PythonFinalProject

Robot Car: Obstacle Avoidance and Wall Following with LiDAR

This project focuses on developing obstacle avoidance and wall-following algorithms using a LiDAR sensor mounted on a custom-built robot. Designed for navigation in a custom environment, the robot uses LiDAR data to detect and avoid obstacles and maintain a consistent distance from walls, enabling smooth and efficient navigation

Installation

Prequisites

• Linux Ubuntu 22.04

• Ros2 humble

• Nav2

• Gazebo

• Rviz

• Visual studio code

• Cyclone DDS

Step 1: Install ROS 2 Humble

Follow the ROS 2 Humble installation instructions for your operating system if ROS 2 is not already installed.

Step 2: Install Required ROS 2 Packages

Install the necessary ROS 2 packages.

sudo apt-get install ros-humble-ros2-control
sudo apt-get install ros-humble-ros2-controllers
sudo apt-get install ros-humble-xacro
sudo apt-get install ros-humble-ros-gz-*
sudo apt-get install ros-humble-*-ros2-control
sudo apt-get install ros-humble-joint-state-publisher-gui
sudo apt-get install ros-humble-turtlesim
sudo apt-get install ros-humble-robot-localization
sudo apt-get install ros-humble-joy-teleop
sudo apt-get install ros-humble-tf-transformations

Step 3: Install Python Packages

Install Python and additional packages:

sudo apt-get install python3-pip
pip install transforms3d

Run Locally

Clone the project

  git clone git@github.com:shivasamkumar/PythonFinalProject.git

Go to the project directory

  cd proj_wrkspace

build the project

  colcon build 

Source your workspace

  source /opt/ros/humble/setup.bash
  source ~/workspace/install/setup.bash 

Launch the project

Slam algorithm with turtle bot and way point follower

• open terminal emulator in linux ubuntu 22.04 with ros2 and Nav2 pre installed

• Run the commands

 ros2 launch turtlebot3_gazebo turtlebot3_my_world.launch.py 
  

• run the command in the other terminal

  ros2 launch turtlebot3_navigation2 navigation2.launch.py	 use_sim_time:=True map:=/home/shiva/maps/custom_map.yaml"

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NOTE

• Note: You have to use the cyclone DDS processor

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Wall Follower and obstacle avoidance

• Clone the repo into your ros2 workspace 
• Use colcon build select-packages -mobile_robo
• Then launch the launch file using "ros2 launch mobile_robo mobile_robo_launch.py"

Demo

                                  Fig 1.1  Wall Following and Obstacle avoidance

                                                Fig 1.2  Map in Rviz  

                             Fig 1.3 Slam algorithm and waypoint Follower in Gazebo and Rviz 

           Fig 1.4 Gazebo virtual environment

Video

                               This video shows the Demonstation of the project

Future versions

• Implementing IMU sensors and Control algorithm

  Integrating IMU sensors and control algorithm for the coustom robot and also implement sensor fusion algorithms

• Hardware Integration