• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.83-88
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• 2023

In this paper, we developed a workout and diet assistance application to meet the growing demand for workout and dietary support services due to the increase in the home training population. The application analyzes the user's workout posture in real-time through the camera and guides the correct posture using guiding lines and voice feedback. It also classifies the foods included in the captured photos, estimates the amount of each food, and calculates and provides nutritional information such as calories. Nutritional information calculations are executed on the server, which then transmits the results back to the application. Once received, this data is presented visually to the user. Additionally, workout results and nutritional information are saved and organized by date for users to review.

• Current Research on Agriculture and Life Sciences
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• v.32 no.2
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• pp.79-84
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• 2014

The precision aerial application of agricultural unmanned helicopters has become a new paradigm for small farms with orchards, paddy, and upland fields. The needs of agricultural applications require easy and affordable control systems. Recent developments of MEMS technology based on inertial sensors and high speed DSP have enabled the fabrication of low-cost attitude system. Therefore, this study evaluates inertial MEMS sensors for estimating the attitude of an agricultural unmanned helicopter. The accuracies and errors of gyro and acceleration sensors were verified using a pendulum system. The true motion values were calculated using a theoretical estimation and absolute encoder measurement of the pendulum, and then the sensor output was compared with reference values. When comparing the sensor measurements and true values, the errors were determined to be 4.32~5.72%, 3.53~6.74%, and 3.91~4.16% for the gyro rate and x-, z- accelerations, respectively. Thus, the measurement results confirmed that the inertial sensors are effective for establishing an attitude and heading reference system (AHRES). The sensors would be constructed in gimbals for the estimating and proving attitude measurements in the following paper.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.683-686
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• 1999

이동로봇은 주행성을 가지며 설정된 이동 경로에 따라 목적지까지 자율적으로 이동하기 위해서는 이동로봇의 실제 위치에 대한 정확한 정보가 확보되어야 한다. 정보확보를 위해서 보통 엔코더, 자이로센서, 비젼센서, 레이저 거리등의 센서를 주로 사용한다. 본 연구에서 주행중인 이동로봇의 위치는 상대센서인 엔코더를 통해 측정된 운동변화량과 출발점에서 이동로봇의 위치로부터 자기유도 주행방법에 의해 계산된다. 이들 상대센서는 이동로봇의 실제 이동에 따라 주행거리 및 주행 방향 변화를 항상 측정할 수 있으므로, 전체 주행구간에 걸쳐 이동로봇의 위치를 연속적으로 측정할 수 있다는 장점이 있으나, 상대센서 측정값에 발생된 오차가 위치 평가값이 연속적으로 누적되므로 실제 위치에 대한 오차가 발생하는 단점이 있다. 즉, 바닥의 미끄럼, 요철, 로봇의 요동(Vibration)등 큰 오차의 요인이 된다. 본 연구에서는 위치를 직접 추정하지 않고 엔코드에서 나온 위치오차, Heading 오차, 자체 엔코드오차 그리고, 자이로 오차와 지자기 센서 오차를 Extended Kalman Filter를 통해 추정하여 이 오차를 다시 위치 계산과 Heading에 되돌려 줌으로서 오차를 보정하는 방법을 제시한다.

• Journal of IKEEE
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• v.19 no.4
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• pp.557-565
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• 2015

In this paper, a method for estimating the location of a quadcopter is proposed by applying an EKF-SLAM algorithm to its flight control, to autonomously control the flight of an unmanned quadcopter. The usefulness of this method is validated through simulations. For autonomously flying the unmanned quadcopter, an algorithm is required to estimate its accurate location, and various approaches exist for this. Among them, SLAM, which has seldom been applied to the quadcopter flight control, was applied in this study to simulate a system that estimates flight trajectories of the quadcopter.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.2
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• pp.106-113
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• 2017

Attitude determination algorithms for aircraft and land vehicles use earth gravitational vector and geomagnetic vector; hence, magnetometers and accelerometers are employed. In dynamic situation, the output from accelerometers includes not only gravitational vector but also motional acceleration, thus it is hard to determine accurate attitude. The acceleration compensation method treated in this paper solves the problem to compensate the specific force vector for motional acceleration calculated by a GPS receiver. This paper analyzed the error from the corrected vector regarded as a constant by conventional acceleration compensation method, and improve the error by rederivation from measurements. The analyzed error factors and improvements by the proposed algorithm are verified by computer simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.548-549
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• 2015

무인 잠수정은 자율 무인잠수정(이하 'AUV' 또는 '자율무인잠수정'을 혼용)과 원격조정잠수정(이하 'ROV'로 지칭)으로 분류를 할 수 있다. ROV는 테더 게이블로 인한 작업 범위의 한계와 운동성능 효율이 떨어지는 단점을 지니고 있어, 테더 케이블이 필요 없는 AUV에 대한 필요성이 증대되고 있다. 추측 항법 시스템인 관성 항법 시스템(inertial navigation system, 이하 'INS'로 지칭)은 외부 도움없이 관성측정 장치(inertial measurement unit, 이하 'IMU'로 지칭)를 활용하여 구성된 시스템을 말한다. IMU는 자이로 스코프(gyroscope), 가속도계(accelerometer), 지자기(magnetic)센서로 구성된 측정 장치로 3개의 센서를 사용하여 상호 보정을 통한 기동 체의 위치, 속도 및 자세 정보를 제공한다. 복합항법시스템은 추측항법시스템이 가지는 누적오차와 측위 항법시스템이 가지는 외부환경에 대한 단점을 상호 보완하는 방법으로 연구가 진행 중이다. 하지만 심해서 또는 해양의 특성에 따라 측위 시스템이 사용되지 못하기 때문에 추측 항법시스템의 다양한 관성 센서를 활용한 상로 보완과 신호처리 방법을 통한 연구 개발이 진행 중이다. 다양한 센서 정보를 통합하는 목적으로 칼만 필터와 같은 최적 필터기법이 보편적으로 사용되고 있다. 칼만 필터는 확률 선형 시스템에 대하여 공정잡음 및 측정 잡음이 가우시안 확률 분포를 따를 때 최적의 추정자가 된다. 또한 가우시안 조건을 만족하지 않는 경우에도 선형 추정자 중에 추정 오차의 분산이 가장 작은 추정자이다. 칼만 필터가 최상의 성능을 발휘 하려면 공정잡음과 측정 잡음의 실제 값을 정확히 알아내는 것이 중요하다. 잡음 수준에 대한 정보가 부정확 할 경우 칼만 필터는 발산 할 수 있기 때문에 시스템에서 잡음 수준의 공산은 칼만 필터의 최적 이득을 결정하는 중요한 요소로 추정치에 큰 영향을 준다. 따라서 칼만 필터를 추측항법시스템에 적용 시킬 경우 실제 모텔의 잡음 공분산을 정확히 추정할 수 있는 기법이 요구된다. 추측항법시스템은 다양한 센서를 활용하기 때문에 움직이는 기동 표적에 적용시 잡음공분상이 변하기 때문에 항법시스템이 저하 될 수 있다. 본 연구에서는 다양한 센서를 융합하여 해양 생체 로봇의 정밀 자세 제어가 가능한 시스템을 제안하고자 한다.

• Smart Media Journal
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• v.12 no.7
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• pp.59-67
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• 2023

Recently, research on behavior analysis tracking human posture and movement has been actively conducted. In particular, OpenPose, an open-source software developed by CMU in 2017, is a representative method for estimating human appearance and behavior. OpenPose can detect and estimate various body parts of a person, such as height, face, and hands in real-time, making it applicable to various fields such as smart healthcare, exercise training, security systems, and medical fields. In this paper, we propose a method for classifying four exercise movements - Squat, Walk, Wave, and Fall-down - which are most commonly performed by users in the gym, using OpenPose-based deep learning models, DNN and CNN. The training data is collected by capturing the user's movements through recorded videos and real-time camera captures. The collected dataset undergoes preprocessing using OpenPose. The preprocessed dataset is then used to train the proposed DNN and CNN models for exercise movement classification. The performance errors of the proposed models are evaluated using MSE, RMSE, and MAE. The performance evaluation results showed that the proposed DNN model outperformed the proposed CNN model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.71-77
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• 2024

The increasing use of smart devices in South Korea has led to a rise in patients with spinal disorders. This study aims to develop an Android application with exercise prompts to prevent spinal disorders, enhance the usability of healthcare applications, and utilize Android's overlay technology to encourage physical activity. Considering South Korea's total population, it is estimated that around one million individuals may suffer from spinal disorders due to smart device usage. Emphasizing the importance of maintaining proper posture and regular exercise habits, this research highlights the need for innovative application development to assist users in preventing musculoskeletal disorders caused by smart device usage.

• Korean Journal of Applied Biomechanics
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• v.18 no.2
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• pp.59-64
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• 2008

D. W. KANG, J. S. CHOI, and G. R. TACK, A Study on Real-Time Sports Activity Classification & Monitoring Using a Tri-axial Accelerometer. Korean Jouranl of Sport Biomechanics, Vol. 18, No. 2, pp. 59-64, 2008. This study was conducted to study the real-time sports activity classification and monitoring using single waist mounted tri-axial accelerometer. This monitoring system detects events of sports activities such as walking, running, cycling, transitions between movements, resting and emergency event of falls. Accelerometer module was developed small and easily attachable on waist using wireless communication system which does not constrain sports activities. The sensor signal was transferred to PC and each movement pattern was classified using the developed algorithm in real-time environment. To evaluate proposed algorithm, experiment was performed with several sports activities such as walking, running, cycling movement for 100sec each and falls, transition movements(sit to stand, lie to stand, stand to sit, lie to sit, stand to lie and sit to lie) for 20 times each with 5 healthy subjects. The results showed that successful detection rate of the system for all activities was 95.4%. In this study, through sports activity monitoring. it was possible to classify accurate sports activities and to notify emergency event such as falls. For further study, the accurate energy consumption algorithm for each sports activity is under development.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.10
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• pp.1171-1179
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• 2012

In this study, we consider a dynamic positioning system (DPS) design problem that can be extended to many application fields. Toward this end, tracking and positioning control problems are discussed. In particular, we design a tracking control system that incorporates an observer based on the 2-DOF servo system design approach in order to obtain the desired state information. In the case of observer design, a weighted $H_{\infty}$ error bound approach for a state estimator is considered. Based on an algebraic Riccati equation (inequality) approach, a necessary and sufficient condition for the existence of a full-order estimator that satisfies the weighted $H_{\infty}$ error bound is introduced. The condition for the existence of the estimator is denoted by a linear matrix inequality (LMI) that yields an optimized solution and the observer gain.