Robot localization and mapping problem with unknown noise characteristics

Hamzah Ahmad, Toru Namerikawa

研究成果: Conference contribution

15 被引用数 (Scopus)

抄録

In this paper, we examine the H? ?Filter-based SLAM especially about its convergence properties. In contrast to Kalman Filter approach that considers zero mean gaussian noise, H Filter is more robust and may provide sufficient solutions for SLAM in an environment with unknown statistical behavior. Due to this advantage, H Filter is proposed in this paper, to efficiently estimate the robot and landmarks location under worst case situations. H Filter requires the designer to appropriately choose the noise's covariance with respect to γ to obtain a desired outcome. We show some of the conditions to be satisfy in order to achieve better estimation results than Kalman Filter. From the experimental results, HFilter performs better than Kalman Filter for a case of bigger robot initial uncertainties. Subsequently, this proved that H Filter can provide another available estimation method for especially in SLAM.

本文言語English
ホスト出版物のタイトル2010 IEEE International Conference on Control Applications, CCA 2010
ページ1275-1280
ページ数6
DOI
出版ステータスPublished - 2010
イベント2010 IEEE International Conference on Control Applications, CCA 2010 - Yokohama, Japan
継続期間: 2010 9 82010 9 10

出版物シリーズ

名前Proceedings of the IEEE International Conference on Control Applications

Other

Other2010 IEEE International Conference on Control Applications, CCA 2010
CountryJapan
CityYokohama
Period10/9/810/9/10

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Mathematics(all)

フィンガープリント 「Robot localization and mapping problem with unknown noise characteristics」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル