Experimental Implementation of an Invariant Extended Kalman Filter-based Scan Matching SLAM
arXiv:1403.5195v19 citations
Originality Synthesis-oriented
AI Analysis
This work addresses localization and mapping for robotics, but it is incremental as it applies an existing IEKF method to a specific hardware setup.
The authors tackled the scan matching SLAM problem by applying an Invariant Extended Kalman Filter (IEKF) to a wheeled robot, achieving successful experimental validation.
We describe an application of the Invariant Extended Kalman Filter (IEKF) design methodology to the scan matching SLAM problem. We review the theoretical foundations of the IEKF and its practical interest of guaranteeing robustness to poor state estimates, then implement the filter on a wheeled robot hardware platform. The proposed design is successfully validated in experimental testing.