Intensity enhanced for solid-state-LiDAR in simultaneous localization and mapping

Abstract

Solid-state light detection and ranging (LiDAR) has the advantages of low cost, small size and strong practicability. However, it faces challenges in simultaneous localization and mapping applications due to its small field of view and irregular scanning patterns. A solid-state LiDAR simultaneous localization and mapping system containing intensity information is proposed. In order to solve the irregular scanning characteristics of solid-state LiDAR, we introduce a data preprocessing framework and add intensity feature points to the front-end odometer. This improves the accuracy and robustness of positioning when geometric feature points are scarce, thus solving the problem of feature point degradation caused by a finite field of view. In the back-end optimization stage, we combine the geometric feature residuals with the intensity feature residuals through the proposed consistent difference function, so that the system can maintain good performance even in challenging environments. Finally, we conducted an extensive evaluation of the proposed algorithm on official datasets and various datasets collected from multiple platforms, and the results confirmed the validity of our approach. Compared with the corresponding method, in indoor scenes, the absolute trajectory error and relative attitude error are decreased by 54.5% and 5.3%. In outdoor scenes, the absolute trajectory error and relative attitude error are decreased by 29.6% and 58.8%.

Keywords

Solid-state lidar / intensity / localization / optimization