SLAM via Variable Reduction from Constraint Maps

- The two dominant forms of SLAM are based on Extended Kalman Filtering and Consistent Pose Estimation. We show that these are particular subsets of a more general view of the SLAM problem, in which variables representing all robot poses and features are kept. The general technique of variable reduction is a unifying view of these methods that is mathematically sound, and which enables us to explore other interesting and computationally compelling forms for solving SLAM problems.

• Type: Conference
• Year: 2005
• Where: ICRA
• Authors: Kurt Konolige
• Keywords: Consistent Pose Estimation, ICRA 2005, Kalman Filtering, Robotics, Slam Problems