Recursive scan-matching SLAM

This paper presents Scan-SLAM, a new generalisation of simultaneous localisation and mapping (SLAM). SLAM implementations based on extended Kalman filter (EKF) data fusion have traditionally relied on simple geometric models for defining landmarks. This limits EKF-SLAM to environments suited to such models and tends to discard much potentially useful data. The approach presented in this paper is a marriage of EKF-SLAM and scan correlation. Landmarks are no longer defined by analytical models; instead they are defined by templates composed of raw sensed data. These templates can be augmented as more data becomes available so that the landmark definition improves with time. A new generic observation model is derived that is generated by scan correlation, and this permits stochastic location estimation for landmarks with arbitrary shape within the Kalman filter framework. The statistical advantages of an EKF representation are augmented with the general applicability of scan matchi...

• Type: Journal
• Year: 2007
• Where: RAS
• Authors: Juan Nieto, Tim Bailey, Eduardo Mario Nebot
• Keywords: Kalman filter, RAS 2007, Scan Correlation, Simultaneous Localisation