2A1-M06 街路樹などの複雑な形状に適応したマップマッチングによる自己位置推定(移動ロボットの自己位置推定と地図構築)

概要

論文の詳細を見る
This paper describes a localization method with 3D map matching. There are various types of conventional localization methods, but relatively large number of conventional methods are weak on high spatial frequency shapes. In outdoor environments, there are many trees and bushes. These branches and leaves have complicated shapes, and the spatial frequency is high. Therefore localization methods adapted to high spatial frequency shapes are required for outdoor localization. We developed a new localization method with 3D map matching. In our method, the spatial frequency of point clouds is reduced, and broader directed edge points are extracted. Then ICDP algorithm matches directed edge points utilizing constraint of gravity direction. We evaluated localization errors on Tsukuba Challenge 2010. The maximum error was 0.675m, it was confirmed that our proposed method is accurate.
一般社団法人日本機械学会の論文
2011-05-26