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SLAM for Dummies

1 slam for Dummies A Tutorial Approach to Simultaneous Localization and Mapping By the Dummies S ren Riisgaard and Morten Rufus Blas 2 1. Table of contents 1. TABLE OF 2. INTRODUCTION ..4 3. ABOUT slam ..6 4. THE THE THE RANGE MEASUREMENT 5. THE slam PROCESS ..10 6. LASER DATA ..14 7. ODOMETRY DATA ..15 8. LANDMARKS ..16 9. LANDMARK EXTRACTION ..19 SPIKE LANDM MULTIPLE 10. DATA ASSOCIATION ..25 11. THE EKF ..28 OVERVIEW OF THE THE The system state: X ..29 The covariance matrix: The Kalman gain: The Jacobian of the measurement model: H ..31 The Jacobian of the prediction model: A ..33 The slam specific Jacobians: Jxr and The process noise: Q and The measurement noise: R and V.

SLAM consists of multiple parts; Landmark extraction, data association, state estimation, state update and landmark update. There are many ways to solve each of ... based on these features. These features are commonly called landmarks and will be explained along with the EKF in the next couple of chapters.

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