Delivery robot

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.

Demo Video

SLAM: Structure of System

Navigation: Structure of System

Step 0: Understand some basics and compile the package

$ 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

Step 1: Configure laser scanner

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.

Step 2: Configure your motors, encoders, and PID controller

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.

Step 3: Test your hardware

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.

Step 4: SLAM!

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

Step 5: Navigation

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

gangooteli / delivery_bot