A Novel Observability Gramian-Based SLAM

This article addresses the computational complexity problems caused by the high coupling of the full covariance matrix in standard simultaneous localization and mapping (SLAM). First, a covariance intersection (CI) based SLAM system (CI-SLAM) is considered. Based on the CI-SLAM, a jointly uniform observability (JUO) condition is applied to enable the CI-SLAM with sufficient observable ability even in harsh environments. Subsequently, a novel observability Gramian-based CI (OGBCI) based SLAM algorithm (OGBCI-SLAM) is developed. Finally, simulations are presented to demonstrate the effectiveness of the proposed OGBCI-SLAM algorithm.