• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.199-208
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• 2022

Inertial Navigation System (INS)/Global Navigation Satellite System (GNSS) integrated navigation system can be used for land vehicle navigation. When the GNSS signal is blocked in a dense urban area or tunnel, however, the problem of increasing the error over time is unavoidable because navigation must be performed only with the INS. In this paper, Non-Holonomic Constraints (NHC) information is utilized to solve this problem. The NHC may correct some of the errors of the INS. However, it should be noted that NHC information is not applicable to all areas within the vehicle. In other words, the lever arm effect occurs according to the distance between the Inertial Measurement Unit (IMU) mounting position and the NHC effective point, which causes the NHC condition not to be satisfied at the IMU mounting position. In this paper, an INS/GNSS/NHC integrated navigation filter is designed, and this filter has a function to compensate for the lever arm effect. Therefore, NHC information can be safely used regardless of the vehicle's driving environment. The performance of the proposed technology is verified through Monte-Carlo simulation, and the performance is confirmed through experimental test.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.611-616
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• 2008

When extracting geo-referenced 3D data from cameras mounted on Mobile Mapping Systems, one of important properties for accuracy of extracted data is the alignment of the relative translation(lever-arm) and rotation(bore-sight) between the coordinate systems of Inertial Measurement Unit(IMU)/Ground Positioning System(GPS) and cameras. Since the conventional method calculates absolute camera orientation using ground control points (GCP), the alignment is determined in one Coordinated System (GPS Coordinated System). It basically require GCP. We proposed a mathematical model for the alignment using the initially uncoupled data of cameras and IMU/GPS without GCPs.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.67-75
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• 2010

This paper presents localization algorithm for mobile robot in outdoor environment. Outdoor environment includes the uncertainty on the ground. Magnetic sensor or IMU(Inertial Measurement Unit) has been used to estimate robot's heading angle. Two sensor is unavailable because mobile robot is electric car affected by magnetic field. Heading angle estimation algorithm for mobile robot is implemented using gyro sensor module consisting of 1-axis gyro sensors. Localization algorithm applied Extended Kalman filter that utilized GPS and encoder, gyro sensor module. Experiment results show that proposed localization algorithm improve considerably localization performance of mobile robots.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.517-528
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• 2011

In this paper, we propose an indoor navigation system that can do walk safely to the destination for visually impaired persons. The proposed system analyzes images taken with the camera finds the ID of the marker to identify the absolute position of the pedestrian. Using the distance and angle obtained from IMU(Inertial Measurement Unit) accelerometer sensor and a gyro sensor, the system decides the relative position of a pedestrian for the previous position to determine the next direction. At the same time, we simplify a complex spatial structure in front of user by means of ultrasonic sensors and determine an avoidance direction by estimating the patterns. Then, it uses a few IR(Infrared Rays) sensors to detect stair. Our system offers position of visually impaired persons incorporating multiple sensors and helps users to arrive to destination safely.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.6
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• pp.373-379
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• 2015

A hybrid navigation system is implemented to apply for a mobile robot. The hybrid navigation system consists of an inertial navigation system and a global positioning system. The inertial navigation system quickly calculates the position and the attitude of the robot by integrating directional accelerations, angular speed, and heading angle from a strap-down inertial measurement unit, but the results are available for a short time since it tends to diverge quickly. Global positioning system delivers position, heading angle, and traveling speed stably, but it has large deviation with slow update. Therefore, a hybrid navigation system uses the result from an inertial navigation system and corrects the result with the help of the global positioning system where an indirect feedback Kalman filter is used. We implement and confirm the performance of the hybrid navigation system through driving a car attaching it.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.243-249
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• 2013

In this paper, GPS(Global Positioning System) that can be used outdoors and GPS(Global Positioning System) is not available for indoor Wi-Fi(Wireless Fidelity) using the Android-based location information system has been designed and implemented. Pedestrians in a room in order to estimate the location of the pedestrian's position, regardless of need to obtain the absolute position and relative position, depending on the movement of pedestrians in a row it is necessary to estimate. In order to estimate the initial position of the pedestrian Wi-Fi Fingerprinting was used. Most existing Wi-Fi Fingerprinting position error small WKNN(Weighted K Nearest Neighbor) algorithm shortcoming EWKNN (Enhanced Weighted K Nearest Neighbor) using the algorithm raised the accuracy of the position. And in order to estimate the relative position of the pedestrian, the smart phone is mounted on the IMUInertial Measurement Unit) because the use did not require additional equipment.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.18-24
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• 2015

Train positioning detection information is fundamental for high-speed railroad inspection, making it possible to simultaneously determine the status and evaluate the integrity of railroad equipment. This paper presents the results of measurements and an analysis of an inertial measurement unit (IMU) used as a positioning detection sensors. Acceleration and angular rate measurements from the IMU were analyzed in the amplitude and frequency domains, with a discussion on vibration and train motions. Using these results and GPS information, the positioning detection of a Korean tilting train express was performed from Naju station to Illo station on the Honam-line. The results of a synchronized analysis of sensor measurements and train motion can help in the design of a train location detection system and improve the positioning detection performance.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.205-211
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• 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
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• v.19 no.10
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• pp.921-927
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• 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
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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.