IAES International Journal of Robotics and Automation (IJRA) Vol. 13, No. 1, March 2024, pp. 41~49 ISSN: 2722-2586, DOI: 10.11591/ijra.v13i1.pp41-49  41 Journal homepage: http://ijra.iaescore.com Robot indoor navigation: comparative analysis of LiDAR 2D and visual SLAM Hind Messbah, Mohamed Emharraf, Mohammed Saber National School of Applied Sciences, SmartICT Lab, Mohammed First University, Oujda, Morocco Article Info ABSTRACT Article history: Received Sep 22, 2023 Revised Nov 27, 2023 Accepted Dec 18, 2023 Robot indoor navigation has become a significant area of research and development for applications such as autonomous robots, smart homes, and industrial automation. This article presents an in-depth comparative analysis of LiDAR 2D and visual sensor simultaneous localization and mapping (SLAM) approaches for robot indoor navigation. The increasing demand for autonomous robots in indoor environments has led to the development of various SLAM techniques for mapping and localization. LiDAR 2D and visual sensor-based SLAM methods are widely used due to their low cost and ease of implementation. The article provides an overview of LiDAR 2D and visual sensor-based SLAM techniques, including their working principles, advantages, and limitations. A comprehensive comparative analysis is conducted, assessing their capabilities in terms of robustness, accuracy, and computational requirements. The article also discusses the impact of environmental factors, such as lighting conditions and obstacles, on the performance of both approaches. The analysis’s findings highlight each approach’s strengths and weaknesses, providing valuable insights for researchers and practitioners in selecting the appropriate SLAM method for robot indoor navigation based on specific requirements and constraints. Keywords: Indoor LiDAR 2D Localization Mapping Navigation Visual sensor This is an open access article under the CC BY-SA license. Corresponding Author: Hind Messbah National School of Applied Sciences, SmartICT Lab, Mohammed First University BP 669 Bd Mohammed VI, Oujda 60000, Morocco Email: h.mesbahi@ump.ac.ma 1. INTRODUCTION Robot indoor navigation involves using robots to move through an indoor space and perform various tasks such as cleaning, delivery, or inspection. Typically used as assistants in interior environments, service robots include the "Roomba" vacuum cleaner, the personal robot PR2 service robot, the Husky, unmanned ground vehicle (UGV) robot, and many others [1]. There are several ways in which robots can navigate indoors, including Sensor-based navigation, this method involves using sensors such as cameras, laser range finders, or sonar to detect obstacles and create a map of the environment [2]. The robot can then use this map to plan its path and avoid obstacles, Map-based navigation: This method involves using a pre-built map of the environment, which the robot can use to plan its path [3]. This requires the robot to have access to the map and the ability to locate itself within the map, hybrid navigation: This method combines sensor-based and map-based navigation to provide more accurate and efficient navigation. The robot uses sensors to detect obstacles and updates its map in real time, allowing it to adjust its path as needed. Overall, robot indoor navigation is an important technology for various industries such as manufacturing, healthcare, and hospitality. It allows for the automation of tasks that were previously performed by humans, leading to increased efficiency and cost savings. When the environment is complex and continually changing, navigation becomes more challenging. The simultaneous localization and mapping