Simulating and Mapping 3D Environments with 2D Lidar in ROS

Welcome to the repository for our project that explores the world of 3D mapping using 2D Lidar in ROS (Robot Operating System). This project focuses on creating a simulated environment, collecting data with a 2D Lidar, and generating 3D maps using ROS and Gazebo.

Table of Contents

• Overview
• Installation
• Usage
• Results
• Contributing
• License

Overview

In this creative project, a combination of a 2D Lidar, ROS, and Gazebo brought forth a new path in the world of 3D mapping. The project commenced with the design of an innovative robot using a tool called SolidWorks. This robot possessed a unique laser scanner capable of observing from 0 to +60 degrees. Employing a specialized tool, laser data was collected and translated into point-like images. Subsequently, through the integration of ROS and a dedicated library called octomap, these images were transformed into highly detailed 3D maps. This endeavor exemplifies the enhancement of a robot's understanding of its surroundings and its ability to autonomously navigate.

Installation

Follow these steps to set up the project locally:

git clone https://github.com/GutlapalliNikhil/3D-Mapping-Using-2D-LiDAR-ROS.git
cd 3D-Mapping-Using-2D-LiDAR-ROS/src
git clone https://github.com/OctoMap/octomap_mapping.git
git clone https://github.com/OctoMap/octomap_msgs.git
git clone https://github.com/OctoMap/octomap_ros.git
cd ..
catkin_make

Usage

1.Launch the Gazebo simulation with the robot model:

roslaunch Assem1 testing.launch

2. Send the values to the servo motor:

rosrun Assem1 lidar_control_node.py

3. Convert the laserscan to pointcloud:

rosrun Assem1 laserscan_to_pointcloud.py

4. Run the Octomap to get the map:

roslaunch octomap_server octomap_mapping.launch

Contributing

I welcome contributions to improve this project. If you find any issues or have suggestions for enhancements, feel free to submit a pull request or open an issue.