A new seam-tracking algorithm through characteristic-point detection for a portable welding robot

Doyoung Chang, Donghoon Son, Jungwoo Lee, Donghun Lee, Tae Wan Kim, Kyu Yeul Lee, Jongwon Kim

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

The welding task in double-hulled structures in shipyards and in steel-frame structures is hazardous and difficult due to the toxic gas and limited workspace. Therefore, many efforts have been undertaken for automation. The main challenge for automation is the development of a simple and robust seam-tracking algorithm that can be applied to a portable welding robot that operates under irregular and diverse task conditions in the workspace. We developed a seam-tracking algorithm for weaving weld path planning using a laser displacement sensor. The goal of the proposed algorithm is to detect the seam of single-butt welding with manually tack-welded non-zero gaps. The focus is on keeping the algorithm simple and affordable so that it can be applied to portable robots that operate in hazardous fields. The algorithm consists of four steps: scanning, filtering, generation of the reference points, and path planning. In the scanning process, the depth data of a cross-section of the seam profile is obtained. Next, a Gaussian filter is used to remove noise from the raw data. A differential characteristic-point detection algorithm is applied to the filtered data to detect the reference points that represent the shape and location of the gap to be welded. Finally, path planning for single-V butt multi-pass welding is done based on the detected reference points. A portable four-axis welding robot is built using the developed algorithm. The algorithm is validated through welding experiments regarding a single-V butt welding task with a manually tack-welded non-zero gap. Crown

Original languageEnglish (US)
Pages (from-to)1-13
Number of pages13
JournalRobotics and Computer-Integrated Manufacturing
Volume28
Issue number1
DOIs
StatePublished - Feb 1 2012
Externally publishedYes

Fingerprint

Welding
Robot
Robots
Reference Point
Path Planning
Motion planning
Butt welding
Workspace
Automation
Scanning
Gaussian Filter
Data Depth
Frame Structure
Shipyards
Irregular
Steel
Welds
Cross section
Filtering
Laser

Keywords

  • Characteristic-point detection
  • Laser displacement sensor
  • Seam-tracking algorithm
  • Welding robot

ASJC Scopus subject areas

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

Cite this

A new seam-tracking algorithm through characteristic-point detection for a portable welding robot. / Chang, Doyoung; Son, Donghoon; Lee, Jungwoo; Lee, Donghun; Kim, Tae Wan; Lee, Kyu Yeul; Kim, Jongwon.

In: Robotics and Computer-Integrated Manufacturing, Vol. 28, No. 1, 01.02.2012, p. 1-13.

Research output: Contribution to journalArticle

Chang, Doyoung ; Son, Donghoon ; Lee, Jungwoo ; Lee, Donghun ; Kim, Tae Wan ; Lee, Kyu Yeul ; Kim, Jongwon. / A new seam-tracking algorithm through characteristic-point detection for a portable welding robot. In: Robotics and Computer-Integrated Manufacturing. 2012 ; Vol. 28, No. 1. pp. 1-13.
@article{e9c373bfc4e042c882187f56222ba785,
title = "A new seam-tracking algorithm through characteristic-point detection for a portable welding robot",
abstract = "The welding task in double-hulled structures in shipyards and in steel-frame structures is hazardous and difficult due to the toxic gas and limited workspace. Therefore, many efforts have been undertaken for automation. The main challenge for automation is the development of a simple and robust seam-tracking algorithm that can be applied to a portable welding robot that operates under irregular and diverse task conditions in the workspace. We developed a seam-tracking algorithm for weaving weld path planning using a laser displacement sensor. The goal of the proposed algorithm is to detect the seam of single-butt welding with manually tack-welded non-zero gaps. The focus is on keeping the algorithm simple and affordable so that it can be applied to portable robots that operate in hazardous fields. The algorithm consists of four steps: scanning, filtering, generation of the reference points, and path planning. In the scanning process, the depth data of a cross-section of the seam profile is obtained. Next, a Gaussian filter is used to remove noise from the raw data. A differential characteristic-point detection algorithm is applied to the filtered data to detect the reference points that represent the shape and location of the gap to be welded. Finally, path planning for single-V butt multi-pass welding is done based on the detected reference points. A portable four-axis welding robot is built using the developed algorithm. The algorithm is validated through welding experiments regarding a single-V butt welding task with a manually tack-welded non-zero gap. Crown",
keywords = "Characteristic-point detection, Laser displacement sensor, Seam-tracking algorithm, Welding robot",
author = "Doyoung Chang and Donghoon Son and Jungwoo Lee and Donghun Lee and Kim, {Tae Wan} and Lee, {Kyu Yeul} and Jongwon Kim",
year = "2012",
month = "2",
day = "1",
doi = "10.1016/j.rcim.2011.06.001",
language = "English (US)",
volume = "28",
pages = "1--13",
journal = "Robotics and Computer-Integrated Manufacturing",
issn = "0736-5845",
publisher = "Elsevier Limited",
number = "1",

}

TY - JOUR

T1 - A new seam-tracking algorithm through characteristic-point detection for a portable welding robot

AU - Chang, Doyoung

AU - Son, Donghoon

AU - Lee, Jungwoo

AU - Lee, Donghun

AU - Kim, Tae Wan

AU - Lee, Kyu Yeul

AU - Kim, Jongwon

PY - 2012/2/1

Y1 - 2012/2/1

N2 - The welding task in double-hulled structures in shipyards and in steel-frame structures is hazardous and difficult due to the toxic gas and limited workspace. Therefore, many efforts have been undertaken for automation. The main challenge for automation is the development of a simple and robust seam-tracking algorithm that can be applied to a portable welding robot that operates under irregular and diverse task conditions in the workspace. We developed a seam-tracking algorithm for weaving weld path planning using a laser displacement sensor. The goal of the proposed algorithm is to detect the seam of single-butt welding with manually tack-welded non-zero gaps. The focus is on keeping the algorithm simple and affordable so that it can be applied to portable robots that operate in hazardous fields. The algorithm consists of four steps: scanning, filtering, generation of the reference points, and path planning. In the scanning process, the depth data of a cross-section of the seam profile is obtained. Next, a Gaussian filter is used to remove noise from the raw data. A differential characteristic-point detection algorithm is applied to the filtered data to detect the reference points that represent the shape and location of the gap to be welded. Finally, path planning for single-V butt multi-pass welding is done based on the detected reference points. A portable four-axis welding robot is built using the developed algorithm. The algorithm is validated through welding experiments regarding a single-V butt welding task with a manually tack-welded non-zero gap. Crown

AB - The welding task in double-hulled structures in shipyards and in steel-frame structures is hazardous and difficult due to the toxic gas and limited workspace. Therefore, many efforts have been undertaken for automation. The main challenge for automation is the development of a simple and robust seam-tracking algorithm that can be applied to a portable welding robot that operates under irregular and diverse task conditions in the workspace. We developed a seam-tracking algorithm for weaving weld path planning using a laser displacement sensor. The goal of the proposed algorithm is to detect the seam of single-butt welding with manually tack-welded non-zero gaps. The focus is on keeping the algorithm simple and affordable so that it can be applied to portable robots that operate in hazardous fields. The algorithm consists of four steps: scanning, filtering, generation of the reference points, and path planning. In the scanning process, the depth data of a cross-section of the seam profile is obtained. Next, a Gaussian filter is used to remove noise from the raw data. A differential characteristic-point detection algorithm is applied to the filtered data to detect the reference points that represent the shape and location of the gap to be welded. Finally, path planning for single-V butt multi-pass welding is done based on the detected reference points. A portable four-axis welding robot is built using the developed algorithm. The algorithm is validated through welding experiments regarding a single-V butt welding task with a manually tack-welded non-zero gap. Crown

KW - Characteristic-point detection

KW - Laser displacement sensor

KW - Seam-tracking algorithm

KW - Welding robot

UR - http://www.scopus.com/inward/record.url?scp=80052030716&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80052030716&partnerID=8YFLogxK

U2 - 10.1016/j.rcim.2011.06.001

DO - 10.1016/j.rcim.2011.06.001

M3 - Article

VL - 28

SP - 1

EP - 13

JO - Robotics and Computer-Integrated Manufacturing

JF - Robotics and Computer-Integrated Manufacturing

SN - 0736-5845

IS - 1

ER -