progress. Version as of April 2024 is from here. Obstacle avoidance is not ported yet.

Need to integrate travis CI for testing of the software.

Different methods are available:

1. Docker based
2. ROS industrial based
3. https://github.com/tdenewiler/node_example

Hi,
From https://gist.github.com/iswariyam/9e04916f92124e1ce50b56b377b60a77. Issues is part of #148
I will be taking care of the following files for linting purposes:

'mir_calibration/mir_kinect_calibration',
'mir_manipulation/mir_arm_relative_motion_control',
'mir_manipulation/mir_grasp_monitors',
'mir_manipulation/mir_gripper_controller',
'mir_manipulation/mir_moveit_scene',
'mir_manipulation/mir_pregrasp_planning',

Related to https://github.com/b-it-bots/unmerged_packages_for_testing/issues/123

Please see that issue for more details

tags: documentation, WIP

cc: @mhwasil

sphinx rtd theme cannot be used as hard dependency anymore

Theme error:
sphinx_rtd_theme is no longer a hard dependency since version 1.4.0. Please install it manually.(pip install sphinx_rtd_theme)

use pip instead.
can you PR @DharminB

Currently, the safe distance from the drawer is being hardcoded in open_drawer_server and close_drawer_server in package mir_manipulate_drawer.

The safe distance is the distance between front laser and drawer surface. The robot needs to make sure that it is far away from the drawer to move that arm without collision. The distance is hardcoded based on how far ahead is the arm gripper from laser when it is in the required orientation. This, however, can be calculated based on

1. joint angles of the recorded arm orientation (here drawer_handle_pre_grasp)
2. transform from front laser to gripper

Currently only x value is needed but it would be better if all 3 values are calculated.

Additional context
#99 (comment)

Currently we only use 3 place poses and cycle back to the first one

This package already provides an interface for moving the manipulator to a given Cartesian pose. However it doesn't work.
The package mir_moveit_to_pose also does this (which actually works. Hence, the functionality should be moved to the mcr_moveit_client package to avoid confusion.

Instead of using hardcoded orientation, mir_pre_grasp_planning should be used to calculate the end pose for the object based on the current position of the robot.

Additional context
#99 (comment)

Here is the list of cpplint errors. These errors need to be fixed manually, so that cpplint check can be added in pre-commit_hooks.yaml.

We want to visualize two things

1. the facts and goals in the knowledge base. This includes locations of objects, their target destinations, state of the robot's rear platform, whether an object is in the gripper, etc.
2. the task plan

Using Rviz markers might be the best way to do this. CAD models of all objects are available here (rviz can be used to display meshes)

Here is the ISAAC SIM for navigation from NVIDIA . Might be useful but someone needs to integrate it. https://developer.nvidia.com/isaac-sim

Changes made in Milan broke the simulation. I narrowed down the problem to commit #8 . Please revert changes.

Generate docs from python docstrings wherever available

hello,

I was trying to install ROS using the docker image. I installed docker and docker-compose (latest versions) from the official docker website then followed the steps given here and changed the host file system path and driver version as per my system.

I had cloned the docker and mas_industrial_robotics repositories in /home/elanton/Robocup directory and then used in terminal (current directory: /home/elanton/Robocup/docker) used the following command sudo docker-compose -f industrial/start-container.yml up ros_kinetic_container and then opened a new terminal and used the following command docker exec -it ros_kinetic_container_1 bash but i get the following error: Got permission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Get http://%2Fvar%2Frun%2Fdocker.sock/v1.40/containers/ros_kinetic_container_1/json: dial unix /var/run/docker.sock: connect: permission denied

Pre-commit hooks are usually run before committing the changes locally. If the checks dont pass then one cannot commit the files. Pre-commit hooks can for example take care of code formatting and linting, and support multiple languages.

Solution
Add .pre-commit-config.yaml to the repo. This file has all the desired configurations.
For more info, refer here.

• Camera mount 1
• Camera mount 2
• Center camera gripper mount
• back platform
• intel d435 camera model and position

Is your feature request related to a problem? Please describe.
Run pick_object_server in simulation to pick an object

• collect @work dataset point cloud for learning
• train model

We need a robust, safe, fast align base using just laser scanner.

Requirements:

1. Needs to be at the lower level. Can take some ideas from LuhBots code (https://github.com/LUHbots/luh_youbot_os/blob/master/luh_youbot_controller/src/module_base_controller/base_controller.cpp)

Additional Info

Just using laser scanner will be not sufficient. We have to use image based alignment. The main idea to align is to have better view of the workspace. So using image to align should be he ultimate goal.

Currently the orientation of the handle in mir_handle_detection is hardcoded. It needs to be calculated. The normal of the plane of the drawer should be used as orientation.

This orientation can later be used to align the robot perpendicular to the drawer surface rather than assuming that it is parallel.

Additional context
#99 (comment)

ros kinetic to melodic migration @deebuls and @sthoduka

Picking objects from bottom shelf is not available as a streamlined solution.

It would be best if there is a action server pipeline entirely dedicated for shelf picking. This will make the normal pick simple and fast (hence more debuggable). It would be similar to how different perceives (mir_perceive_location and mir_perceive_cavity) and different inserts (mir_insert_object and mir_insert_cavity) are handled.

tags: new feature, refactoring
Assigned to: @DharminB
Project: german open 2020

PPT wiggle arm goes to joint limits . Need to debug

The current slow behaviour of DBC is due to low loop rate.

@mhwasil

Generate world configuration for at work scenario (walls and workstations and shelves)
This will be represented using a .xacro file.
Accompanied with it should be an occupancy grid (.pgm and .yaml) (along with navigation_goals.yaml if possible)

This could help the testing of robocup related software since we can test against different configurations of workstations in simulation.

See #142
Also use grasp plugin for default youbot gripper

Describe the bug

check below

Define a message in mir_planning_msgs that's similar to the Status message defined in ropod_ros_msgs

The purpose of this message is to enumerate all possible outcomes of all components, including success and failure outcomes. Eventually this message will be a field in the feedback/result of GenericExecute

For now only module_code, status_code and sm_state are required.
You could use status codes 1-100 for mir_move_base_safe, 101-200 for mir_perceive_location etc.

To find out all the possible outcomes of an action you can talk to the following people:

mir_move_base_safe - Dharmin
mir_perceive_location - Wasil
mir_perceive_cavity - Heruka
mir_perceive_rtt - Heruka
mir_pick_object/from_shelf/from_drawer - Carlo / Dharmin
mir_place_object - Carlo / Dharmin
mir_stage/unstage_object - Carlo Dharmin
mir_insert_cavity/object - Carlo/ Dharmin

I am trying the build the repository and ending up with errors all the time
please find error log below

Errors << mcr_algorithms:make /home/santosh/kinetic/logs/mcr_algorithms/build.make.000.log
In file included from /home/santosh/kinetic/src/mas_common_robotics/mcr_common/mcr_algorithms/common/src/machine_learning/svm_trainer.cpp:1:0:
/home/santosh/kinetic/src/mas_common_robotics/mcr_common/mcr_algorithms/common/include/mcr_algorithms/machine_learning/svm_trainer.h:4:24: fatal error: libsvm/svm.h: No such file or directory
compilation terminated.
make[2]: *** [CMakeFiles/mcr_machine_learning.dir/common/src/machine_learning/svm_trainer.cpp.o] Error 1
make[1]: *** [CMakeFiles/mcr_machine_learning.dir/all] Error 2
make: *** [all] Error 2
cd /home/santosh/kinetic/build/mcr_algorithms; catkin build --get-env mcr_algorithms | catkin env -si /usr/bin/make --jobserver-fds=6,7 -j; cd -
...............................................................................
Failed << mcr_algorithms:make [ Exited with code 2 ]
Failed <<< mcr_algorithms [ 6.5 seconds ]
Abandoned <<< mcr_base_collision_checker [ Unrelated job failed ]
Abandoned <<< mcr_cavity_detector [ Unrelated job failed ]
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Abandoned <<< mcr_teleop [ Unrelated job failed ]
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Abandoned <<< mcr_trajectory_time_parameterizer [ Unrelated job failed ]
Abandoned <<< mcr_twist_limiter [ Unrelated job failed ]
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Abandoned <<< mir_insert_object [ Unrelated job failed ]
Abandoned <<< mir_knowledge [ Unrelated job failed ]
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Abandoned <<< youbot_battery_monitor [ Unrelated job failed ]
Abandoned <<< youbot_dashboard [ Unrelated job failed ]
Abandoned <<< youbot_description [ Unrelated job failed ]
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Abandoned <<< mcr_geometric_relation_monitors [ Unrelated job failed ]
Abandoned <<< mas_perception_libs [ Unrelated job failed ]
Abandoned <<< mcr_cavity_recognition [ Unrelated job failed ]
Abandoned <<< mcr_contour_matching [ Unrelated job failed ]
Abandoned <<< mcr_leg_detection [ Unrelated job failed ]
Abandoned <<< mcr_linear_regression [ Unrelated job failed ]
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Abandoned <<< mcr_twist_demultiplexer [ Unrelated job failed ]
Abandoned <<< mcr_twist_synchronizer [ Unrelated job failed ]
Abandoned <<< mcr_knowledge [ Unrelated job failed ]
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Abandoned <<< mir_arm_cartesian_control [ Unrelated job failed ]
Abandoned <<< mir_arm_motions [ Unrelated job failed ]
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Abandoned <<< mir_kinect_calibration [ Unrelated job failed ]
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Abandoned <<< mir_manipulation_monitors [ Unrelated job failed ]
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Abandoned <<< mir_base_placement [ Unrelated job failed ]
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Abandoned <<< mir_pregrasp_planning [ Unrelated job failed ]
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Abandoned <<< mir_teleop [ Unrelated job failed ]
Abandoned <<< mir_trajectory_time_parameterizer [ Unrelated job failed ]
Abandoned <<< mir_visual_servoing [ Unrelated job failed ]
Abandoned <<< mir_whole_body_control_functionality [ Unrelated job failed ]
Abandoned <<< mir_whole_body_motion_calculator [ Unrelated job failed ]
Abandoned <<< mir_knowledge_base_analyzer [ Unrelated job failed ]
Abandoned <<< rosplan_knowledge_base [ Unrelated job failed ]
Abandoned <<< rosplan_planning_system [ Unrelated job failed ]
Abandoned <<< mcr_pddl_problem_generator [ Unrelated job failed ]
Abandoned <<< mir_plan_loader_msgs [ Unrelated job failed ]
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Abandoned <<< mir_planner_executor [ Unrelated job failed ]
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Abandoned <<< youbot_driver_ros_interface [ Unrelated job failed ]
Abandoned <<< youbot_gazebo_robot [ Unrelated job failed ]
Abandoned <<< youbot_moveit [ Unrelated job failed ]
Finished <<< mcr_arm_motions [ 3.5 seconds ]

Errors << lama_planner:make /home/santosh/kinetic/logs/lama_planner/build.make.000.log
make[3]: warning: jobserver unavailable: using -j1. Add '+' to parent make rule.
CMake Error at /usr/share/cmake-3.5/Modules/CMakeTestCCompiler.cmake:61 (message):
The C compiler "/usr/bin/gcc" is not able to compile a simple test program.

It fails with the following output:

Change Dir: /home/santosh/kinetic/src/lama_planner/build/LAMA/builds/release32/CMakeFiles/CMakeTmp

Run Build Command:"/usr/bin/make" "cmTC_1781f/fast"

make[4]: Entering directory
'/home/santosh/kinetic/src/lama_planner/build/LAMA/builds/release32/CMakeFiles/CMakeTmp'

/usr/bin/make -f CMakeFiles/cmTC_1781f.dir/build.make
CMakeFiles/cmTC_1781f.dir/build

make[5]: Entering directory
'/home/santosh/kinetic/src/lama_planner/build/LAMA/builds/release32/CMakeFiles/CMakeTmp'

Building C object CMakeFiles/cmTC_1781f.dir/testCCompiler.c.o

/usr/bin/gcc -m32 -o CMakeFiles/cmTC_1781f.dir/testCCompiler.c.o -c
/home/santosh/kinetic/src/lama_planner/build/LAMA/builds/release32/CMakeFiles/CMakeTmp/testCCompiler.c

Linking C executable cmTC_1781f

/usr/bin/cmake -E cmake_link_script CMakeFiles/cmTC_1781f.dir/link.txt
--verbose=1

/usr/bin/gcc -m32 CMakeFiles/cmTC_1781f.dir/testCCompiler.c.o -o cmTC_1781f
-rdynamic

/usr/bin/ld: cannot find crt1.o: No such file or directory

/usr/bin/ld: cannot find crti.o: No such file or directory

/usr/bin/ld: skipping incompatible /usr/lib/gcc/x86_64-linux-gnu/5/libgcc.a
when searching for -lgcc

/usr/bin/ld: cannot find -lgcc

/usr/bin/ld: skipping incompatible
/usr/lib/gcc/x86_64-linux-gnu/5/libgcc_s.so when searching for -lgcc_s

/usr/bin/ld: cannot find -lgcc_s

/usr/bin/ld: cannot find -lc

/usr/bin/ld: skipping incompatible /usr/lib/gcc/x86_64-linux-gnu/5/libgcc.a
when searching for -lgcc

/usr/bin/ld: cannot find -lgcc

/usr/bin/ld: skipping incompatible
/usr/lib/gcc/x86_64-linux-gnu/5/libgcc_s.so when searching for -lgcc_s

/usr/bin/ld: cannot find -lgcc_s

/usr/bin/ld: cannot find crtn.o: No such file or directory

collect2: error: ld returned 1 exit status

CMakeFiles/cmTC_1781f.dir/build.make:97: recipe for target 'cmTC_1781f'
failed

make[5]: *** [cmTC_1781f] Error 1

make[5]: Leaving directory
'/home/santosh/kinetic/src/lama_planner/build/LAMA/builds/release32/CMakeFiles/CMakeTmp'

Makefile:126: recipe for target 'cmTC_1781f/fast' failed

make[4]: *** [cmTC_1781f/fast] Error 2

make[4]: Leaving directory
'/home/santosh/kinetic/src/lama_planner/build/LAMA/builds/release32/CMakeFiles/CMakeTmp'

CMake will not be able to correctly generate this project.
Call Stack (most recent call first):
CMakeLists.txt:44 (project)

Traceback (most recent call last):
File "build/LAMA/build.py", line 153, in
main()
File "build/LAMA/build.py", line 149, in main
build(config_name, CONFIGS[config_name], make_parameters)
File "build/LAMA/build.py", line 125, in build
cwd=build_path)
File "build/LAMA/build.py", line 102, in try_run
subprocess.check_call(cmd, cwd=cwd)
File "/usr/lib/python2.7/subprocess.py", line 541, in check_call
raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command '['cmake', '-G', 'Unix Makefiles', '-DCMAKE_BUILD_TYPE=Release', '../../src']' returned non-zero exit status 1
make[3]: *** [lama_planner] Error 1
make[2]: *** [CMakeFiles/lama_planner] Error 2
make[1]: *** [CMakeFiles/lama_planner.dir/all] Error 2
make: *** [all] Error 2
cd /home/santosh/kinetic/build/lama_planner; catkin build --get-env lama_planner | catkin env -si /usr/bin/make --jobserver-fds=6,7 -j; cd -
...............................................................................
Failed << lama_planner:make [ Exited with code 2 ]
Failed <<< lama_planner [ 19.0 seconds ]
Finished <<< mcr_background_change_detection [ 16.2 seconds ]
[build] Summary: 4 of 196 packages succeeded.
[build] Ignored: 28 packages were skipped or are blacklisted.
[build] Warnings: 1 packages succeeded with warnings.
[build] Abandoned: 190 packages were abandoned.
[build] Failed: 2 packages failed.
[build] Runtime: 23.6 seconds total.
[build] Note: Workspace packages have changed, please re-source setup files to use them.

Converting the trained weights of mobilenet v2 to movidius graph.

Integrating the movidius into current framework.

To incorporate picking from a drawer, some more actions need to be added to the task planning domain.

I think this would be at least open and close, but probably also a new perceive action which has a precondition that the drawer is open.

The actions to pick from a drawer might look like:

1. perceive
2. open
3. pick
4. stage
5. close

We might also want to add actions for putting objects back in the drawer.

The docs should have everything you need to get task planning running independent of the robot.
cc: @DharminB