@inproceedings{974d2d5e7f2146e2a0dea889ae8d0d0f,
title = "Performance improvement of outdoor localization using elevation moment of inertia (EMOI)",
abstract = "This research proposes a novel approach to outdoor localization based on map matching. The main map for localization is an elevation map which is a grid map with elevation information on each cell. This research presents an elevation moment of inertia (EMOI) which represents the distribution of elevation around a robot in the elevation map. A robot continues to build a local elevation map using a laser sensor and calculates its EMOI. This EMOI is then compared with the EMOIs for all cells of the given reference elevation map to find a robot pose with respect to the reference map. The experimental results of particle filter-based localization show that the proposed EMOI-based approach can be successfully used for outdoor localization with an elevation map.",
keywords = "Elevation map, Monte Carlo localization, Outdoor localization",
author = "Kwon, {Tae Bum} and Song, {Jae Bok} and Lee, {Yong Ju}",
year = "2010",
language = "English",
isbn = "9784990288044",
series = "Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10",
pages = "144--147",
booktitle = "Proceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10",
note = "15th International Symposium on Artificial Life and Robotics, AROB '10 ; Conference date: 04-02-2010 Through 06-02-2010",
}