RobotSLAM: A Lightweight Low-cost 3D LiDAR SLAM Handheld Device

Abstract

As the importance of Mobile Laser Scanning (MLS) technology in 3D mapping continues to grow, the development of low-cost, portable devices to address the complex mapping needs of various environments has become a key area of research in the industry. Currently, handheld MLS devices are increasingly being applied in a wide range of surveying tasks, especially in small outdoor spaces, indoor environments, and narrow areas with limited accessibility. This study proposes the development of a novel handheld mobile laser scanning system, RobotSLAM Lite. The system integrates a LiDAR sensor and a fisheye camera through a multi-sensor fusion approach to enable Simultaneous Localization and Mapping (SLAM). A dedicated data processing platform, RobotSLAM Engine, has also been developed to generate and optimize point cloud maps with true-color information. To evaluate the system’s performance, the study was conducted at the Norwegian University of Science and Technology, utilizing an experimental building and nearby roads as test sites. High-precision point cloud data obtained from a terrestrial laser scanner (Leica ScanStation P30 TLS) and RTK measurement Ground Control Points (GCPs) were used as reference benchmarks. A four-metric evaluation framework, comprising absolute coordinate deviation, point cloud density distribution, surface roughness, and cloud-to-cloud distance (C2C), was established to quantitatively analyze the mapping accuracy of the device in indoor and outdoor scenarios at various scales. Experimental results indicate that RobotSLAM Lite provides centimeter-level accuracy while significantly reducing both equipment cost and operational complexity, offering a new technological solution for 3D mapping in both large and small spaces.