• Journal of Drive and Control
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• v.13 no.1
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• pp.49-53
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• 2016

The accurate calculation of bucket tip position has a large influence on showing the motion of an excavator on the display device of the excavator and controlling the excavator automatically. It is generally known that Inertial Measurement Unit (IMU) sensors are more accurate than accelerometer-based sensors while the boom, arm or bucket moves because additional forces beyond gravity add additional acceleration to the sensors. To prove the accuracy difference between the two types of sensors, a position recognition system using an accelerometer-based sensor and an IMU sensor is implemented on the excavator. The experimental results show that the system using the IMU sensor significantly reduces the position recognition error while bucket moves and additional force beyond gravity exists.

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

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.65-72
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• 2012

With the development of MEMS, small and low-priced sensors integrating IMU and GPS have produced and exploited for diverse field. In this research, we have judged that MEMS-based IMU/GPS sensor is suitable for light-weighted mobile mapping system and carried out experiments to analyze the characteristics of MTi-G, which was developed from XSens company. From a sensor which fixed to dashboard, coordinates results with no post-processing were achieved for test area. On the whole, the results show satisfactory performances but some errors also were discovered from parts of the road due to sensor properties, XKF characteristics and GPS reception environment. We could confirm the potential of light-weighted mobile mapping system. Experiments considering various GPS reception environments and road condition and more detailed level of accuracy analysis will be performed for further research.

• Journal of Sensor Science and Technology
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• v.25 no.3
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• pp.202-207
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• 2016

Estimation of vertical position is critical in applications of sports science and fall detection and also controls of unmanned aerial vehicles and motor boats. Due to low accuracy of GPS(global positioning system) in the vertical direction, the integration of IMU(inertial measurement unit) with the GPS is not suitable for the vertical position estimation. This paper investigates an IMU-barometer integration for estimation of vertical position (as well as vertical velocity). In particular, a new two-step Kalman/complementary filter is proposed for accurate and efficient estimation using 6-axis IMU and barometer signals. The two-step filter is composed of (i) a Kalman filter that estimates vertical acceleration via tilt orientation of the sensor using the IMU signals and (ii) a complementary filter that estimates vertical position using the barometer signal and the vertical acceleration from the first step. The estimation performance was evaluated against a reference optical motion capture system. In the experimental results, the averaged estimation error of the proposed method was 19.7 cm while that of the raw barometer signal was 43.4 cm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.10
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• pp.53-59
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• 2004

A calibration technique for a redundant IMU with low-grade inertial sensors is proposed. In order to calibrate the redundant IMU that can detect and isolate a faulty sensor, the fundamental coordinate frames in the IMU are defined and the IMU error is modeled based on the frames. Equations to estimate the error coefficients of the redundant IMU are formulated, and a test sequence using the 2-axis rate table is also presented. Finally, a redundant IMU with cone configuration is implemented using the low-grade inertial sensors and the performance of the proposed technique is verified by some experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.179-186
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• 2015

In this paper, a novel lateral control system is proposed for the purpose of improving lane keeping performance which is independent from GPS signals. Lane keeping is a key function for the realization of unmanned driving systems. In order to obtain this objective, a vision sensor based real-time lane detection scheme is developed. Furthermore, we employ a data fusion along with a real-time steering angle of the test vehicle to improve its lane keeping performance. The fused direction data can be obtained by an IMU sensor and vision sensor. The performance of the proposed system was verified by computer simulations along with field tests using MOHAVE, a commercial vehicle from Kia Motors of Korea.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.5
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• pp.439-446
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• 2019

A real time transporter locating system for shipyard has been implemented through the GNSS and IMU sensor. There are a lot of block movements by transporters at the shipyard, which need to be controlled and monitored for conforming to the shipbuilding process. For the precise and safe transporter motion at the yard, a locating system has been developed by using the GNSS and IMU sensors for the transporter. There are several obstacles of the GPS signals for locating the transporter at the yard, such as, buildings and metal structures. To overcome the weakness of the GPS signal transmission, the IMU data have been properly integrated together. The performance of the proposed real time block locating system has been verified through the real experiments with transporters carrying blocks at a shipyard.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1011-1019
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• 2019

In this paper, we propose a system that can more precisely identify and monitor the position of the tool used in the assembling workplace such as automobile production. The proposed positioning monitoring system is a combination of UWB communication module and MEMS IMU sensor. Since UWB does not need modulation and demodulation function and has low power density, UWB is widely used in indoor positioning field. However, it may cause positioning error due to errors in RF transmission and reception process, which may cause positioning accuracy. Therefore, in this paper, we propose an algorithm that uses IMU as an auxiliary means to compensate for errors that may occur in positioning using only UWB. The tag and anchor of UWB module measure the transmission / reception time by transmitting signals to each other and then estimate the distance between tag and anchor. The MEMS IMU sensor serves to provide positioning calibration information. The tag, which is a mobile node and attached to a moving tool, measures the three-dimensional position of the tool and transfers the coordinate data to the anchor. Thus, it is possible to confirm whether or not the specific tool is properly used according to the prescribed regulations.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.11-18
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• 2008

This study is implementation of attitude control system(ACS - Attitude Control System). for a multi legs robot. This study designs H/W of Inertial Measurement Unit (IMU) and attitude control algorithm S/W. Compare performance with Mtx and MTx in order to verify action performance of this system after implementation, and will verify a system integrated IMU of a multi-legs robot. ACS uses Gyro and an accelerometer and an earth magnetism sensor, and it is a system controlling a roll, pitch angle attitude of an object. Generally, low price MEMS is difficult to calculate a correct situation of an object as an error occurs severely the Inertial sensor. This study implements IMU in order to develop ACS as use MEMS, accelerometer, Gyro sensor and earth magnetism sensor. Design algorithm each a roll, pitch, yaw attitude guaranteeing regular performance, and do poling in a system as include an attitude calculation program in an IMU system implemented. Mixed output of Gyro and an accelerometer, and recompensed a roll, pitch angle, and loaded in this study on a target platform in order to implement the ACS which guaranteed performance more than a continuously regular level, and operated by real time, and did porting, and verified.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.525-528
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• 2003

In this paper, we present a novel idea to integrate low cost Inertial Measurement Unit(IMU) and Differential Global Positioning System (DGPS) for Telematics applications. As well known, low cost IMU produces large positioning and attitude errors in very short time due to the poor quality of inertial sensor assembly. To conquer the limitation, we present a bimodal approach for integrating IMU and DGPS, taking advantage of positioning and orientation data calculated from CCD images based on photogrammetry and stereo-vision techniques. The positioning and orientation data from the photogrammetric approach are fed back into the Kalman filter to reduce and compensate IMU errors and improve the performance. Experimental results are presented to show the robustness of the proposed method that can provide accurate position and attitude information for extended period for non-aided GPS information.