Simultaneous Localization and Mapping for Mobile Robots in Dynamic Environments

Abstract

This paper presents a new SLAM framework for solving the problem of SLAM in dynamic environments. The landmark location change causes the error of robot pose estimation and landmark mapping. In this paper, we propose Dynamic EKF SLAM based on the independence of the dynamic landmarks. The proposed framework decomposes the SLAM problem into a traditional SLAM problem for the static landmarks and individual SLAM problems for the dynamic landmarks. Therefore, in the dynamic environments, it is able to minimize the error caused by the dynamic landmarks and reduce the uncertainty in the robot pose and the landmark locations. The simulation results show the validity and robustness of the proposed approach in terms of robot path estimation error, landmark location mapping error, and the variances of robot and landmarks.