A closed loop path planning and following for Turtlebot3 robot in Gazebo simulator using RRT+APF path planner and differential drive controller.
- RRT - Rapidly Exploring Random Trees
- APF - Artificial Potential Field
Demo video with gazebo simulation youtube
- python 3.6 or above
- numpy
- matplotlib
- opencv
- turtlebot3
Install turtlebot3 packages using instructions from here.
Clone the project folder in your catkin workspace and build the package using following commands
cd catkin_ws/src/
git clone https://github.com/HrushikeshBudhale/rrt_apf_planner_project.git
cd ..
export TURTLEBOT3_MODEL=burger
catkin build rrt_follower
source devel/setup.bash
Launch the nodes using following command
roslaunch rrt_follower turtlebot3_map.launch
# or
roslaunch rrt_follower turtlebot3_map.launch start_x:=1 start_y:=1 start_angle:=0 goal_x:=9 goal_y:=9
On launching the gazebo simulator, running this node will first plan the path and then user can see the the robot moving towards goal location.
- Efficient use of vectorized arrays takes less than 0.5 sec to find path between 2 farthest points in the map.