• Title/Summary/Keyword: Laser Vision Sensor(LVS)

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Trends of Sensor-based Intelligent Arc Welding Robot System (센서기반 지능형 아크 용접 로봇 시스템의 동향)

  • Joung, Ji Hoon;Shin, Hyeon-Ho;Song, Young Hoon;Kim, SooJong
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.10
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    • pp.1051-1056
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    • 2014
  • In this paper, we introduce an intelligent robotic arc welding system which exploits sensors like as LVS (Laser Vision Sensor), Hall effect sensor, voltmeter and so on. The use of industrial robot is saturated because of its own limitation, and one of the major limitations is that industrial robot cannot recognize the environment. Lately, sensor-based environmental awareness research of the industrial robot is performed actively to overcome such limitation, and it can expand application field and improve productivity. We classify the sensor-based intelligent arc welding robot system by the goal and the sensing data. The goals can be categorized into detection of a welding start point, tracking of a welding line and correction of a torch deformation. The Sensing data can be categorized into welding data (i.e. current, voltage and short circuit detection) and displacement data (i.e. distance, position). This paper covers not only the explanation of the each category but also its advantage and limitation.

Autonomous Calibration of a 2D Laser Displacement Sensor by Matching a Single Point on a Flat Structure (평면 구조물의 단일점 일치를 이용한 2차원 레이저 거리감지센서의 자동 캘리브레이션)

  • Joung, Ji Hoon;Kang, Tae-Sun;Shin, Hyeon-Ho;Kim, SooJong
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.2
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    • pp.218-222
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    • 2014
  • In this paper, we introduce an autonomous calibration method for a 2D laser displacement sensor (e.g. laser vision sensor and laser range finder) by matching a single point on a flat structure. Many arc welding robots install a 2D laser displacement sensor to expand their application by recognizing their environment (e.g. base metal and seam). In such systems, sensing data should be transformed to the robot's coordinates, and the geometric relation (i.e. rotation and translation) between the robot's coordinates and sensor coordinates should be known for the transformation. Calibration means the inference process of geometric relation between the sensor and robot. Generally, the matching of more than 3 points is required to infer the geometric relation. However, we introduce a novel method to calibrate using only 1 point matching and use a specific flat structure (i.e. circular hole) which enables us to find the geometric relation with a single point matching. We make the rotation component of the calibration results as a constant to use only a single point by moving a robot to a specific pose. The flat structure can be installed easily in a manufacturing site, because the structure does not have a volume (i.e. almost 2D structure). The calibration process is fully autonomous and does not need any manual operation. A robot which installed the sensor moves to the specific pose by sensing features of the circular hole such as length of chord and center position of the chord. We show the precision of the proposed method by performing repetitive experiments in various situations. Furthermore, we applied the result of the proposed method to sensor based seam tracking with a robot, and report the difference of the robot's TCP (Tool Center Point) trajectory. This experiment shows that the proposed method ensures precision.