ENPM661_Project5_RRT

Autonomous robotic exploration based on multiple rapidly-exploring randomized trees

ENPM661 Spring 2022 Section 0101

Jerry Pittman, Jr. UID: 117707120 Maitreya Ravindra Kulkarni, UID: 117506075 jpittma1@umd.edu and mkulk98@umd.edu

Github Repo: https://github.com/jpittma1/ENPM661_Project5_RRT.git

You can see the Towards Data Science Story of this Project

There are three Main steps to be executed in this project.

• Step 1 : Place the Robot in the Environment within Gazebo

• Step 2 : Perform Autonomous exploration (Local RRT and Global RRT) of the environment and generate the Map (SLAM)

• Step 3 : Perform pathplanning and go to goal in the environment

Step 1 : Place the Robot in the Environment within Gazebo

Set your environment variable to the model robot to be used in bashrc file.

export TURTLEBOT3_MODEL=waffle_pi

Execute the given launch to open Gazebo with the given world file and place the robot Turtlebot3 Waffle pi model in it.

roslaunch ros_autonomous_slam turtlebot3_world.launch

Keep this process running always and execute other commands in a different terminal.

Step 2 : Perform Autonomous exploration of the environment and generate the Map

roslaunch ros_autonomous_slam autonomous_explorer.launch
--OR--
roslaunch ros_autonomous_slam autonomous_explorer.launch explorer:=RRT

Run the Autonomous Explorer launch file which executes two tasks for us at the same time:

1. It starts the SLAM node in the Navigation stack with a custom modified RVIZ file to monitor the mapping of the environment.
2. It simultaneously starts the Autonomous explorer which is a Python based controller to move around the robot grazing all the areas whcih helps the SLAM Node to complete the mapping. The default algorithm used for the exploration is RRT algorithm.

The RRT exploration requires a rectangular region around to be defined in the RVIZ window using four points and an starting point for exploration within the known region of the robot. The total five points must be defined in the exact sequence given below using the RVIZ Publish Points option (Top Left, Bottom Left, Bottom Right, Top Right, On/near Robot in white LiDAR visibile region). Source

Monitor the Mapping process in RVIZ window and sit back and relax unitll our robot finishes mapping.

Once you are satisfied with the constructed map, Save the map.

rosrun map_server map_saver -f my_map

The my_map.pgm and my_map.yaml gets saved in your worspace directory. Move these to files to the package's maps folder (catkin_ws\src\ros_autonomous_slam\maps).Now your new map which is basically a occupancy grid is constructed !

Step 3 : Perform pathplanning and go to goal in the environment

We will be using the Navigation stack of the ROS to perform the pathplanning and go to goal using /movebase/goal actions. The given blow launch execution opens up a RVIZ window which shows the Robot location within the previously constructed map.

roslaunch ros_autonomous_slam turtlebot3_navigation.launch

The RVIZ Window shows the robot's local map construction using its Laser sensors with respect to the Global Map previously constructed in Step 2 with help of a cost map.

Setting Goal in the RVIZ Window

• First estimate the initial Pose i.e locating the real robot location with respect to the Map. This can be set in the RVIZ window itself using the 2D Pose Estimate and pointing and dragging the arrow in the current robot's locaion and orientation.
  
• An GOAL point can be set in the RVIZ window itself using the 2D Nav Goal option which will be available in the top window tab.This allows you to set a goal point in the map within the RVIZ environment, then the robot automaticals performs the path palnning and starts to move in its path.