• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.11
• /
• pp.968-973
• /
• 2013

In the transportation industry, especially in the shipbuilding process, 3D surface measurement of large-scale hull pieces is needed for fabrication and assembly. We suggest an efficient method for checking the shape of curved plates under the forming operation with short time by measuring 3D profiles along the multi lines of the target surface. For accurate profile reconstruction, 2D camera calibration and 3D calibration using gauge blocks were performed. The evaluation test shows that the measurement accuracy is within the boundary of tolerance required in the shipbuilding process.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.12
• /
• pp.1164-1171
• /
• 2004

A new multi-scale simulation model is proposed to analyze heart mechanics. Electrophysiology of a cardiac cell is numerically approximated using the previous model of human ventricular myocyte. The ion transports across cell membrane initiated by action potential induce an excitation-contraction mechanism in the cell via cross bridge dynamics. Negroni and Lascano model (NL model) is employed to calculate the tension of cross bridge which is closely related to the ion dynamics in cytoplasm. To convert the tension on cell level into contraction force of cardiac muscle, we introduce a simple geometric model of ventricle with a thin-walled hemispheric shape. It is assumed that cardiac tissue is composed of a set of cardiac myocytes and its orientation on the hemispheric surface of ventricle remains constant everywhere in the domain. Application of Laplace law to the ventricle model enables us to determine the ventricular pressure that induces blood circulation in a body. A lumped parameter model with 7 compartments is utilized to describe the systemic circulation interacting with the cardiac cell mechanism via NL model and Laplace law. Numerical simulation shows that the ion transports in cell level eventually generate blood hemodynamics on system level via cross bridge dynamics and Laplace law. Computational results using the present multi-scale model are well compared with the existing ones. Especially it is shown that the typical characteristics of heart mechanics, such as pressure volume relation, stroke volume and ejection fraction, can be generated by the present multi-scale cardiovascular model, covering from cardiac cells to circulation system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.5
• /
• pp.413-418
• /
• 2012

This paper presents a multi-robot path planner for environment exploration and monitoring. Robotics systems are being widely used as data measurement tools, especially in dangerous environment. For large scale environment monitoring, multiple robots are required in order to save time. The path planner should not only consider the collision avoidance but efficient coordination of robots for optimal measurements. Nonlinear spring force based planning algorithm is integrated with the spatial gradient following path planner. Perturbation/Correlation based estimation of spatial gradient is applied. An algorithm of tuning the stiffness for robot coordination is presented. The performance of the proposed algorithm is discussed with simulation results.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.250-253
• /
• 1998

This paper presents a multi-modal neural network composed of a preprocessing module and a multi-layer neural network module in order to enhance the nonlinear characteristics of neural network. The former module is based on spectral method using Chebyschev polynomials and transforms input data into spectra. The latter module identifies the system using the spectra generated by the preprocessing module. The omnibus numerical experiments show that the method is applicable to many a nonlinear dynamic system in the real world, and that preprocessing using Chebyschev polynomials reduces the number of neurons required for the multi-layer neural network.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.2
• /
• pp.107-116
• /
• 2003

This paper presents a systematic design methodology for fault tolerant controller against a fault in actuators and sensors of linear stochastic systems with uncertainties. The scheme is based on fault detection and diagnosis(isolation and estimation) using a bank of robust two-stage Kalman filters, and accommodation of the actuator fault by eigenstructure assignment and immediate compensation of the sensor's faulty measurement. In order to clarify the fault feature in test statistics of residual, noise reduction method is given by multi-scale discrete wavelet transform. The effectiveness of our approach Is shown via simulations for a VTOL(vertical take-off and landing) aircraft subjected to parameter variations, external disturbances, process and sensor noises.

• The Journal of Korea Robotics Society
• /
• v.12 no.3
• /
• pp.313-321
• /
• 2017

One of the most frequently performed tasks in human-robot interaction (HRI), intelligent vehicles, and security systems is face related applications such as face recognition, facial expression recognition, driver state monitoring, and gaze estimation. In these applications, accurate head pose estimation is an important issue. However, conventional methods have been lacking in accuracy, robustness or processing speed in practical use. In this paper, we propose a novel method for estimating head pose with a monocular camera. The proposed algorithm is based on a deep neural network for multi-task learning using a small grayscale image. This network jointly detects multi-view faces and estimates head pose in hard environmental conditions such as illumination change and large pose change. The proposed framework quantitatively and qualitatively outperforms the state-of-the-art method with an average head pose mean error of less than $4.5^{\circ}$ in real-time.

• The Journal of Korea Robotics Society
• /
• v.17 no.3
• /
• pp.353-358
• /
• 2022

Due to the limited field of view of the pinhole camera, there is a lack of stability and accuracy in camera pose estimation applications such as visual SLAM. Nowadays, multiple-camera setups and large field of cameras are used to solve such issues. However, a multiple-camera system increases the computation complexity of the algorithm. Therefore, in multiple camera-assisted visual simultaneous localization and mapping (vSLAM) the multi-view tracking algorithm is proposed that can be used to balance the budget of the features in tracking and local mapping. The proposed algorithm is based on PanoSLAM architecture with a panoramic camera model. To avoid the scale issue 3D LiDAR is fused with omnidirectional camera setup. The depth is directly estimated from 3D LiDAR and the remaining features are triangulated from pose information. To validate the method, we collected a dataset from the outdoor environment and performed extensive experiments. The accuracy was measured by the absolute trajectory error which shows comparable robustness in various environments.

• The Journal of Korea Robotics Society
• /
• v.19 no.3
• /
• pp.281-286
• /
• 2024

This paper describes the solution method of Team AIRLAB used to participate in the League of Robot Runners Competition which tackles the problem of Lifelong Multi-agent Pathfinding (MAPF). In lifelong MAPF, multiple agents are tasked to navigate to their respective goal locations where new goals are consecutively revealed once they reach initial goals. The agents need to avoid collisions and deadlock situations while they navigate to perform tasks. Our method consists of (i) Puzzle Heuristics, (ii) MAPF-LNS2, and (iii) RHCR. The Puzzle Heuristics is our own algorithm that generates a compact heuristic table contributing to reduce memory consumption and computation time. MAPF-LNS2 and RHCR are state-of-the-art algorithms for MAPF. By combining these three algorithms, our method can improve the efficiency of paths for all agents significantly.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.201-204
• /
• 1998

This paper presents a new construction method of candidate controllers using Multi-modal Neural Network(MNN). To improve a control performance of multiple controller, we construct, candidate controllers which consist of MNN. MNN can learn more complicated function than multilayer neural network. MNN consists of preprocessing module and neural network module. The preprocessing module transforms input signals into spectra which are used as input of the following neural network module. We apply the proposed method to multiple control system which controls the cart-pole balancing system and show the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.1047-1052
• /
• 1989

A novel multi-purpose monitoring platform-LTA vehicle is presented with much improved kinetic performances together with its structural analysis and its scale model test data. This provides a useful mean of monitoring, exploring and remote sensing platform that flies over the wide range of atmosphere and can be used as a safe economic device.