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RUNNING.md

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Since you will need at least 5 terminals to run this project my suggestion is to use a package like terminator.

  1. Launch the simulation environment roslaunch robotino_simulations world.launch here.

    1. Select the desired environment with name:=<arg>. We tested our work with name:="cafe" and name:="small_house" x:=-2.0.

      .world files are placed in robotino_simulations/worlds/

    2. This node takes care also of launching the nodes for generating the necessary ground truth transforms

    3. In case a shift is needed (like with the AWS's small_house) the robot_ekf in robotino_description/launch/robotino.launch should be adapted to get the corrispondent starting pose so that groundtruth can reflect this shift

  2. Run the MPC: roslaunch robotino_mpc robotino_mpc.launch. Parameters in robotino_mpc/cfg/nmpc.yaml will be used in the code to configure mainly the topics while NMPC constraints can be configured either dynamically (rosrun rqt_reconfigure rqt_reconfigure) or by editing the robotino_mpc/cfg/NonLinearMPC.cfg file. Note that the latter require a catkin_make.
  3. Run RTABMap: roslaunch robotino_simulations rtabmap.launch which is here. Many things will be launched here.
    1. move_base and the costmap converter found here. The parameters are placed in robotino_simulations/config
    2. The "main" mapping.launch file contains:
      • libpointmatcher odometry node
      • rgbd_sync node (from RTABMap)
      • config parameters of RTABMap
    3. the argument delete:=-d lets the user delete the previously generated db at launch
    4. the default folder of the db is .ros/rtabmap.db (setted with the db argument)
    5. RTABMap parameters can be edited directly in robotino_simulations/launch/mapping.launch
    6. RTABMapViz (the visualization tool of RTABMap) is currently commented in robotino_simulations/launch/mapping.launch. Note that with this enabled performance will suffer most probably requiring RTABMap to use its memory management techniques.
    7. Note that some arguments, like "compressed" (which is triggerred by remote:=true) are useful only in case of distributed systems and real robot scenarios
  4. [optional] Run the logger: rosrun robotino_simulations rtabmap_eval.py. This will log odometry, loop closures, map entropy, explored space, wheels rotations in different "npy" files saved on the node running location.
  5. Run the active node: roslaunch active_slam active_node.launch. This will launch the frontier extraction and the map information optimizer.
  6. [optional] Run the features' follower: roslaunch robotino_camera_heading best_heading.launch. The camera specifics are placed in robotino_simulations/config/camera.yaml
  7. The FSM is launched with roslaunch robotino_fsm robotino_fsm.launch kind:=2.
    • With kind you can select the utility [see the paper for reference]:
      • 2: Shannon
      • 5: Dynamic weight with obstacles
      • 7: Interpolation
      • 9: Shannon with obstacles
    • With only_last:=true/false you can decide if the system should use only the last waypoint to chose the path or use the whole information.
    • With weighted_avg:=true/false you can switch between weighted avg and weighted sum as total utility of a path
    • With pre_fix:=true/false you can decide if the system should pre-optimize the heading after choosing the path to follow. Only applicable if only_last:=true
    • With mid_optimizer:=true/false you can turn on/off the optimization procedure for the next waypoint.