Fundamental and experimental analysis of mobile robot simultaneous localization and mapping

Jiangdong Sun

doi:10.1117/12.2673181

14 April 2023 Fundamental and experimental analysis of mobile robot simultaneous localization and mapping

Jiangdong Sun

Proceedings Volume 12612, International Conference on Artificial Intelligence and Industrial Design (AIID 2022); 126120W (2023) https://doi.org/10.1117/12.2673181
Event: International Conference on Artificial Intelligence and Industrial Design (AIID 2022), 2022, Zhuhai, China

Abstract

Robots require both high precision localization and mapping solutions in unknown environments. Simultaneous localization and mapping is well matched to the requirement. In this article, the process of transforming SLAM problem into a state estimation problem is presented. Some implementations of SLAM are introduced. EKF-SLAM is easy to implement, but unable to build large maps, and unable to deal with nonlinear errors well. Fast-SLAM introduces particle filtering on the basis of EKF-SLAM, which solves nonlinear errors and increases the computation speed significantly. Graph-SLAM is based on graph optimization, able to build large maps and has good real-time performance. Visual SLAM and semantic SLAM are developing rapidly and will be the key development of SLAM in the future. The characteristics of each method are corroborated in the experimental results.

Citation Download Citation

Jiangdong Sun "Fundamental and experimental analysis of mobile robot simultaneous localization and mapping", Proc. SPIE 12612, International Conference on Artificial Intelligence and Industrial Design (AIID 2022), 126120W (14 April 2023); https://doi.org/10.1117/12.2673181

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