• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.12
• /
• pp.2146-2155
• /
• 1997

This paper presents the Wire Parallel Mechanism for robot pose measurement which can be used to robot calibration. It is constructed with six parallel links using wire. The position and orientation of the end effector of a robot are calculated from the wire length that measured by the encoder. The unique solution is obtained from a Newton-Raphson method and geometric configuration of the mechanism, also the method to estimate a measuring space is presented. Through the simulations, it is verified that the proposed mechanism can measure a robot pose, and has a large measuring space. In conclusion, it can be used effectively in a robot pose measurement with little cost and effort.

• Current Optics and Photonics
• /
• v.8 no.3
• /
• pp.300-306
• /
• 2024

To solve the nozzle swing angle non-contact measurement problem, we present a nozzle pose estimation algorithm involving weighted measurement uncertainty based on rotation parameters. Firstly, the instantaneous axis of the rocket nozzle is constructed and used to model the pivot point and the nozzle coordinate system. Then, the rotation matrix and translation vector are parameterized by Cayley-Gibbs-Rodriguez parameters, and the novel object space collinearity error equation involving weighted measurement uncertainty of feature points is constructed. The nozzle pose is obtained at this step by the Gröbner basis method. Finally, the swing angle is calculated based on the conversion relationship between the nozzle static coordinate system and the nozzle dynamic coordinate system. Experimental results prove the high accuracy and robustness of the proposed method. In the space of 1.5 m × 1.5 m × 1.5 m, the maximum angle error of nozzle swing is 0.103°.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.10
• /
• pp.839-846
• /
• 2016

Bin picking is a task of picking a small object from a bin. For accurate bin picking, the 3D pose information, position, and orientation of a small object is required because the object is mixed with other objects of the same type in the bin. Using this 3D pose information, a robotic gripper can pick an object using exact distance and orientation measurements. In this paper, we propose a 3D vision technique for accurate measurement of 3D position and orientation of small objects, on which a paper label is stuck to the surface. We use a maximally stable extremal regions (MSERs) algorithm to detect the label areas in a left bin image acquired from a stereo camera. In each label area, image features are detected and their correlation with a right image is determined by a stereo vision technique. Then, the 3D position and orientation of the objects are measured accurately using a transformation from the camera coordinate system to the new label coordinate system. For stable measurement during a bin picking task, the pose information is filtered by averaging at fixed time intervals. Our experimental results indicate that the proposed technique yields pose accuracy between 0.4~0.5mm in positional measurements and $0.2-0.6^{\circ}$ in angle measurements.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2003.07b
• /
• pp.1227-1230
• /
• 2003

In this paper, we propose a pose estimation method using local map acquired from 2d laser range finder information. The proposed method uses extended kalman filter. The state equation is a navigation system equation of Nomad Super Scout II. The measurement equation is a map-based measurement equation using a SICK PLS 101-112 sensor. We describe a map consisting of geometric features such as plane, edge and corner. For pose estimation we scan external environments by laser rage finer. And then these data are fed to kalman filter to estimate robot pose and position. The proposed method enables very fast simultaneous map building and pose estimation.

• Journal of Digital Convergence
• /
• v.18 no.12
• /
• pp.97-103
• /
• 2020

The proposed system is composed of two parts, an AI physical fitness measurement part and an AI physical fitness management part. In the AI fitness measurement part, a guide to physical fitness measurement and accurate calculation of the measured value are performed through deep learning-based pose recognition. Based on these measurements, the AI fitness management part designs personalized exercise programs and provides them to dedicated smart applications. To guide the measurement posture, the posture of the subject to be measured is photographed through a webcam and the skeleton line is extracted. Next, the skeletal line of the learned preparation posture is compared with the extracted skeletal line to determine whether or not it is normal, and voice guidance is provided to maintain the normal posture.

• Journal of Astronomy and Space Sciences
• /
• v.35 no.4
• /
• pp.263-277
• /
• 2018

This paper presents a vision-based relative pose estimation algorithm and its validation through both numerical and hardware experiments. The algorithm and the hardware system were simultaneously designed considering actual experimental conditions. Two estimation techniques were utilized to estimate relative pose; one was a nonlinear least square method for initial estimation, and the other was an extended Kalman Filter for subsequent on-line estimation. A measurement model of the vision sensor and equations of motion including nonlinear perturbations were utilized in the estimation process. Numerical simulations were performed and analyzed for both the autonomous docking and formation flying scenarios. A configuration of LED-based beacons was designed to avoid measurement singularity, and its structural information was implemented in the estimation algorithm. The proposed algorithm was verified again in the experimental environment by using the Autonomous Spacecraft Test Environment for Rendezvous In proXimity (ASTERIX) facility. Additionally, a laser distance meter was added to the estimation algorithm to improve the relative position estimation accuracy. Throughout this study, the performance required for autonomous docking could be presented by confirming the change in estimation accuracy with respect to the level of measurement error. In addition, hardware experiments confirmed the effectiveness of the suggested algorithm and its applicability to actual tasks in the real world.

• Smart Structures and Systems
• /
• v.18 no.4
• /
• pp.801-818
• /
• 2016

To estimate structural displacement, a visually servoed paired structured light system (ViSP) was proposed in previous studies. The ViSP is composed of two sides facing each other, each with one or two laser pointers, a 2-DOF manipulator, a camera, and a screen. By calculating the positions of the laser beams projected onto the screens and rotation angles of the manipulators, relative 6-DOF displacement between two sides can be estimated. Although the performance of the system has been verified through various simulations and experimental tests, it has a limitation that the accuracy of the displacement measurement depends on the alignment of the laser pointers. In deriving the kinematic equation of the ViSP, the laser pointers were assumed to be installed perfectly normal to the same side screen. In reality, however, this is very difficult to achieve due to installation errors. In other words, the pose of laser pointers should be calibrated carefully before measuring the displacement. To calibrate the initial pose of the laser pointers, a specially designed jig device is made and employed. Experimental tests have been performed to validate the performance of the proposed calibration method and the results show that the estimated displacement with the initial pose calibration increases the accuracy of the 6-DOF displacement estimation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.8
• /
• pp.3011-3024
• /
• 2021

Pose estimation of the sensor is important issue in many applications such as robotics, navigation, tracking, and Augmented Reality. This paper proposes visual-inertial integration system appropriate for dynamically moving condition of the sensor. The orientation estimated from Inertial Measurement Unit (IMU) sensor is used to calculate the essential matrix based on the intrinsic parameters of the camera. Using the epipolar geometry, the outliers of the feature point matching are eliminated in the image sequences. The pose of the sensor can be obtained from the feature point matching. The use of IMU sensor can help initially eliminate erroneous point matches in the image of dynamic scene. After the outliers are removed from the feature points, these selected feature points matching relations are used to calculate the precise fundamental matrix. Finally, with the feature point matching relation, the pose of the sensor is estimated. The proposed procedure was implemented and tested, comparing with the existing methods. Experimental results have shown the effectiveness of the technique proposed in this paper.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.7
• /
• pp.167-174
• /
• 1998

This paper presents an unoccluded cylindrical object pose measurement using a slit beam laser in which a robot recognizes all of the unoccluded objects from the top of jumbled objects, and picks them up one by one. The elliptical equation parameters of a projected curve edge on a slice are calculated using LSM. The coefficients of standard elliptical equation are compared with these parameters to estimate the object pose. The hamming distances between the estimated coordinates and the calculated ones are extracted as measures to evaluate a local constraint and a smoothing surface curvature. The edges between slices are linked using error function based on the edge types and the hamming distances. The linked edges on slices are compared with the model object's length to recognize the unoccluded object. This proposed method may provide a solution to the automation of part handling in manufacturing environments such as punch press operation or part assembly.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.5
• /
• pp.134-142
• /
• 1997

In this study, we proposed the wire parallel mechanism that can be used to measure a full pose of a robot. It is composed of six parallel links using wire. The position and orientation of the end effectorf of a robot are calculated using the length of wires which is measured by the encoder. The complex non- linear equations of the forward kinematics are solved by using a numerical method, and the unique solution is obtained from the geometric configuration of the device. The length error of the wire which occurs in static condition is compensated by the relational equation that considered longitudinal extension and defoection of the wire. Through this work, we known that the proposed device has a good accuracy( .+-. 0.01mm) in a large measuring region, so it can be used effectively in a callibration of a robot which required a low cost.