• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.327-333
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• 2007

We propose a navigation algorithm using image-based visual servoing utilizing a fixed camera. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the image error between the goal position and the position of a mobile robot. The residual function which is the image error between the position of a mobile robot and the goal position is generally large for this navigation problem. So, this navigation problem can be considered as the nonlinear least squares problem for the large residual case. For large residual, we propose a method to find the second-order term using the secant approximation method. The performance was evaluated using the simulation.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.5
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• pp.299-305
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• 2014

In this paper, a simple version of the hybrid navigation system using Kalman filter is proposed. The implemented hybrid navigation system is composed of a GPS to measure the position and the velocity, and a IMU(inertial measurement unit) to measure the acceleration and the posture of a mobile robot. A discrete Kalman filter is applied to provide the position of the robot by fusing both of the sensor data. When GPS signal is available, the navigation system estimates the position of the robot from the Kalman filter using position and velocity from GPS, and acceleration from IMU. During the interval until next GPS signal arrives, the system calculates the position of the robot using acceleration from IMU and velocity obtained at the previous step. Performance of the navigation system is verified by comparing the real path and the estimated path of the mobile robot. From experiments, we conclude that the navigation system is acceptable for the mobile robot.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.3
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• pp.117-123
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• 2017

In this paper, we propose a performance index that can compare the position estimation performance according to the time slot allocation order, which is superior in the position estimation performance in the operation of the Link-16 based relative navigation system. In order to verify the validity of the performance index, a software-based Link-16 relative navigation system performance analysis platform composed of a signal generator, a signal reception and navigation algorithm execution unit, and a performance analysis unit was designed. Using the designed software platform, we analyzed the relationship between proposed performance index and position estimation performance according to time slot allocation order in the same position reference (PR) arrangement. The performance index of the proposed time slot allocation is expected to be utilized not only for the Link-16 system, but also for the Time Division Multiple Access (TDMA)-based navigation system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.82-82
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• 2000

The way which estimates a position from Navigation is Dead-reckoning Navigation and Radio Navigation. Generally dead-reckoning navigation uses Gyro and odometer as sensor, but these have problems which are an integrating noise and a noise-sensitivity. Gps which is used by radio-navigation has a Troposthetic error and MultiPath ewer and so on. For minimizing a Troposthetic error and a Multipath error, this paper suggests to an algorithm which use vanishing point on CCD camera.

• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.287-293
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• 2018

This paper presents a satellite relative navigation strategy for formation flying, which chooses an appropriate navigation algorithm according to the operating environment. Not only global positioning system (GPS) measurements, but laser measurements can also be utilized to determine the relative positions of satellites. Laser data is used solely or together with GPS measurements. Numerical simulations were conducted to compare the relative navigation algorithm using only laser data and laser data combined with GPS data. If an accurate direction of laser pointing is estimated, the relative position of satellites can be determined using only laser measurements. If not, the combined algorithm has better performance, and is irrelevant to the precision of the relative angle data between two satellites in spherical coordinates. Within 10 km relative distance between satellites, relative navigation using double difference GPS data makes more precise relative position estimation results. If the simulation results are applied to the relative navigation strategy, the proper algorithm can be chosen, and the relative position of satellites can be estimated precisely in changing mission environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2520-2527
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• 2015

Position information is important to carry out military operations. In general, GPS is used to estimate position. However, GPS is vulnerable to jamming due to the low received signal strength, therefore GPS can be easily jammed. The relative navigation is an auxiliary navigation system defined in JTIDS. When GPS is jammed, the relative navigation requires ground reference units on the ground to operate accurately. If the ground reference unit does not exist, nodes operated by the relative navigation depend on the inertial navigation system to identify their position. However, this positioning scheme based on only INS causes accumulative position error, therefore the nodes cannot identify their position accurately for a long time. In this paper, we propose an alternative to reduce position error generated by depending inertial navigation system. In order to verify that the performance of proposed scheme is better than that of the existing scheme, various simulations are conducted.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.1
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• pp.35-44
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• 2022

In this paper, a dual foot (DF)-PDR system is proposed for the fusion of integration (IA)-based PDR systems independently applied on both shoes. The horizontal positions of the two shoes estimated from each PDR system are fused based on a particle filter. The proposed method bounds the position error even if the walking time increases without an additional sensor. The distribution of particles is a non-Gaussian distribution to express the lateral error due to systematic drift. Assuming that the shoe position is the pedestrian position, the multi-modal position distribution can be fused into one using the Gaussian sum. The fused pedestrian position is used as a measurement of each particle filter so that the position error is corrected. As a result, experimental results show that position of pedestrians can be effectively estimated by using only the inertial sensors attached to both shoes.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.289-294
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• 2023

As technologies such as cameras, Laser Imaging, Detection, and Ranging (LiDAR), and Global Navigation Satellite Systems (GNSS) become more sophisticated and common, their use in autonomous driving technologies is being explored in various fields. In the maritime area, technologies related to collision avoidance between ships are being developed to evaluate and avoid the risk of collision between ships by setting various scenarios. However, the position of each vessel used in the process of developing collision avoidance technology between vessels uses data obtained through GNSS, and may include a position error of 10 m or more depending on the situation. In this paper, a study on the dynamic safety navigation range including the positional inaccuracy of the ship is conducted. By combining the concept of the protection level obtained using GNSS raw data with a conventional safe navigation range, a safer navigation range can be calculated for dynamic navigation. The calculated range is verified using data obtained while sailing in an actual sea environment.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.75-75
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• 2000

Recently, number of navigation system using GPS and other complementary sensors has been developed to offer high-position accuracy. In this paper, an integration of GPS and Dead-Reckoning, which consists of a fiber optical gyroscope and two high-precision wheel-motor encoders for a unmanned navigation system, is presented. The main objective of this integrated GPS/DR unmanned navigation system is to provide accurate position and heading navigation data continuously for autonomous mobile robot. We propose a method for increasing the accuracy of the estimated position of the mobile robot by its DR sensors, high-precision wheel-motor encoders and a fiber optical gyroscope. We used Kalman filter theory to combine GPS and DR measurements. The performance of GPS/DR navigation system is evaluated.