• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1830-1835
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• 2015

In this paper, we propose an algorithm for the automatic registration of two rigid parts using multiple 3D sensor systems on a robot. Four sets of structured laser stripe system consisted of a camera and a visible laser stripe is used for the acquisition of 3D information. Detailed procedures including extrinsic calibration among four 3D sensor systems and hand/eye calibration of 3D sensing system on robot arm are presented. We find a best pose using search-based pose estimation algorithm where cost function is proposed by reflecting geometric constraints between sensor systems and target objects. A pose with minimum gap and height difference is found by greedy search. Experimental result using demo system shows the robustness and feasibility of the proposed algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.11 s.188
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• pp.58-67
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• 2006

Due to the variety of signal processing and complicated mathematical analysis, it is not easy to accomplish 3D bin-picking with non-contact sensor. To solve this difficulties the reliable signal processing algorithm and a good sensing device has been recommended. In this research, 3D laser scanner and CCD camera is applied as a sensing device respectively. With these sensor we develop a two-step bin-picking method and reliable algorithm for the recognition of 3D bin object. In the proposed bin-picking, the problem is reduced to 2D intial recognition with CCD camera at first, and then 3D pose detection with a laser scanner. To get a good movement in the robot base frame, the hand eye calibration between robot's end effector and sensing device should be also carried out. In this paper, we examine auto-calibration technique in the sensor calibration step. A new thinning algorithm and constrained hough transform is also studied for the robustness in the real environment usage. From the experimental results, we could see the robust bin-picking operation under the non-aligned 3D hole object.

• The Journal of Korea Robotics Society
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• v.11 no.1
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• pp.9-18
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• 2016

A rectangle-based relative localization method is proposed for a mobile robot based on a novel geometric formulation. In an artificial environment where a mobile robot navigates, rectangular shapes are ubiquitous. When a scene rectangle is captured using a camera attached to a mobile robot, localization can be performed and described in the relative coordinates of the scene rectangle. Especially, our method works with a single image for a scene rectangle whose aspect ratio is not known. Moreover, a camera calibration is unnecessary with an assumption of the pinhole camera model. The proposed method is largely based on the theory of coupled line cameras (CLC), which provides a basis for efficient computation with analytic solutions and intuitive geometric interpretation. We introduce the fundamentals of CLC and describe the proposed method with some experimental results in simulation environment.

• Nuclear Engineering and Technology
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• v.41 no.1
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• pp.125-134
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• 2009

This paper presents details on a tube inspection robotic system and a positioning method of the robot for a steam generator (SG) in nuclear power plants (NPPs). The robotic system is separated into three parts for easy handling, which reduces the radiation exposure during installation. The system has a supporting leg to increase the rigidity of the robot base. Since there are several thousands of tubes to be inspected inside a SG, it is very important to position the tool of the robot at the right tubes even if the robot base is positioned inaccurately during the installation. In order to obtain absolute accuracy of a position, the robot kinematics was mathematically modeled with the modified DH(Denavit-Hartenberg) model and calibrated on site using tube holes as calibration points. To tune the PID gains of a commercial motor driver systematically, the time delay control (TDC) based gain tuning method was adopted. To verify the performance of the robotic system, experiments on a Framatomes 51B Model type SG mockup were undertaken.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.4
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• pp.319-326
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• 2014

Accurate estimation of the robot's position has an important role in autonomous navigation. Odometry is one of the most widely used techniques for mobile robot positioning. However, odometry has a well-known drawback that the position errors are accumulated when the travel distance increases. The UMBmark method is the conventional odometry calibration scheme for two wheel differential mobile robots. In the UMBmark method, the approximations for small angles are used in order to simplify the calculations. In this paper, we propose the new calibration scheme by using experimental orientation errors. Kinematic parameters can be calculated accurately without approximations by using experimental orientation errors. The numerical simulation and experimental results show that the odometry accuracy can be improved by the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.168-172
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• 2001

The accuracy problem of robot manipulators has long been one of the principal concerns in robot design and control. A practical and economical way of enhancing the manipulator accuracy, without affecting its hardware, is kinematic calibration. In this paper an effective and practical method is presented for kinematic calibration of Stewart platforms. In our method differential errors in kinematical parameters are linearly related to differential errors in the platform pose, expressed through the forward kinematics. The algorithm is tested using simulated measurement in which measurement noise is included.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.16-22
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• 2019

Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.16-22
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• 2008

Recently, automatic parking assist systems are commercially available in some cars. In order to improve the reliability and the accuracy of parking control, pose uncertainty of a vehicle and some experimental issues should be solved. In this paper, following three schemes are proposed. (1) Odometry calibration scheme for the Car-Like Mobile Robot.(CLMR) (2) Accurate localization using Extended Kalman Filter(EKF) based redundant odometry fusion. (3) Trajectory tracking controller to compensate the tracking error of the CLMR. The proposed schemes are experimentally verified using a miniature Car-Like Mobile Robot. This paper shows that odometry accuracy and trajectory tracking performance can be dramatically improved by using the proposed schemes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.667-668
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• 2012

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2325-2330
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• 2005

A potential field method for solving the problem of path planning based on global and local information for a mobile robot moving among a set of stationary obstacles is described. The concept of various method used path planning is used design a planning strategy. A real human living area is constructed by many moving and imminence obstacles. Home service mobile robot must avoid many obstacles instantly. A path that safe and attraction towards the goal is chosen. The potential function depends on distance from the goal and heuristic function relies on surrounding environments. Three additional combined methods are proposed to apply to human living area, calibration robots position by measured surrounding environment and adapted home service robots. In this work, we proposed the application of various path planning theory to real area, human living. First, we consider potential field method. Potential field method is attractive method, but that method has great problem called local minimum. So we proposed intermediate point in real area. Intermediate point was set in doorframe and between walls there is connect other room or other area. Intermediate point is very efficiency in computing path. That point is able to smaller area, area divided by intermediate point line. The important idea is intermediate point is permanent point until destruction house or apartment house. Second step is move robot with sensing on front of mobile robot. With sensing, mobile robot recognize obstacle and judge moving obstacle. If mobile robot is reach the intermediate point, robot sensing the surround of point. Mobile robot has data about intermediate point, so mobile robot is able to calibration robots position and direction. Third, we gave uncertainty to robot and obstacles. Because, mobile robot was motion and sensing ability is not enough to control. Robot and obstacle have uncertainty. So, mobile robot planed safe path planning to collision free. Finally, escape local minimum, that has possibility occur robot do not work. Local minimum problem solved by virtual obstacle method. Next is some supposition in real living area.