Earticle

초록

영어

We discuss the current technology behind automatic selection of landmarks by simultaneous localization and mapping (SLAM), using a single camera in an unfamiliar indoor environment, and we propose an improved method. As currently implemented, automatic landmark selection by vision-based SLAM results in many useless landmarks, because features of the image are distinguished from the surrounding environment and are detected repeatedly. These useless landmarks create a serious problem for the SLAM system because they complicate data association. To solve this problem, we propose a method in which a robot initially collects landmarks through automatic detection while traversing the entire area where the robot performs SLAM and then, through clustering, selects only those landmarks that exhibit high rarity. This enhances system performance. Experimental results showed that this method of automatic landmark selection results in a high-rarity landmark being selected. Our method improves the performance of SLAM compared to conventional methods, an increases the accuracy of data associations.

목차

Abstract
 1. Introduction
 2. The Proposed Method
  2. 1. Clustering with the visual feature value
  2. 2. Landmark selection using clustering
 3. Experimental Results
 4. Conclusions
 References

키워드

저자

• Chuho Yi [ Future IT R&D Lab, LG Electronics, Korea ]
• Yongmin Shin [ Home Appliance R&D Lab, LG Electronics, Korea ]
• Jungwon Cho [ Department of Computer Education, Jeju National University, Korea ] Corresponding author.

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605