These repo includes different algorithms for mapping using lidar on Turtlebot. R7auto_nav implements the code that was used in the demo and integrated the firing mechanism.
R2auto_nav is implements basic unmapped area detected, R3 and R4 are duplicates of R2. R5 attempts to implement breath first search and has worked in gazebo but not on actual map. R6 and R7 implements wall following algorithm. R6 takes the turtlebot as the front when moving forward while R7 takes the payload as the front.
Information about the turtlebot3 burger used can be found here.
Installation can be found here (Make sure to click on Foxy tab).
- Under ~/colcon_ws/build/auto_nav, do
git clone https://github.com/ideasxiang/r2auto_nav.git - Connect to Wifi hotspot
- SSH into turtlebot using
sshrp - Run
rosbuin terminal connected to Turtlebot - Run
rslamin another terminal - Open another terminal and
sshrp - Copy the code for fly_sub3.py onto the rpi on Turtlebot and edit the port connected to thermal sensor (See below to find the port used)
- Run
python3 fly_sub3.pyin the same terminal - Open another terminal and
sshrp - Copy the code for fly_pub3.py onto the rpi on Turtlebot and edit the port connected to thermal sensor (See below to find the port used)
- Run
python3 fly_pub3.pyin the same terminal - In a new terminal,
cd ~/colcon_wsand docolcon build(Ensure that installation for Turtlebot3 Foxy is done) ros2 run auto_nav r7auto_navto run the wall following algorithm (Ensure in the folder auto_nav that setup.py has correct code)- Voilà you are done
- Connect MLX90614 evaluation board with FTDI Basic Breakout to rpi on turtlebot using USB cable
- Open terminal in ubuntu
sudo apt-get install minicomdmesg | grep tty- Note the tty port used e.g. ttyUSB1
- Open r7auto_nav.py file
- Search for
threshold = float(ambient_temp) + 0.5 - Change it to
threshold = float(ambient_temp) + 1.0or whichever value - Run
cd ~/colcon_ws - Run
colcon build