NDLI: Recognition of inside pipeline geometry by using monocular camera and PSD sensors

Content Provider	IEEE Xplore Digital Library
Author	Yun Seok Choi Ho Moon Kim Jung Seok Suh Hyeong Min Mun Seung Ung Yang Chan Min Park Hyouk Ryeol Choi
Copyright Year	2014
Description	Author affiliation: Dept. of Mech. Eng., Sungkyunkwan Univ., Suwon, South Korea (Yun Seok Choi; Ho Moon Kim; Jung Seok Suh; Hyeong Min Mun; Seung Ung Yang; Chan Min Park; Hyouk Ryeol Choi)
Abstract	To deploy an untethered robot inside pipelines autonomously, it is prerequisite to recognize pipeline elements such as straight pipeline, elbow, T-branch and miter. This paper presents an algorithm for recognizing pipeline elements using a monocular camera and PSD (Position Sensitive Device) sensors. Previously, we have presented a method that uses special features of the pipelines (such as elbows or branches) as landmarks by recognizing the shadows of the elbows and branches. Though it is effective, it has limitations and we propose a method of using PSD sensors as a supplementary sensor to overcome the weakness. The method is easy to implement, but helps us collect accurate information necessary for navigating inside pipelines without heavy computation. The method is composed of two parts, which is the method for distinguishing T-branch and miter and searching the direction in T-branch and elbow respectively. The design for the sensing module is presented and the algorithm for recognition procedures is addressed. The sensing module is implemented in an in-pipe robot, called MRINSPECT VI, and its performances are validated.
Starting Page	634
Ending Page	639
File Size	1755008
Page Count	6
File Format	PDF
e-ISBN	9781479957361
DOI	10.1109/AIM.2014.6878150
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-08
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pipelines Robot sensing systems Elbow Cameras Image processing
Content Type	Text
Resource Type	Article

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