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논문 기본 정보

자료유형
학술저널
저자정보
Jihye Moon (University of Science and Technology) Hoesung Yang (University of Science and Technology) Kangbok Lee (University of Science and Technology) Seungil Myong (University of Science and Technology)
저널정보
제어로봇시스템학회 제어로봇시스템학회 논문지 제어로봇시스템학회 논문지 제25권 제1호
발행연도
2019.1
수록면
88 - 97 (10page)
DOI
10.5302/J.ICROS.2019.18.0116

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초록· 키워드

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In this paper we propose five techniques applying the Teager-Kaiser energy operator(TKEO) to eliminate gyro drifts with a waist-worn IMU sensor for infra-less pedestrian dead reckoning (PDR). For providing the service to firefighters in a variety of environments, in this research, we selected a low-cost IMU sensor and used acceleration and gyro. The PDR consists of walking distance and direction estimation processes, in the distance estimation process, the peak and zero crossing detection algorithms were used to detect the steps, and the walking distance was calculated using a fuzzy interface system. For estimating the correct direction, the roll and pitch drifts were eliminated by using an extended Kalman filter. In the process, we developed a yaw drift reduction algorithm that consists of two filters and devised three techniques with TKEO. The drift was modeled as a linear function and reduced with the three techniques, and the extra noises were eliminated by the filters. To compare the existing work, the heuristic drift reduction (HDR) was implemented. In the experiments, after each walk along 580 m and 234 m, the proposed algorithm reported position errors of 0.37% and 0.29%, which exceeded the 2.31% and 6.14% of the HDR.

목차

Abstract
I. INTRODUCTION
II. RELEVANT WORKS
III. METHODOLOGY
IV. EXPERIMENT AND RESULTS
V. COMPARISON WITH THE EXISTING METHOD
VI. CONCLUSION AND FUTURE WORKS
REFERENCES

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UCI(KEPA) : I410-ECN-0101-2019-003-000325008