Abstract

Lidar (also known as light detection and ranging) and inertial measurement unit (IMU) have become the core components in simultaneous localization and mapping (SLAM) system. Aiming at the problems of low accuracy and poor robustness, we propose what we believe is a novel scheme, including a local map matching rule, a plane representation method, and a key frame filtering process. Our solution removes redundant data during the plane fitting process and achieves higher accuracy. Experimental results prove that our method outperforms other popular methods in terms of trajectory errors and robustness under different scenarios.

© 2021 Optical Society of America

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