Multi-Sensor SLAM Positioning and Navigation

This paper provides a comprehensive review of advancements in Positioning and Navigation, focusing on the integration of key technologies to enhance operational efficiency and sustainability. The study examines the application of sensors in robotic systems, with particular emphasis on visual Simultaneous Localization and Mapping (SLAM) and LiDAR SLAM technologies. Visual SLAM, which uses monocular or binocular cameras to capture environmental images for navigation and mapping, offers cost-effective solutions but faces challenges such as sensitivity to lighting conditions and high computational demands. LiDAR SLAM, utilizing laser pulses to create precise 3D maps, complements visual SLAM by improving accuracy and robustness. The review also covers the integration of these technologies with deep learning and other advanced algorithms, highlighting their potential to enhance robotic performance and address practical limitations. The paper identifies future research directions aimed at advancing these technologies for more effective and sustainable practices.