• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1070-1075
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• 2015

This paper proposes a calibration algorithm for a three-degree-of-freedom (DOF) planar cable-driven parallel robot (CDPR). To evaluate the proposed algorithm, we calibrated winches and an optical tracking sensor, measured the end-effector pose using the optical tracking sensor, and calculated the accurate robot configuration using the measurement information. To conduct an accuracy test on the end-effector pose, we followed guidelines from "Manipulating industrial robots - Performance criteria and related test methods." Through the test, it is verified that the position accuracy can be improved by up to 20% for a $2m{\times}2m$-sized planar cable robot using the proposed calibration algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.702-707
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• 2004

This article is concerned with container pose estimation using CCD a camera and a range sensor. In particular, the issues of characteristic point extraction and image noise reduction are described. The Euler-Lagrange equation for gaussian and random noise reduction is introduced. The alternating direction implicit(ADI) method for solving Euler-Lagrange equation based on partial differential equation(PDE) is applied. The vertex points as characteristic points of a container and a spreader are founded using k order curvature calculation algorithm since the golden and the bisection section algorithm can't solve the local minimum and maximum problems. The proposed algorithm in image preprocess is effective in image denoise. Furthermore, this proposed system using a camera and a range sensor is very low price since the previous system can be used without reconstruction.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.6
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• pp.537-542
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• 2015

The measurement of 3D shape is important in inspecting the quality of product. In this paper, we present a 3D shape measurement system of fastener using a camera and a slit laser. Calibration structure with slits is used in the extrinsic calibration of the camera and laser. The pose of the camera and laser is computed under the same world coordinate system in the calibration structure. Reflection of laser light on the metal surface causes many difficulties in the robust detection of them on image. We overcome this difficulty by using color and dynamic programming. Motor stage is used to rotate the fastener to recover the whole 3D shape of the surface of it.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.41-48
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• 2014

This paper analyzes the Monte Carlo localization (MCL) method, which estimates the pose of an indoor mobile robot. A mobile robot must know where it is to navigate in an indoor environment. The MCL technique is one of the most influential and popular techniques for estimation of robot position and orientation using a particle filter. For the analysis, we perform experiments in an indoor environment with a differential drive robot and ultrasonic range sensor system. The analysis uses MATLAB for implementation of the MCL and investigates the effects of the control parameters on the MCL performance. The control parameters are the uncertainty of the motion model of the mobile robot and the noise level of the measurement model of the range sensor.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.122-129
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• 2020

The circumference of the body is not only an indicator in order to buy clothes in our life but an important factor which can increase the effectiveness healing properly after figuring out the shape of body in a hospital. There are several measurement tools and methods so as to know this, however, it spends a lot of time because of the method measured by hand for accurate identification, compared to the modern advanced societies. Also, the current equipments for automatic body scanning are not easy to use due to their big volume or high price generally. In this papers, OpenPose model which is a deep learning-based Skeleton Tracking is used in order to solve the problems previous methods have and for ease of application. It was researched to find joints and an approximation by applying the data of the deep camera via reference data of the measurement parts provided by the hospitals and to develop a program which is able to measure the circumference of the body lighter and easier by utilizing the elliptical circumference formula.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.51-59
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• 2016

In this paper we present (1) analysis of imaging sonar measurement for two-view relative pose estimation of an autonomous vehicle and (2) bundle adjustment and 3D reconstruction method using imaging sonar. Sonar has been a popular sensor for underwater application due to its robustness to water turbidity and visibility in water medium. While vision based motion estimation has been applied to many ground vehicles for motion estimation and 3D reconstruction, imaging sonar addresses challenges in relative sensor frame motion. We focus on the fact that the sonar measurement inherently poses ambiguity in its measurement. This paper illustrates the source of the ambiguity in sonar measurements and summarizes assumptions for sonar based robot navigation. For validation, we synthetically generated underwater seafloor with varying complexity to analyze the error in the motion estimation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3981-4004
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• 2019

This paper proposes a novel method for locating objects in real space from a single remote image and measuring actual distances between them by automatic detection and perspective transformation. The dimensions of the real space are known in advance. First, the corner points of the interested region are detected from an image using deep learning. Then, based on the corner points, the region of interest (ROI) is extracted and made proportional to real space by applying warp-perspective transformation. Finally, the objects are detected and mapped to the real-world location. Removing distortion from the image using camera calibration improves the accuracy in most of the cases. The deep learning framework Darknet is used for detection, and necessary modifications are made to integrate perspective transformation, camera calibration, un-distortion, etc. Experiments are performed with two types of cameras, one with barrel and the other with pincushion distortions. The results show that the difference between calculated distances and measured on real space with measurement tapes are very small; approximately 1 cm on an average. Furthermore, automatic corner detection allows the system to be used with any type of camera that has a fixed pose or in motion; using more points significantly enhances the accuracy of real-world mapping even without camera calibration. Perspective transformation also increases the object detection efficiency by making unified sizes of all objects.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.6
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• pp.15-23
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• 2011

Stereo vision approach to solve the problem using a single camera three dimension precise distance measurement and object recognition method is proposed. Precise three dimensional information of objects can be obtained using single camera, a laser light and a rotating flat mirror. With a simple thresholding operation on the depth information, the segmentations of objects can be obtained. Comparing the signatures of object boundaries with database, objects can be recognized. Improving the simulation results for the object recognition by precise distance measurement are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.81-81
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• 2000

We use camera to apply human vision system in measurement. To do that, we need to know about camera parameters. The camera parameters are consisted of internal parameters and external parameters. we can fix scale factor&focal length in internal parameters, we can acquire external parameters. And we want to use these parameters in automatically driven vehicle by using camera. When we observe an camera parameters in respect with that the external parameters are important parameters. We can acquire external parameter as fixing focal length&scale factor. To get lane coordinate in image, we propose a lane detection filter. After searching lanes, we can seek vanishing point. And then y-axis seek y-sxis rotation component(${\beta}$). By using these parameter, we can find x-axis translation component(Xo). Before we make stepping motor rotate to be y-axis rotation component(${\beta}$), '0', we estimate image coordinates of lane at (t+1). Using this point, we apply this system to Kalman filter. And then we calculate to new parameters whick make minimum error.