• International Journal of Aeronautical and Space Sciences
• /
• v.13 no.3
• /
• pp.398-404
• /
• 2012

A fault detection process is necessary for high integrity systems like satellites, missiles and aircrafts. Especially, the satellite has to be expected to detect faults autonomously because it cannot be fixed by an expert in the space. Faults can cause critical errors to the entire system and the satellite does not have sufficient computation power to operate a large scale fault management system. Thus, a fault detection method, which has less computational burden, is required. In this paper, we proposed a modified PCA (Principal Component Analysis) as a powerful fault detection method of redundant IMU (Inertial Measurement Unit). The proposed method combines PCA with the parity space approach and it is much more efficient than the others. The proposed fault detection algorithm, modified PCA, is shown to outperform fault detection through a simulation example.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1762-1763
• /
• 2011

자동차 블랙박스는 자동차의 사고 전/후의 주행상태를 저장하여 사고의 원인을 규명하는데 사용된다. 사고 발생 시의 자동차의 주행상태를 정확히 기록하기 위해서는 자동차의 위치와 속도에 대한 정보도 필요하므로 자동차 블랙박스에서는 위치/속도 정보를 제공하기 위한 항법 시스템이 필요하다. 본 논문에서는 GPS 수신기와 MEMS 기반의 IMU를 사용하는 자동차 블랙박스용 항법 시스템을 설계하고 그에 대한 성능평가 결과를 제시하고자 한다.

• Journal of Navigation and Port Research
• /
• v.28 no.9
• /
• pp.803-808
• /
• 2004

In this paper, an INS compensation algorithm is proposed using the accelerometer from IMU. First, we denote the basic INS algorithm and show that how to compensate the position error when low cost IMU is used. Second, considering the ship's characteristic and ocean environments, we consider with a drift as a periodic external environment change which is affected with exact position. To develop the compensation algorithm, we use a repetitive method to reduce the external environment changes. Lastly, we verify the proposed algorithm through the experiments, where the acceleration sensor is used to acquire real data.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.8
• /
• pp.774-778
• /
• 2008

The inaccuracy of inertial sensors used in low cost IMU's limits the usage to ARS, at best. Sensor fusion technologies are widely used to overcome this problem. GPS is the most popular secondary sensor, but GPS alone cannot fully compensate the IMU errors in the initial alignment process and rectilinear flights. This paper presents a new concept of aiding the low cost IMU with the sun line of sight vector. The simulation and experimental results in this paper proves that aiding of INS/GPS with the sun line of sight vector increases the observability and improves accuracy remarkably.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.7
• /
• pp.1074-1080
• /
• 2015

In the last decades, the increasing interest in unmanned aerial vehicle(UAV) for military, surveillance, and rescue applications made necessary the development of flight control theory and body structure more and more efficient and fast. In this paper, we describe the design and performance of a prototype hexarotor UAV platform featuring an inertial measurement unit(IMU) based autonomous-flying for use in bluetooth communication environments. The proposed system comprises the construction of the test hexarotor platform, the implementation of an IMU, dynamic modeling and simulation in the hexarotor helicopter. Furthermore, the hexarotor helicopter with implemented IMU is connected with a micro controller unit(ARM-cortex) board. The P-PD control algorithm was used to control the hexarotor. We used the Matlab software to help us to tune the P-PD control parameters for quick response and minimizing the fluctuation. The control simulation and experiment on the real system are implemented in the test platform, evaluated and compared against each other.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2016.10a
• /
• pp.143-144
• /
• 2016

본 논문은 보행자의 각 발에 부착된 2개의 IMU(Inertial Measurement Unit) 정보를 융합하여 위치 추적 성능을 향상시키는 보행자 추측 항법 알고리즘을 제안하였다. 센서내의 방향드리프트로 인해 IMU기반 보행자 위치추적은 시간이 지남에 따라 성능이 크게 저하된다. 제안하는 알고리즘은 방향 드리프트로 인해 각 발의 이동경로가 발산하는 점에 착안하여, 보폭이 일정 값을 초과할 시 이를 보정하고 사용자의 위치를 계산한다. 실험을 통해 제안하는 알고리즘이 방향 드리프트를 효과적으로 감소시키는 것을 확인하였다.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2004.11a
• /
• pp.117-121
• /
• 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 and dynamics position determination by Attitude Heading Reference System with Micro Electro Mechanical System for a basis

• The Journal of Korea Robotics Society
• /
• v.15 no.3
• /
• pp.205-211
• /
• 2020

In this paper, we propose a modified ORB-SLAM (Oriented FAST and Rotated BRIEF Simultaneous Localization And Mapping) for precise indoor navigation of a mobile robot. The exact posture and position estimation by the ORB-SLAM is not possible all the times for the indoor navigation of a mobile robot when there are not enough features in the environment. To overcome this shortcoming, additional IMU (Inertial Measurement Unit) and encoder sensors were installed and utilized to calibrate the ORB-SLAM. By fusing the global information acquired by the SLAM and the dynamic local location information of the IMU and the encoder sensors, the mobile robot can be obtained the precise navigation information in the indoor environment with few feature points. The superiority of the modified ORB-SLAM was verified to compared with the conventional algorithm by the real experiments of a mobile robot navigation in a corridor environment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.10
• /
• pp.921-927
• /
• 2013

This paper presents a user interface for vision based indirect teaching of a robotic manipulator with Kinect and IMU (Inertial Measurement Unit) sensors. The user interface system is designed to control the manipulator more easily in joint space, Cartesian space and tool frame. We use the skeleton data of the user from Kinect and Wrist-mounted IMU sensors to calculate the user's joint angles and wrist movement for robot control. The interface system proposed in this paper allows the user to teach the manipulator without a pre-programming process. This will improve the teaching time of the robot and eventually enable increased productivity. Simulation and experimental results are presented to verify the performance of the robot control and interface system.

• International Journal of Ocean System Engineering
• /
• v.1 no.3
• /
• pp.165-170
• /
• 2011

In this paper, for the accurate estimation of the position and orientation of the UUV (unmanned underwater vehicle), an AHRS (Attitude Heading Reference System) was developed using the IMU (inertial measurement unit) sensor which provides information on acceleration and orientation in the object coordinate and the initial alignment algorithm and the E-KF (extended Kalman Filter). The initial position and orientation of the UUV are estimated using the initial alignment algorithm with 3-axis acceleration and geomagnetic information of the IMU sensor. The position and orientation of the UUV are estimated using the AHRS composed of 3-axis acceleration, velocity, and geomagnetic information and the E-KF. For the performance test of the orientation estimation of the AHRS, a testbed using IMU sensor(ADIS16405) and DSP28335 coded with an E-KF algorithm was developed and its performance was verified through tests.