PR2 Programming by Demonstration

This repository contains the work of Maya Cakmak and the Human-Centered Robotics Lab at the University of Washington. Please see those sites for citing publications. We abbreviate Programming by Demonstration with PbD.

System Requirements

Currently the PbD system has the following requirements:

• Ubuntu 14.04
• ROS Indigo
• mongo_msg_db and mongo_msg_db_msgs

Installing

Clone this repository and build on both your desktop machine and on the robot:

cd ~/catkin_ws/src
git clone https://github.com/hcrlab/blinky.git
git clone https://github.com/jstnhuang/mongo_msg_db_msgs.git
git clone https://github.com/jstnhuang/mongo_msg_db.git
git clone https://github.com/jstnhuang/rapid.git
git clone https://github.com/PR2/pr2_pbd.git
cd ~/catkin_ws
rosdep install --from-paths src --ignore-src --rosdistro=indigo -y
catkin_make

Running

PR2

Commands on PR2 (c1)

robot claim
robot start
source ~/catkin_ws/devel/setup.bash
roslaunch pr2_pbd_interaction pbd_backend.launch

Desktop

setrobot <ROBOT_NAME>
roslaunch pr2_pbd_interaction pbd_frontend.launch
roslaunch pr2_pbd_interaction pbd_frontend.launch  # rviz, rqt, speech

# Optionally open PR2 dashboard in another terminal window
setrobot <ROBOT_NAME>
rosrun rqt_pr2_dashboard rqt_pr2_dashboard # Optional

Plug in a microphone to your computer. Speak into the microphone to issue speech commands to the robot. The voice commands are not currently documented.

Running in simulation (untested)

roslaunch pr2_pbd_interaction pbd_simulation_stack.launch

Common issues

Saving poses / executing actions is very slow

If it takes a very long time to save a pose, it is likely because MoveIt is configured to automatically infer the planning scene from sensor data. This makes it very slow to compute IK solutions, which are used to color the gripper markers in RViz. To eliminate this behavior, run MoveIt with a dummy sensor:

<include file="$(find pr2_moveit_config)/launch/move_group.launch" machine="c2">
  <arg name="moveit_octomap_sensor_params_file" value="$(find my_package)/config/sensors_dummy.yaml"/>
</include>

Where sensors_dummy.yaml looks like this:

sensors:
    - sensor_plugin: occupancy_map_monitor/PointCloudOctomapUpdater
      point_cloud_topic: /head_mount_kinect/depth_registered/pointsdummy
      max_range: 5.0
      point_subsample: 10
      padding_offset: 0.1
      padding_scale: 1.0
      filtered_cloud_topic: filtered_cloud

Running tests (not currently working)

Desktop

rostest pr2_pbd_interaction test_endtoend.test

PR2

roscd pr2_pbd_interaction
python test/test_endtoend_realrobot.py

Code coverage (not currently working)

After running the tests, you can view code coverage by opening ~/.ros/htmlcov/index.html with a web browser. Note that you can also view code coverage for normal execution by passing coverage:=true when launching pr2_pbd_backend.

With an account setup at Coveralls, edit the .coveralls.yml with your repo_token, and track coverage there by running coveralls --data_file ~/.ros/.coverage.

Contributing

Before creating a pull request, please do the following things:

0. Lint your Python to pep8 standards by running pep8 file1 file2 ....
1. Optionally format all your Python code with yapf and all your C++ code with clang-format. See the HCR Lab's auto code formatting guide.
2. Run the tests on your desktop (see above).

(Untested) To lint all python files in common directories, run the tests on the desktop, open up code coverage with Google Chrome, and send the results to Coveralls (assuming Coveralls account and .coveralls.yml correctly setup), we have provided a script:

$ roscd pr2_pbd_interaction; ./scripts/test_and_coverage.sh

Questions, feedback, improvements

Please use the Github issues page for this project.