Assurance-based Learning-enabled Cyber-Physical Systems

Behaviour Tree complex example with RQT for behaviour trees, RViz and PlotJuggler in the ALC Toolchain

• This video presents how to use the IDE in ALC Toolchain to work and visualize Behaviour Trees
• Run IDELaunch plugin to start IDE first
• Open IDE with the link provided
• Open 5 terminal windows inside:
  1. Start ros-core docker ('cd bluerov/ngc/src/aadocker' and 'source run_roscore.sh')
  2. Start aa_uuvsim docker ('cd bluerov/ngc/src/aadocker' and 'source run_aauuvsim_am.sh' then 'source run_xvfb.sh bluerov')
  3. 'cd bluerov/src/aadocker/aa_uuvsim' and run 'setup_gazebo_ros_connection.sh' then run 'rqt'
  4. 'cd bluerov/src/aadocker/aa_uuvsim' and run 'setup_gazebo_ros_connection.sh' then run 'rosrun plotjuggler PlotJuggler'
  5. 'cd bluerov/src/aadocker/aa_uuvsim' and run 'setup_gazebo_ros_connection.sh' then lanch bluerov RViz
• In RQT open PyTrees Behaviour Tree and select '/BlueROV_tree'
  • The tree will be updated based on the contingency actions
  • Blue nodes are 'Running'
  • Red nodes are 'Failure'
  • Green nodes are 'Success'
• In PlotJuggler start ROS subscription and select topics to listen (e.g. LEC2 AM)
• In RViz the BlueROV can be seen during mission execution