• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.967-976
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• 2016

This paper presents a 3D carrier-smoothed GNSS/DR (Global Navigation Satellite System/Dead Reckoning) integrated system for precise ground-vehicle trajectory estimation. For precise DR navigation on sloping roads, the AHRS (Attitude Heading Reference System) methodology is employed. By combining the integrated carrier phase of GNSS and DR sensor measurements, a vehicle trajectory with an accuracy of less than 20cm is obtained even when cycle slip or change of visibility occur. In order to supplement the weak GNSS environment with DR successfully, the DR sensor is precisely compensated for using GNSS Doppler measurements when GNSS visibility is good. By integrating a multi-GNSS receiver with low-cost IMU, a precise 3D navigation system for land vehicles is proposed in this paper. For real-time implementation, a decoupled Kalman filter is employed in the integrated system. Through field experiments, the performance of the proposed system is verified in various road environments, including sloping roads, good-visibility areas, high multi-path areas, and under-ground parking areas.

• Journal of Ocean Engineering and Technology
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• v.26 no.5
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• pp.81-86
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• 2012

Unmanned underwater vehicles have many applications in scientific, military, and commercial areas because of their autonomy. In many cases, an underwater vehicle adopts a control algorithm based on a tactical inertial sensor for precise control. However, a control algorithm that uses a tactical inertial sensor is unsuitable for some underwater vehicle missions such as torpedo decoys. This paper proposes a control algorithm for an unmanned underwater vehicle that does not require precise control. The control algorithm proposed for an unmanned underwater vehicle adopts a low cost MEMS inertial sensor, and simulations using the specifications of the MEMS inertial sensor under development are performed to verify the control algorithm under a real environment. The results of these simulations are presented.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.2
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• pp.18-25
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• 2012

The availability of the GPS signal has been expanded greatly in the field of society overall through the development and construction of the GNSS(Global Navigation Satellite System). Furthermore, in the military, aviation and field of space, the GPS signal is applied widely through the combination of INS consisting of gyroscope and accelerometer, IMU, AHRS with the addition of magnetic sensor. Particularly, the performance of these equipments or sensors is very important with GPS and PAR(Precision Approach Radar) in the flight control of the aircraft. This paper deals with MATLAB simulation and ROLSO(Reduced Order Luenberger State Observer) design to reduce the load of system and realize the stable lateral direction approach control in an appropriate time for reduction of the horizontal error which is importantly considered while an aircraft lands instead of the FOLSO(Full Order Luenberger State Observer) using all measurement values. Consequently, ROLSO is expected to be used for the aircraft's attitude control in the aircraft landing causing the burden to the pilots.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.59-64
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• 2004

In this paper, the error compensation method of the low-cost IMU is proposed. In general, the position and attitude error calculated by accelerometers and gyros grows with time. Therefore the additional information is required to compensate the drift. The attitude angles can be bound accelerometer mixing algorithm and the heading angle can be aided by single antenna GPS velocity. The Kalman filter is used for error compensation. The result is verified by comparing with the attitude calculated by Attitude Heading Reference System with Micro Electro Mechanical System for a basis

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1928-1929
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• 2011

무인항공기란(Unmanned Aerial Vehicle : UAV)란 일반적으로 조종사 없이 사전에 입력된 프로그램에 따라 또는 비행체 스스로 주위환경(장애물, 항로)을 인식하고 판단하여 자율 비행(Autonomous Flying)하는 비행체를 말한다. 본 논문에서는 항법센서(Attitude Heading Referance System: AHRS)를 비행제어 시스템과 통합한 시스템에 관하여 다루었다.

• 한국항공운항학회:학술대회논문집
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• 2016.05a
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• pp.35-38
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• 2016

본 논문에서는 실외 환경에서 GPS 센서 보다 빠른 주기의 위치 추정 기법을 소개한다. 빠른 제어주기가 필요한 멀티콥터 시스템에서 위치 제어에 GPS 센서를 사용하기 위해서는 상대적으로 느린 GPS 데이터의 출력주기를 보완하는 처리가 필요하다. 이 문제를 해결하기 위해 오픈소스 프로젝트를 분석하고 활용하여 가능성을 확인하는 선행 연구를 진행하였다. matlab에서 알고리즘을 검증하고 임베디드 장비에 직접 구동해봄으로써 성능을 확인하였다. 이 알고리즘에서는 멀터콥터의 위치 추정 계산을 위해 AHRS, GPS센서, barometer 센서를 사용한다.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.427-434
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• 2016

This paper focuses on a real-time hardware processing by implementing the ARM Cortex-M4 based embedded system, using a conversion algorithm from a muscular sense to both visual and auditory elements, which recognizes rotations of a human body, directional changes and motion amounts out of human senses. As an input method of muscular sense, AHRS(Attitude Heading Reference System) was used to acquire roll, pitch and yaw values in real time. These three input values were converted into three elements of HSI color model such as intensity, hue and saturation, respectively. Final color signals were acquired by converting HSI into RGB color model. In addition, Three input values of muscular sense were converted into three elements of sound such as octave, scale and velocity, which were synthesized to give an output sound using MIDI(Musical Instrument Digital Interface). The analysis results of both output color and sound signals revealed that input signals of muscular sense were correctly converted into both color and sound in real time by the proposed conversion method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.12
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• pp.1124-1131
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• 2015

This paper describes a 5-dof ground testbed which emulates micro-gravity environment for developing Rendezvous/docking algorithm of a nano-satellite. The testbed consists of two parts, the low part which eliminates friction force with ground and the upper part which has 3-dof rotational motion with respect to the low part. For Vison-based autonomous navigation algorithm, we use camera, LIDAR and AHRS as sensors and eight cold gas thrusters and three axis directional reaction wheels as actuators. All system software are implemented with C++ based on on-board computer and Linux OS.

• Journal of Advanced Navigation Technology
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• v.8 no.1
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• pp.19-26
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• 2004

This paper deals with the automatic flight control system for an unmanned target drone which is operated by an army as an anti-air gun shooting training. By automation of unmanned target drone that is manually operated by external pilot, pilot can reduce workload and an army can reduce the budget. Most UAVs which are developed until today use high-cost sensors as AHRS and IMU to measure the attitude, but those are contradictory for the reduction of budget. This paper says the development of low-cost automatic flight control system which makes possible of automatic flight with low-cost sensors. We have developed the integrated automatic flight control system by integrating electricity module, switching module, monitoring module and RC receiver as an one module. We also prove the performance of automatic flight control system by flight test.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.4
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• pp.359-365
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• 2011

A mobile surveillance robot is defined as a surveillance robot system that is mounted on a mobile platform and is used to protect public areas such as airports or harbors from invaders. The mobile surveillance robot that is mounted on a mobile platform consists of a gun module, a camera system module, an embedded control system, and AHRS (Attitude and Heading Reference System). It has two axis control systems for controlling its elevation and azimuth. In order to obtain stable images for targeting invaders, this system requires a stabilizer to compensate any disturbance due to vehicle motion. In this study, a virtual model of a mobile surveillance robot has been created and ADAMS/Matlab simulations have been performed to verify the suitability of the proposed stabilization algorithm. Further, the suitability of the stabilization algorithm has also been verified using a mock-up of the mobile surveillance robot and a 6-DOF (Degree Of Freedom) motion simulator.