GRID-BASED SCAN-TO-MAP MATCHING FOR ACCURATE SIMULTANEOUS LOCALIZATION AND MAPPING: THEORY AND PRELIMINARY NUMERICAL STUDY

摘要

This paper presents a grid-based scan-to-map matching technique for accurate simultaneous localization and mapping (SLAM). At every acquisition of a new scan, the proposed technique estimates the relative position from which the previous scan was taken, and further corrects its estimation error by matching the new scan to the globally defined map. In order to achieve best scan-to-map matching at each acquisition, the map to match is represented as a grid map with multiple normal distributions (NDs) in each cell. Additionally, the new scan is also represented by NDs, developing a novel ND-to-ND matching technique. The ND-to-ND matching technique has significant potential in the enhancement of the global matching as well as the computational efficiency. Experimental results first show that the proposed technique successfully matches new scans to the map generating very small position and orientation errors, and then demonstrates the effectiveness of the multi-ND representation in comparison to the single-ND representation.