• International Journal of Aeronautical and Space Sciences
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• 제18권3호
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• pp.555-564
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• 2017

In this paper, a new technique for attitude and heading reference system (AHRS) using low-cost MEMS sensors of the gyroscope, accelerometer, and magnetometer is addressed particularly in vibration environments. The motion of MEMS sensors interact with the scale factor and cross-coupling errors to produce random errors by the harsh environment. A new adaptive attitude estimation algorithm based on the Kalman filter is developed to overcome these undesirable side effects by analyzing windowed measurement error covariance. The key idea is that performance degradation of accelerometers, for example, due to linear vibrations can be reduced by the proposed measurement error covariance analysis. The computed error covariance is utilized to the measurement covariance of Kalman filters adaptively. Finally, the proposed approach is verified by using numerical simulations and experiments in an acceleration phase and/or vibrating environments.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.281-282
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• 2019

In recent years welfare of animals is the biggest challenge because animals, especially dogs are widely recognized as pet as well as they are using as service animals. So, for the wellbeing of the dog it is necessary to perform objective assessment to track their behavior in everyday life. In this paper, we have proposed an automatic behavior assessment system for dogs based on a neck worn and tail worn accelerometer and gyroscope platform, and data analysis techniques that recognize typical dog activities. We evaluate the system based on the analysis of 8 behavior traits in 3 dogs, incorporating 2 breeds of various sizes. Our proposed framework able to reproduce the manual assessment that is based on the video recording which is treated as gold standard that exhibits the real-life use case of automated dog behavior analysis.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제5권10호
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• pp.331-338
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• 2016

본 논문에서는 모션 센서를 이용한 군대 수신호 전송 시스템을 제안한다. 제안 시스템은 분대장 디바이스와 분대원 디바이스, 서버로 구성된다. 분대장 디바이스와 분대원 디바이스는 마이크로 아두이노와 가속도 센서, 자이로스코프 센서로 구현되었으며, 서버는 라즈베리파이3을 사용하여 구현되었다. 분대장 디바이스와 분대원 디바이스는 밴드 형태로 제작되었기 때문에 가볍고 휴대성이 좋다. 또한, 제안 시스템은 시야가 확보되지 않는 상황에서 진동을 통해 수신호를 전송할 수 있다. 제안 시스템에서 구현된 디바이스는 4가지의 수신호를 인식할 수 있으며, 실험을 통해 88.82%의 인식 성공률을 보였다. 본 연구의 결과물을 통해 군 작전의 효율성과 병사의 생존율을 높일 것을 기대한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권3호
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• pp.230-245
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• 2005

In this paper, we develop a gesture-based input device equipped with accelerometers and gyroscopes. The sensors measure the inertial measurements, i.e., accelerations and angular velocities produced by the movement of the system when a user is inputting gestures on a plane surface or in a 3D space. The gyroscope measurements are integrated to give orientation of the device and consequently used to compensate the accelerations. The compensated accelerations are doubly integrated to yield the position of the device. With this approach, a user's gesture input trajectories can be recovered without any external sensors. Three versions of motion tracking algorithms are provided to cope with wide spectrum of applications. Then, a Bayesian network based recognition system processes the recovered trajectories to identify the gesture class. Experimental results convincingly show the feasibility and effectiveness of the proposed gesture input device. In order to show practical use of the proposed input method, we implemented a prototype system, which is a gesture-based remote controller (Magic Wand).

• 한국산학기술학회논문지
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• 제22권3호
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• pp.770-776
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• 2021

위치 파악을 위한 시스템은 지난 몇 년 동안 적극적으로 연구 및 개발되었으며 많은 응용 분야에 적용되고 있다. 본 논문은 가속도계와 단일 축 자이로 스코프로 구성된 센서 시스템을 사용하여 실내와 실외의 넓은 공간에서 위치를 파악하는 방법을 제안한다. 가속도계와 자이로 스코프를 사용하여 사람의 움직임을 인식하는 시스템을 설계 한 후 기하학적 알고리즘을 센서 데이터에 적용하여 오차율을 줄이고자 하였다. 특히 활용성을 고려하기 위하여 센서 기기를 허리에 느슨하게 착용함으로써 실험 데이터가 실제 응용 분야에 유용하게 사용될 수 있도록 고려하였다. 반지름이 1m, 3m인 원형 트랙의 실험 결과를 바탕으로 본 논문에서는 회전 각도의 임계 값을 이용한 알고리즘을 제안하고 실험 결과에 적용하였다. 그리드 패턴 트랙 모델에 대한 추적 실험을 수행했으며, 최종 추적 지점과 목표 지점의 평균 편차는 원시 센서 데이터의 경우 약 15.2m로 확인 되었으며, 회전 각도 임계 값을 사용하는 알고리즘을 사용하여 약 4.0m로 줄일 수 있었다.

• 센서학회지
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• 제8권2호
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• pp.139-147
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• 1999

본 논문에서는 관성 항법 장치 및 동작 제어 장치 능에서 회전 각속도를 검출하기 위하여 널리 사용되는 동조 자이로스코프의 새로운 각속도 검출방법을 제시하였다. 제안된 방법은 자이로스코프의 모델을 사용하여 재평형 루프의 설계를 수행함으로써 기존의 PI제어 방법만을 사용하였을 경우보다 외부 입력에 대하여 속도 검출을 위한 픽업단의 회전각도가 과도 및 정상 상태에서 작은 검출각을 유지시킨 상태에서 입력 각속도를 검출할 수 있으며 이에 따라 자유 자이로스코프의 기계적인 변경 없이도 시스템의 동작 범위를 매우 넓히는 것이 가능함을 보였다. 제안된 방법을 사용한 동조자이로스코프 시스템의 모델 및 전달 특성을 제시하였으며 최종적으로 컴퓨터 모의실험 모델 및 그 결과를 제시하여 그 타당성을 확인하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.616-619
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• 2003

In this paper, we develop an input device equipped with accelerometers and gyroscopes. The installed sensors measure the inertial measurements i.e., accelerations and angular rates produced by the movement of the system when a user is writing on the plane surface or in the three dimensional space. The gyroscope measurement are integrated once to give the attitude of the system and consequently used to remove the gravity included in the acceleration measurements. The compensated accelerations bin doubly integrated to yield the position of the system. Due to the integration processes involved in recovering the users'motions, the accuracy of the position estimation significantly deteriorates with time. Among various error sources of the system incorrect estimation of attitude causes the largest portion of the positioning error since the gravity is not fully cancelled. In order to solve this problem, we propose a Kalman filler-based attitude estimation algorithm which fuses measurement data from accelerometers and gyroscopes by fuzzy logic approach. In addition, the online calibration of the gyroscope biases are performed in parallel with the attitude estimation to give more accurate attitude estimation. The effectiveness and the feasibility of the presented system is demonstrated through computer simulations and actual experiments.

• 센서학회지
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• 제24권1호
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• pp.47-53
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• 2015

Fall-related injuries in elderly people are a major health care problem. This paper introduces determination of fall direction before impact using support vector machine (SVM). Once a falling phase is detected, dynamic characteristic parameters measured by the accelerometer and gyroscope and then processed by a Kalman filter are used in the SVM to determine the fall directions, i.e., forward (F), backward (B), rightward (R), and leftward (L). This paper compares the determination sensitivities according to the selected parameters for the SVM (velocities, tilt angles, vs. accelerations) and sensor attachment locations (waist vs. chest) with regards to the binary classification (i.e., F vs. B and R vs. L) and the multi-class classification (i.e., F, B, R, vs. L). Based on the velocity of waist which was superior to other parameters, the SVM in the binary case achieved 100% sensitivities for both F vs. B and R vs. L, while the SVM in the multi-class case achieved the sensitivities of F 93.8%, B 91.3%, R 62.3%, and L 63.6%.

• 반도체디스플레이기술학회지
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• 제22권2호
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• pp.112-119
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• 2023

In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

• Journal of Multimedia Information System
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• 제2권2호
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• pp.233-240
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• 2015

Mobile devices are becoming increasingly sophisticated and the latest generation of smartphones now incorporates many diverse and powerful sensors. These sensors include acceleration sensor, magnetic field sensor, light sensor, proximity sensor, gyroscope sensor, pressure sensor, rotation vector sensor, gravity sensor and orientation sensor. The availability of these sensors in mass-marketed communication devices creates exciting new opportunities for data mining and data mining applications. In this paper, we describe and evaluate a system that uses phone-based accelerometers to perform activity recognition, a task which involves identifying the physical activity that a user is performing. To implement our system, we collected labeled accelerometer data from 10 users as they performed daily activities such as "phone detached", "idle", "walking", "running", and "jumping", and then aggregated this time series data into examples that summarize the user activity 5-minute intervals. We then used the resulting training data to induce a predictive model for activity recognition. This work is significant because the activity recognition model permits us to gain useful knowledge about the habits of millions of users-just by having them carry cell phones in their pockets.