LiDBot (Autonomous Bot for 2D mapping)
Sahil Waje
Electronics and Telecommunication Engineering Atharva College of Engineering
Mumbai,India
wajesahil-extc@atharvacoe.ac.in
Yayati Rupawate
Electronics and Telecommunication Engineering Atharva College of Engineering
Mumbai,India
rupawateyayati-extc@atharvacoe.ac.in
Tej Vesavkar
Electronics and Telecommunication Engineering Atharva College of Engineering
Mumbai,India
vesavkartej-extc@atharvacoe.ac.in
Shreya Pawar
Electronics and Telecommunication Engineering Atharva College of Engineering
Mumbai,India pawarshreya-extc@atharvacoe.ac.in
Dr.Jyoti Gurav
Associate Proffesor Atharva College of Engineering
Mumbai,India jyotigurav@atharvacoe.ac.in
Abstract—This paper introduces an autonomous robotic system that employs LiDAR (Light Detection and Ranging) technology, driven by a Raspberry Pi 4 single-board computer, and seamlessly integrated with the Robot Operating System 2 (ROS2) for the purpose of 2D mapping and Simultaneous Localization and Mapping (SLAM) in indoor environments. The Raspberry Pi 4 serves as the onboard computer, responsible for processing LiDAR data, sensor fusion, control algorithms, and communication with external devices. ROS2 acts as the middleware, ensuring a seamless use of sensors, control algorithms, and visualization tools. The implementation of SLAM algorithms is an important aspect of this project, allowing the robot to construct an intricate 2D map of its environment while concurrently determining its own position within that map. This information proves indispensable for secure and efficient navigation within dynamic indoor surroundings. Furthermore, the autonomous robot adeptly maneuvers through these environments while continually updating its map and self- localization estimations. The paper showcases performance metrics such as map precision, navigation speed and computational efficiency within the provided resources. This research contributes substantively to the domain of robotics by furnishing a practical implementation of an autonomous robot system utilizing LiDAR, Raspberry Pi 4, and ROS2, underscoring its efficiency in 2D mapping and SLAM.
Key Words: LiDBot, Simultaneous Localization and Mapping (SLAM), Light Detection and Ranging(LiDAR), Robot Operating System 2(ROS2), Raspberry Pi4, 2D Mapping.
