2D Laser SLAM With Closed Shape Features: Fourier Series Parameterization and Submap Joining
Jiaheng Zhao, Tiancheng Li, Tong Yang, Liang Zhao, Shoudong Huang
Abstract
One of the valuable directions in feature based SLAM is to parameterize and estimate features accurately. In the real world, closed shape features are especially common. It is necessary to study the feature based SLAM problem on closed shape features. The main contribution of this letter is a 2D laser SLAM approach with Fourier series based feature parameterization and submap joining. In this letter, the Fourier series are introduced to parameterize irregular closed shape features and the SLAM problem with Fourier series feature parameterization is formulated. A submap joining process is also derived in order to reduce the high dependence on precise initial guess and the computing time. The proposed method has been evaluated on both synthetic and actual data and is able to obtain accurate trajectory and feature boundaries. The practical experiment also shows that our method surpasses Cartographer under certain scenarios. We also show that our method has the ability to be applied to the general environment.