A Decorrelated Distributed EKF-SLAM System for the Autonomous Navigation of Mobile Robots

This paper proposes a novel distributed EKF-SLAM system that combines the advantages of EKF-SLAM and distributed SLAM systems. The system model of this novel SLAM system has a distributed structure, and each subsystem is a special SLAM system corresponding to every effectively observed landmark by feeding the heading information from a magnetic compass is introduced into the observation equation. Aim at the correlation problem in distributed SLAM system, a decorrelated distributed EKF (DDEKF) was developed to estimate the robot pose and landmarks. DDEKF reconstructs and extends the maximum allocation covariance (MAC) method so that it can be applied to the distributed structure where the number of local filters is dynamically changed. Then, the local filter estimation results are weighted and fused in the main filter to obtain the estimation result. Finally, the experimental tests were performed in an outdoor environment, and the experiment results demonstrate that the proposed novel distributed EKF-SLAM system has a better performance than the existing SLAM system.