Exploring Enhanced Localization Techniques: LIDAR-SLAM for Mobile Robots

This project outlines the development of a mobile localization robot using ROS Noetic that is based on Lidar-SLAM technology. Using a RPlidar sensor and the SLAM algorithm, the robot is designed to locate its position and direction in an unknown environment, scanning its surroundings and localizing itself. The system is built with ROS, a popular robotics framework, and operates on the Ubuntu 20.0 virtual OS running on a MacOS Monterey host system, which provides an energy-efficient robotics hardware. The method employed in this study, Lidar-SLAM, creates a 2D representation of the environment and evaluates the robot's location and direction by analysing the point cloud data captured by the Lidar sensor. The robot has a differential drive system, which allows it to move and turn precisely in small places. The Arduino uno microcontroller present on the differential drive communicates with ROS via a USB serial peripheral between the Arduino and macOS host system. The proposed system has the potential to undergo real-world testing by placing the robot in an unfamiliar location and evaluating its performance based on how accurately it can localize and map the surroundings. This project provides a low-cost and small solution for mobile robot localization based on Lidar-SLAM technology, which can be scaled and utilized for a variety of applications including warehouse management, surveillance, and inspection. The ROS-based design enables for simple integration with other robotic systems and provides a comprehensive set of robotics development tools. With its low-cost and energy-efficient features, it offers an ideal base for further enhancing the robotic applications, particularly in remote or resource-constrained areas.