• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.450-451
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• 2008

The Bimodal tram is developed in KRRI (Korea Railroad Research Institute). This vehicle will be used in the public transportation system. The Bimodal tram has the advantages of both bus and train. Bus system has the advantages of flexibility of the routes delivering passengers to the destination and easy accessibility. Train is to meet the scheduled arrival and massive public transportations. The vehicle is the rubber tired tram and is all wheel steered single articulation. The vehicle can be automatically operated by navigation control system (NCS). For the automatic driving, the vehicle lanes will be marked with permanent magnets that are buried in the road. The control algorithm developed for navigation control has to be verified before being applied in the vehicle. In this purpose, we design the simulator for controller test of the bimodal tram.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.251-257
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• 2012

Unmanned ground vehicles have important military, reconnaissance, and materials handling application. Many of these applications require the UGVs to move at high speeds through uneven, natural terrain with various compositions and physical parameters. This paper presents a framework for high speed autonomous navigation based on the integrated real time traversability. Specifically, the proposed system performs real-time dynamic simulation and calculate maximum traversing velocity guaranteeing safe motion over rough terrain. The architecture of autonomous navigation is firstly presented for high-speed autonomous navigation. Then, the integrated real time traversability, which is composed of initial velocity profiling step, dynamic analysis step, road classification step and stable velocity profiling step, is introduced. Experimental results are presented that demonstrate the method for a $6{\times}6$ autonomous vehicle moving on flat terrain with bump.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.648-654
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• 2010

In this paper, a navigation system was designed, and performance tested in order to confirm the safety improvement of the GNSS(Global Navigation Satellite System)-based AGV(Autonomous Guided Vehicle) which used only position information on of GNSS. We developed DR(Dead Reckoning) navigation system that involve the use of GNSS abnormal positoning error detection and GNSS signal outage. The test results show that GNSS positioning error is detection can be archived with an error of more than 0.15m. In addition, the DR driving position error is 1.5m for an 8s GNSS positioning service outage.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.508-511
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• 2007

Car navigation system is one of the most important applications in telematics. A newest trend of car navigation system is using real video captured by camera equipped on the vehicle, because video can overcome the semantic gap between map and real world. In this paper, we suggest a visual car navigation system that visually represents navigation information or route guidance. It can improve drivers' understanding about real world by capturing real-time video and displaying navigation information overlaid on it. Main services of the visual car navigation system are graphical turn guidance and lane change guidance. We suggest the system architecture that implements the services by integrating conventional route finding and guidance, computer vision functions, and augmented reality display functions. What we designed as a core part of the system is visual navigation controller, which controls other modules and dynamically determines visual representation methods of navigation information according to a determination rule based on current location and driving circumstances. We briefly show the implementation of system.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.702-708
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• 2013

Underwater TRN (Underwater Terrain Referenced Navigation) estimates an underwater vehicle state by measuring a distance between the vehicle and undersea terrain, and comparing it with the known terrain database. TRN belongs to absolute navigation methods, which are used to compensate a drift error of dead reckoning measurements such as IMU (Inertial Measurement Unit) or DVL (Doppler Velocity Log). However, underwater TRN is different to other absolute methods such as USBL (Ultra-Short Baseline) and LBL (Long Baseline), because TRN is independent of the external environment. As a magnetic-field-based navigation, TRN is a kind of geophysical navigation. This paper develops an EKF (Extended Kalman Filter) formulation for underwater TRN. A filter propagation part is composed by an inertial navigation system, and a filter update is executed with echo-sounder measurement. For large-initial-error cases, an adaptive EKF approach is also presented, to keep the filter be stable. At the end, simulation studies are given to verify the performance of the proposed TRN filter. With simplified sensor and terrain database models, the simulation results show that the underwater TRN could support conventional underwater navigation methods.

• Journal of Ocean Engineering and Technology
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• v.30 no.5
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• pp.367-373
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• 2016

This paper describes the development of a navigation HILS (hardware in the loop simulation) system for an integrated navigation performance analysis of a large diameter unmanned underwater vehicle (LDUUV). The HILS system was used for the performance analysis of the LDUUV. When a conventional HILS system is used, it is not possible to calculate the velocity and position using an inertial navigation system (INS). To cope with this problem, an external acceleration was generated. To evaluate the proposed method, we compare the results of a Monte Carlo simulation and navigation HILS experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.904-911
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• 2016

This paper presents a novel driving system by the humanoid robot to drive a vehicle in disaster response situations. To enhance robot's capability for substituting human activities in responding to natural and man-made disaster, the one of prerequisite skills for the rescue robot is the mounted mobility to maneuver a vehicle safely in disaster site. Therefore, our driving system for the humanoid is developed in order to steer a vehicle through unknown obstacles even under poor communication conditions such as time-delay and black-out. Especially, the proposed system includes a tele-manipulation interface and stable navigation strategies. First, we propose a new type of path estimation method to overcome limited communication. Second, we establish navigation strategies when the operator cannot recognize obstacles based on Dynamic Window Approach. The effectiveness of the proposed developments is verified through simulation and experiments, which demonstrate suitable system for driving a vehicle in disaster response.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.1
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• pp.21-29
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• 2003

The Strap Down Inertial Measurement Unit(SDIMU) is recently used for the sensor package of the modern underwater vehicles such as torpedoes and unmanned underwater-vehicles. For using SDIMU, an initial alignment must be carried out before the fire or navigation stage. The general initial alignment methods require that a mother vehicle Is a stationary condition or the Inertial Navigation System(INS) of vehicle is received the specific of data navigation from the mother vehicle. But an underwater vehicle dropped from aircraft is hard to satisfy above both necessary conditions of the general initial alignment. So, we suggest a new strap down initial alignment method of an underwater vehicle dropped from aircraft without using any aided sensors. The highlight point of this method is that a period of initial alignment is not before the fire but during running stage to fix alignment error. And we verify it by analyzing various data of S/W simulations, Hardware In the Loop Simulation(HILS) tests and sea trials.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.387-395
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• 2020

Accuracy of an integrated Global Positioning System (GPS) / Inertial Navigation System (INS) relies heavily on the visibility of GPS satellites. Especially, its accuracy is dramatically degraded in urban canyon due to signal obstructions due to large structures. In this paper, we propose a new integrated positioning system that effectively combines INS, GPS, ultrasonic sensor, and barometer in GPS-denied environments. In the proposed system, the ultrasonic sensor provides velocity information along the forward direction of moving vehicle. The barometer output provides height information compensated for the pressure variation due to fast vehicle movements. To evaluate the performance of the proposed system, an experiment was carried out by mounting the proposed system on a test car. By the experiment result, it was confirmed that the proposed system bears good potential to maintain positioning accuracy in harsh urban environments.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.2
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• pp.137-147
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• 2024

This paper presents a novel Long Short-Term Memory (LSTM) network architecture for the integration of an Inertial Measurement Unit (IMU) and Global Navigation Satellite Systems (GNSS). The proposed algorithm consists of two independent LSTM networks and the LSTM networks are trained to predict attitudes and velocities from the sequence of IMU measurements and mechanization solutions. In this paper, three GNSS receivers are used to provide Real Time Kinematic (RTK) GNSS attitude and position information of a vehicle, and the information is used as a target output while training the network. The performance of the proposed method was evaluated with both experimental and simulation data using a lowcost IMU and three RTK-GNSS receivers. The test results showed that the proposed LSTM network could improve positioning accuracy by more than 90% compared to the position solutions obtained using a conventional Kalman filter based IMU/GNSS integration for more than 30 seconds of GNSS outages.