Autonomous-Driving-with-Turtlebot3

Final project :- TurtleBot Path-finding and Automatic Parking

Code structure

1. Wall follower & finding goal

The wall follower class will navigate through its surroundings using a wall follower algorithm. The process consists of the following steps:

• First robot will save the starting position coordinate and start moving towards closest wall.
• The robot will locate the closest wall and save the cordinates.
• It will then follow the wall while avoiding any obstacles.
• Once the robot has completed a full lap of the environment, it will come to a halt and store the all possible parking spot.

2.Mapping

• The mapping class will operate simultaneously with the wall follower function, using LIDAR values to gather information about the environment and its positions.
• It will store data about all detected obstacles in the form of coordinates and keep a record of this information in a file called "ranges.txt" when robot will reach coordinates of nearest position.

3.Trajectory planning

• The path planning class, using the A* algorithm, will take three inputs: the map, the current position of the robot, and the desired destination.
• It will then generate all potential paths, compare them, and choose the shortest path to reach the goal.

4. Path follower

• The path planning class will receive the points of the shortest path generated by the Astar planning class.
• It utilize a PI controller to guide the robot towards the destination along this path.

Project implementation map

Map of Real Enviroment

Map of A* Star Algorithm

Task 1: Path Planning towards starting position and Path Planning towards parking spot

Task 2: Path Planning towards starting position and Path Planning towards parking spot