Welcome to cellphone robot project! This is part of Project Cellphone robot : a RPi-based navigation robot. In our project we decide to use Raspberry Pi 3 Model B , a single-board computer with considerate computation power. Read wiki for concrete details.

Our robot is able to accomplish the following task:

• Build an map while moving around
• Receive goal location from android app and navigate to the goal based on the map built

The android app can be found here.

$ cd ~/catkin_ws
$ catkin_make -DCMAKE_BUILD_TYPE=Release -j1

If you plan to run your packages on multi-machines, read start remote node/rviz and start launch file for remote machine

You ought to configure your favorite laser scanner and publish the reading in the form of LaserScan

# Single scan from a planar laser range-finder
#
# If you have another ranging device with different behavior (e.g. a sonar
# array), please find or create a different message, since applications
# will make fairly laser-specific assumptions about this data

Header header            # timestamp in the header is the acquisition time of 
                         # the first ray in the scan.
                         #
                         # in frame frame_id, angles are measured around 
                         # the positive Z axis (counterclockwise, if Z is up)
                         # with zero angle being forward along the x axis
                         
float32 angle_min        # start angle of the scan [rad]
float32 angle_max        # end angle of the scan [rad]
float32 angle_increment  # angular distance between measurements [rad]

float32 time_increment   # time between measurements [seconds] - if your scanner
                         # is moving, this will be used in interpolating position
                         # of 3d points
float32 scan_time        # time between scans [seconds]

float32 range_min        # minimum range value [m]
float32 range_max        # maximum range value [m]

float32[] ranges         # range data [m] (Note: values < range_min or > range_max should be discarded)
float32[] intensities    # intensity data [device-specific units].  If your
                         # device does not provide intensities, please leave
                         # the array empty.

For our project, we use Neato XV-11 sensor. For more details, see here.

If you publish your message to /scan, you should be able to see the lidar reading visualization after running rviz.

We provide two options for converting reference velocity published to topic \cmd_vel to actual motions of robots:

• a high-level ROS-package: This package encoder reading and output control effort through DCmotor class defined in hardware.py.

  Note: The system will be susceptible to delay and timeout. I would recommend use external hardware with real ISR to get encoder readings and output PWM signal. However, it is easier to debug in ROS

• ROS arduino bridge: We use arduino UNO to run PID control for motors and let it communicate with ROS using serial communication. If you decide not to use

Note: If you decide to use your own package, you should also output Odometry Message and tf from odom to base_link.

We provide two scripts to generate reference velocity for motors:

• key_publisher.py: It publishes pressed keys to topic \action.

• key_to_twist_ramp: It subscribes to \action and publishes reference speed to \cmd_vel.

Open ros_cellphonerobot/launch/slam.launch and configure your hardware nodes.

Then run roslaunch ros_cellphonerobot slam.launch in your terminal.

Tweak parameter setting in your mapping_default.launch.

Run Rviz to make sure SLAM is generating desired occupancy grid in \maphector. After that, start the key_publisher to move your robot around.

Run the following to save the occupancy grid.

rosrun map_server map_saver -f mapname /map:=/maphector

Change the map to be published in cellphonerobot/launch/move_base.launch

  <node name="map_server" pkg="map_server" type="map_server" args="$(find ros_cellphonerobot)/map/map_name.yaml" output="screen"/>

Try running roslaunch ros_cellphonerobot slam.launch in your terminal.

Tweak your parameter setting.

• Start rviz

• Click 2D pose estimate and see if the lidar reading align with the map.

• Click 2D Nav Goal to check the planning and actual paths