9th International Conference on ICT for Sustainable Development

Authors - Ritesh Vernekar, Ashok S. D., Raghuttam P. B., Nalini C. I., P.C.Nissimagoudar
Abstract - This study employs the Velodyne VLP-16 LiDAR sensor alongside the LeGO-LOAM algorithm to generate high-definition (HD) maps. Known as LeGO-LOAM HD, our approach focuses on accurately estimating the posture of objects in real-time across different environments. Lightweight nature of our architecture enables efficient posture evaluation on low-power embedded systems. LeGO-LOAM HD effectively utilizes the ground plane for point cloud segmentation and optimization, effectively eliminating noise and identifying planar and edge characteristics. To modify the posture with six degrees of freedom between consecutive scans, a twostep Levenberg-Marquardt optimization strategy is employed. Comparative tests have proven that LeGO-LOAM HD delivers reliable outcomes while demanding less processing power. This system has been seamlessly integrated into a SLAM framework designed to cater to various mapping applications. By introducing a customized strategy, this research contributes to the field of autonomous navigation and mapping, enhancing the creation of high-definition maps even in challenging conditions.