Earticle

초록

영어

This paper shows how effectively sonar data can be worked with approaches suggested for the indoor SLAM (Simultaneous Localization And Mapping). A sonar sensor occasionally provides wrong distance range due to the wide beam width and the specular reflection phenomenon. To overcome weak points enough to use for the SLAM, several approaches are proposed. First, distance ranges acquired from the same object have been stored by using the FPA (Footprint-association) model, which associates two sonar footprints into a hypothesized circle frame. Using the Least Squares method, a line feature is extracted from the data stored through the FPA model. By using raw sonar data together with the extracted features as observations, the visibility for landmarks can be improved, and the SLAM performance can be stabilized. Additionally, the SP (Symmetries and Perturbations) model, a representation of uncertain geometric information that combines the probability theory and the theory of symmetries, is applied in this paper. The proposed methods have been tested in a real home environment with a mobile robot.

목차

Abstract
 1. Introduction
 2. Feature Extraction
  2.1 Ultrasonic Sensor
  2.2 Footprint-association(FPA) Model
  2.3 Feature Extraction through Least Square
 3. SLAM
  3.1 SP Model
  3.2 Observations
  3.3 Map Management
  3.4 Framework of SLAM
 4. Experimental Results
 5. Conclusion
 Acknowledgment
 References

키워드

저자

• 이세진 [ Se-Jin Lee | 경일대학교 로봇응용학과 ]
• 이경민 [ Kyoungmin Lee | Dept. of Computer Science, Naval Postgraduate School ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국기계항공기술학회지(구 한국기계기술학회지) [Journal of the Korean Society of Mechanical and Aviation Technology ]

• 간기

  격월간

• pISSN

  1229-604X

• eISSN

  2508-3805

• 수록기간

  1999~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 550 DDC 620