• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.4131-4138
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• 2012

In this paper, we propose a Pedestrian Position Information System(PPIS) using low-cost inertial sensors in GPS-disabled area. The proposed scheme estimates the attitude/heading angle and step detection of pedestrian. Additionally, the estimation error due to the inertial sensors is mitigated by using additional sensors. We implement a portable hardware module to evaluate performance of the proposed system. Through the experiments in indoor building, the estimation error of position information was measured as 2.4% approximately.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.2
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• pp.137-144
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• 2015

In this paper, we present an inertial sensor-based gait analysis system to measure and analyze lower-limb movements. We developed an integral AHRS(Attitude Heading Reference System) using a combination of rate gyroscope, accelerometer and magnetometer sensor signals. Several AHRS modules mounted on segments of the patient's body provide the quaternions representing the patient segments's orientation in space. And a method is also proposed for calculating three-dimensional inter-segment joint angle which is an important bio-mechanical measure for a variety of applications related to rehabilitation. To evaluate the performance of our AHRS module, the Vicon motion capture system, which offers millimeter resolution of 3D spatial displacements and orientations, is used as a reference. The evaluation resulted in a RMSE(Root Mean Square Error) of 1.08 and 1.72 degree in yaw and pitch angle. In order to evaluate the performance of our the gait analysis system, we compared the joint angle for the hip, knee and ankle with those provided by Vicon system. The result shows that our system will provide an in-depth insight into the effectiveness, appropriate level of care, and feedback of the rehabilitation process by performing real-time limb or gait analysis during the post-stroke recovery.

• Geophysics and Geophysical Exploration
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• v.23 no.3
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• pp.208-214
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• 2020

In this study, we have developed a drone magnetic exploration system (proto-type) using a fluxgate magnetic sensor. Hardware of the system consists of a fluxgate magnetometer, an inertial measurement unit (IMU), a GPS, and a communication module. And we have developed monitoring software, which enables it to transmit the measured data to the ground control system (GCS) in real time. The measured magnetic data are finally saved as 1 Hz data after passing through a notch filter and a band-pass filter. For verification of this system, a preliminary test was conducted to check the magnetic responses of a magnetic object first, then the field test was carried out in two iron mines. We tested the developed system on the field test in Pocheon, Gyeonggi and Jeongseon, Gangwon. The magnetic data from the developed drone system was very similar to those from unmanned airship system developed by Korea Institute of Geoscience and Mineral Resources (KIGAM). As a result, preliminary experiment and field test have demonstrated that this system is applicable for outdoor aeromagnetic exploration. It requires more studies to improve filter function and instrument performance to minimize noise in the future.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.489-497
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• 2010

This paper presents the design of hardware platform, which is a test bed for the navigation system and hovering type AUV (Autonomous Underwater Vehicle) under the OCP (Open Control Platform). The developed AUV test bed consists of two hulls, four thrusters, and the navigation system which uses a SBC2440II with IMU (Inertial Measurement Unit). And the SMC (Sliding Mode Control) is chosen for the diving and steering control of the AUV. This paper uses ACE/TAO RTEC (Real-Time Event Channel) as a middleware platform in order to control and communicate in the developed AUV test bed. In this paper, two computers are used and each of them is dedicated for the specific purpose, the first computer is used as the SMC module and the middleware platform for the ACE/TAO RTEC and the second computer is used for the sensor controller. We analyze the performance of the AUV test bed under the OCP.