• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.734-745
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• 2017

The navigation system of lunar lander are composed of various navigation sensors which have a complementary characteristics such as inertial measurement unit, star tracker, altimeter, velocimeter, and camera for terrain relative navigation to achieve the precision and autonomous navigation capability. The required performance of sensors has to be determined according to the landing scenario and mission requirement. In this paper, the specifications of navigation sensors are investigated through covariance analysis. The reference error model with 77 state vector and measurement model are derived for covariance analysis. The mission requirement is categorized as precision exploration with 90m($3{\sigma}$ ) landing accuracy and area exploration with 6km($3{\sigma}$ ), and the landing scenario is divided into PDI(Powered descent initiation) and DOI(Deorbit initiation) scenario according to the beginning of autonomous navigation. The required specifications of the navigation sensors are derived by analyzing the performance according to the sensor combination and landing scenario.

• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.287-292
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• 2024

The initial suppression of fires is critical to protecting human and material resources. In response to this, fire prevention and suppression systems using artificial intelligence and robot technology have recently been studied. In particular, an autonomous driving system that detects a fire using CNN is attracting attention. These systems respond quickly in the event of a fire, enabling initial fire suppression. However, since the conventional system is not equipped with a fire suppression function, direct intervention of firefighters is required. (1) To overcome these limitations, we propose an autonomous fire detection robot system equipped with a fire suppression function ROS-based firefighting system called 'ADEFS' (Autonomous-Detect & Extinguish-Fire Service). (2) The system performs three tasks to detect and extinguish. Tasks are to run the Ros-based SLAM Navigation, YOLO-CNN, and Four-degree freedom manipulator connected to the fire extinguishing pump. (3) Through this, early response in the event of a fire can minimize damage to life and property and can reduce labor costs, which can also be expected to reduce costs for companies.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.5
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• pp.303-309
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• 2011

In this paper, an intelligent force control technique is applied to an autonomous helicopter. Although most research on the autonomous helicopter system is about navigation and control, force control of an autonomous helicopter system is quite new and not presented yet. After controlling the position of the helicopter by the LQR method, force control is applied. The adaptive impedance force control algorithm is introduced and tested to regulate the desired force under unknown location and stiffness of the environment. To compensate for uncertainty from outer disturbance, a neural network is added to form an intelligent force control framework. Simulation studies show that the proposed force control algorithm works well.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.120-126
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• 2010

This paper presents to study the path tracking method of AGV(autonomous guided vehicle) which has a laser guidance system. An existing automatic guided vehicles(AGVs) which were able to drive on wired line only had a automatic guidance system. However, the automatic guidance systems that those used had the high cost of installation and maintenance, and the difficulty of system change according to variation of working environment. To solve such problems, we make the laser guidance system which is consisted of a laser navigation and gyro, encoder. That is robust against noise, and flexible according to working environment through sensor fusion. The laser guidance system can do a perfect autonomous driving. However, the commercialization of perfect autonomous driving system is difficult, because the perfect autonomous driving system must recognize the whole environment of working space. Hence, this paper studied the path tracking of AGV using laser guidance system without wired line. The path tracking method is consisted of virtual path generation method and driving control method. To experiment, we use the fork-type AGV which is made by ourselves, and do a path tracking experiments repeatedly on same experimental environment. In result, we verified that proposed system is efficient and stable for actual fork-type AGV.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1417-1423
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• 2020

This paper proposes a waypoint guidance algorithm for the Autonomous Underwater Vehicle(AUV). The proposed simplified guidance algorithm is presented, which is combined LOS guidance and cross-track guidance for path following. Cross-track error is calculated using the position of the AUV and reference path. LOS guidance and cross-track guidance are appropriately changed according to cross-track error. And the stability of the system has been improved using variable cross-track control gain by cross-track error. Also, in this paper, navigation hardware in-the loop simulation(HILS) is implemented to verify navigation algorithm of AUV that performs combined navigation using inertial navigation device and doppler velocity log(DVL). Finally, we design integrated system HILS (including navigation HILS) for performance verification of guidance algorithm of the autonomous underwater vehicle. By comparing the sea test result with HILS result, the proposed guidance algorithm and HILS configuration were confirmed be correct.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.51-55
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• 1997

This study is devote to developing navigation filter for detecting sensor failure in multi-sensor navigation system. In multi-sensor navigation system, Kalman filter is generally used to fuse data of each sensors. Sensor failure is fatal in case that the sensor is used as external measurement of Kalman filter therefore detection and recovery of sensor failure is one the important feature of navigation filter. Generally each sensors have its specific feature in measuring navigational information. Fuzzy theory is proposed to detect external sensor failure and provide valid external measurement to Kalman filter avoiding filter divergence and instability. This idea is applied to Autonomous Underwater Vehicle(AUV) which has two navigation sensor i. e self contained inertial sensor and acoustic external sensor. 2 dimensional simulation result shows acceptable failure detection and recovery

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.391-399
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• 2018

V2X communication is a technology in which a vehicle exchanges information with various entities such as other vehicles, infrastructure, networks, pedestrians, etc. through a wired or wireless network. Recently, V2X communication technology has been steadily developed and recently it has played an important role in autonomous cooperation driving technology combined with autonomous vehicle technology. Autonomous vehicles can utilize the external information received via V2X communication to extend the recognition range of existing sensors and to support more safe and natural autonomous driving. In order to operate these autonomous cooperative vehicles on public roads, the security and reliability of autonomous V2X communication should be verified in advance. In this paper, we present test scenarios and test procedures of secure V2X communication for cooperative automated driving and present verification results.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.1
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• pp.31-40
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• 2019

In recent years, Intelligent Transport Systems (ITS) and Autonomous Vehicle Technology have actively studied around the world. In order to achieve the purpose of Advanced Driver Assistance System (ADAS) and Autonomous Vehicle Technology, it must be obtained accurate and reliable positioning. However, the problem of positioning in the urban area is a low position accuracy caused by the reduction of the number of visible satellites due to high buildings. In this paper, we analyzed the availability of precise positioning system in urban area are using GPS/BDS integrated system. For this study, GPS and BDS satellite signals were collected using two low-cost receivers in the open sky and a designed software based platform for precise positioning performance analysis. And we analyzed the precise positioning performance by changing the mask angle considering the urban area. From the results, it can be confirmed that the performance of precise positioning of GPS only and BDS only decrease in the environment where mask angle is $40^{\circ}$ to $45^{\circ}$, however, GPS/BDS integrated system maintains high performance of precise positioning.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.475-475
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• 2000

This paper describes the construction of an autonomous mobile robot with functions of collision avoidance and speech recognition that is used for teaching path of the robot. The human voice as a teaching method provides more convenient user-interface to mobile robot. For safe navigation, the autonomous mobile robot needs abilities to recognize surrounding environment and avoid collision. We use u1trasonic sensors to obtain the distance from the mobile robot to the various obstacles. By navigation algorithm, the robot forecasts the possibility of collision with obstacles and modifies a path if it detects dangerous obstacles. For these functions, the robot system is composed of four separated control modules, which are a speech recognition module, a servo motor control module, an ultrasonic sensor module, and a main control module. These modules are integrated by CAN(controller area network) in order to provide real-time communication.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.129-140
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• 2023

Autonomous driving systems are likely to be operated in various complex environments. However, the well-known integrated Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), which is currently the major source for absolute position information, still has difficulties in accurate positioning in harsh signal environments such as urban canyons. To overcome these difficulties, integrated Visual/Inertial/GNSS (VIG) navigation systems have been extensively studied in various areas. Recently, a Compressed-State Constraint Kalman Filter (CSCKF)-based VIG navigation system (CSCKF-VIG) using a monocular camera, an Inertial Measurement Unit (IMU), and GNSS receivers has been studied with the aim of providing robust and accurate position information in urban areas. For this new filter-based navigation system, on the basis of time-propagation measurement fusion theory, unnecessary camera states are not required in the system state. This paper presents a performance evaluation of the CSCKF-VIG system compared to other conventional navigation systems. First, the CSCKF-VIG is introduced in detail compared to the well-known Multi-State Constraint Kalman Filter (MSCKF). The CSCKF-VIG system is then evaluated by a field experiment in different GNSS availability situations. The results show that accuracy is improved in the GNSS-degraded environment compared to that of the conventional systems.