• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.676-681
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• 2013

For underwater vehicles, the use of sensors such as cameras and laser scanners is limited by the difference in environment compared to robots designed to work on dry land. In underwater environments, if use is made of sound signals, valuable information can be obtained. The most important application is the localization of underwater sound sources. The estimated location of a sound source can be used to control underwater robots or submarines. Thus, the purpose of this research is to estimate the source's direction and location in a noisy underwater environment. The direction of the sound source is obtained using two hydrophones. Furthermore, if we assume that the robot or sound source is moving, the location of the sound source is estimated using more than two estimated directions. The feasibility of the developed algorithm is examined by experiments in a water tank and in the ocean.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1796-1799
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• 1997

This thersis presents precise position control emthods of a 3-PRPS in-parallel manipulator for industrial applications such as assembly of highly integrated semiconductors and microsurgery. Since real-time ontrol is one of the most important issues required for industrial application, the experimental hardware is set up with a VME based DSP controller. In the 3-PRPS parallel mainpulator, structurally existing frictiion at three horizontal links considerably degrades the precise position control. In order to compensate the friction of the horizontal links in the joint space, a disturbance compensation usign disturbance and velocity observers has been proposed and investigated. We analyzed the decision method of eigenvalues of the disturbance observer and the effects of the control resulted form tehsystem model errors. Through a series of simulations and experiments, we see that the methods is capable of compensating variations of the robot parameters such as inertia and damping as well as the joint friction. Experiments show that the disturbance compensation method usign disturbance and velocity observer is very effective to compensate the friction. Compared with conventional PID position control, it decreased position errors ina circular motion by approximately 70%.

• International Journal of Control, Automation, and Systems
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• 제1권1호
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• pp.142-148
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• 2003

Reinforcement learning is considered as an important tool for robotic learning in unknown/uncertain environments. In this paper, we propose an evaluation function expressed in a vector form to realize multi-dimensional reinforcement learning. The novel feature of the proposed method is that learning one behavior induces parallel learning of other behaviors though the objectives of each behavior are different. In brief, all behaviors watch other behaviors from a critical point of view. Therefore, in the proposed method, there is cross-criticism and parallel learning that make the multi-dimensional learning process more efficient. By ap-plying the proposed learning method, we carried out multi-dimensional evaluation (reward) and multi-dimensional learning simultaneously in one trial. A special neural network (Q-net), in which the weights and the output are represented by vectors, is proposed to realize a critic net-work for Q-learning. The proposed learning method is applied for behavior planning of mobile robots.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1458-1463
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• 2004

Tracking is one of the most important pre-required task for many application such as human-computer interaction through gesture and face recognition, motion analysis, visual servoing, augment reality, industrial assembly and robot obstacle avoidance. Recently, 3D information of object is required in realtime for many aforementioned applications. 3D tracking is difficult problem to solve because during the image formation process of the camera, explicit 3D information about objects in the scene is lost. Recently, many vision system use stereo camera especially for 3D tracking. The 3D feature based tracking(3DFBT) which is on of the 3D tracking system using stereo vision have many advantage compare to other tracking methods. If we assumed the correspondence problem which is one of the subproblem of 3DFBT is solved, the accuracy of tracking depends on the accuracy of camera calibration. However, The existing calibration method based on accurate camera model so that modelling error and weakness to lens distortion are embedded. Therefore, this thesis proposes 3D feature based tracking method using SVM which is used to solve reconstruction problem.

• 제어로봇시스템학회논문지
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• 제13권11호
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• pp.1074-1081
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• 2007

This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.

• 제어로봇시스템학회논문지
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• 제17권1호
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• pp.38-46
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• 2011

The OPRoS (Open Platform for Robotic Service) framework provides uniform operating environment for service robots. As an OPRoS-based service robot has to support real-time as well as non-real-time applications, application of Windows NT kernel based operating system can be restrictive. On the other hand, various benefits such as rich library and device support and abundant developer pool can be enjoyed when service robots are built on Windows NT. The paper presents a user-mode component scheduler of OPRoS, which can provide near real-time scheduling service on Windows NT based on the restricted real-time features of Windows NT kernel. The component scheduler thread with the highest real-time priority in Windows NT system acquires CPU control. And then the component scheduler suspends and resumes each periodic component executors based on its priority and precedence dependency so that the component executors are scheduled in the preemptive manner. We show experiment analysis on the performance limitations of the proposed scheduling technique. The analysis and experimental results show that the proposed scheduler guarantees highly reliable timing down to the resolution of 10ms.

• JSTS:Journal of Semiconductor Technology and Science
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• 제12권2호
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• pp.193-202
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• 2012

In this paper, we propose a new approach for compact range sensor system for real-time robot applications. Instead of using off-the-shelf camera and projector, we devise a compact system with a CMOS image-sensor and a DMD (Digital Micro-mirror Device) that yields smaller dimension ($168{\times}50{\times}60mm$) and lighter weight (500g). We also realize one chip hard-wired processing of projection of structured-light and computing the range by exploiting correspondences between CMOS images-ensor and DMD. This application-specific chip processing is implemented on an FPGA in real-time. Our range acquisition system performs 30 times faster than the same implementation in software. We also devise an efficient methodology to identify a proper light intensity to enhance the quality of range sensor and minimize the decoding error. Our experimental results show that the total-error is reduced by 16% compared to the average case.

• 한국멀티미디어학회논문지
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• 제23권8호
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• pp.1006-1018
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• 2020

Dataset is getting more import to develop a learning based algorithm. Quality of the algorithm definitely depends on dataset. So we introduce new dataset over 200 thousands images which are fully labeled multi modal sensor data. Proposed dataset was designed and constructed for researchers who want to develop detection, tracking, and action classification in outdoor environment for surveillance scenarios. The dataset includes various images and multi modal sensor data under different weather and lighting condition. Therefor, we hope it will be very helpful to develop more robust algorithm for systems equipped with difference kinds of sensors in outdoor application. Case studies with the proposed dataset are also discussed in this paper.

• 한국융합학회논문지
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• 제11권4호
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• pp.247-254
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• 2020

4차혁명에 따른 사회 문화 경제적 변화는 푸드테크 산업의 성장을 견인하는 배경이 되고 있다. 한국의 푸드테크산업은 아직까지 배달앱에 집중되어 있고 스마트팜, 인공지능을 비롯한 로봇시장은 발전 초기단계이다. 미국은 대체육업체가 이미 유니콘 기업에 다수 포함되어 있는 반면 소고기 수입 4위국인 한국은 대체육 개발이 미흡하다. 프랑스는 유럽 최대의 농업 국가답게 어그테크 중심으로 푸드테크가 발전하고 있으며 중국은 세계 제일의 인구수를 앞세워 거대화 된 온라인 전자 상거래 시장을 토대로 배달앱 중심의 푸드테크가 발달했다. 한국도 과거산업에 초점이 맞춰진 규제를 신산업에 적용할 수 있도록 변경하고 정계와 재계의 투자 및 연구에 집중하여 다양한 푸드테크 산업을 발전시켜야 할 것이다.

• 전력전자학회논문지
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• 제9권3호
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• pp.253-259
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• 2004

본 논문은 BLDC 전동기의 고성능 속도제어를 위하여 외란 초크 관측기를 기반으로 한 속도 제어 방법에 대하여 기술하였다. 강성이 낮은 로봇 팔이나 추적 응용의 경우 시스템의 안정성 측면에서 속도 제어기의 이득 값을 크게 할 수 없다. 따라서 외란 토크 관측기를 이용한 전향 보상 방법을 이용하였다. 본 방법으로 속도 제어기의 이득을 충분히 크게 할 수 없을 때 외란 토크에 대한 속도 응답 특성을 향상시킬 수 있다. 결과적으로, 고성능 분야의 응용을 위한 BLDC 전동기의 속도 제어가 가능하게 된다.