• The Journal of Korea Robotics Society
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• v.9 no.3
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• pp.154-159
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• 2014

The Global Positioning System (GPS) is widely used to aid the navigation of aerial vehicles. However, the GPS cannot be used indoors, so alternative navigation methods are needed to be developed for micro aerial vehicles (MAVs) flying in GPS-denied environments. In this paper, a real-time three-dimensional (3-D) indoor navigation system and closed-loop control of a quad-rotor aerial vehicle equipped with an inertial measurement unit (IMU) and a low-cost light detection and ranging (LIDAR) is presented. In order to estimate the pose of the vehicle equipped with the two-dimensional LIDAR, an octree-based grid map and Monte-Carlo Localization (MCL) are adopted. The navigation results using the MCL are then evaluated by making a comparison with a motion capture system. Finally, the results are used for closed-loop control in order to validate its positioning accuracy during procedures for stable hovering and waypoint-following.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.141-148
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• 2003

This paper presents a rotating ann test for assessment of an underwater hybrid navigation system for a semi-autonomous underwater vehicle. The navigation system consists of an inertial measurement unit (IMU), an ultra-short baseline (USBL) acoustic navigation sensor and a doppler velocity log (DVL) accompanying a magnetic compass. The errors of inertial measurement units increase with time due to the bias errors of gyros and accelerometers. A navigational system model is derived to include the error model of the USBL acoustic navigation sensor and the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 25 in the order. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors and correct the state equation when the measurements are available. The rotating ann tests are conducted in the Ocean Engineering Basin of KRISO, KORDI to generate circular motion in laboratory, where the USBL system was absent in the basin. The hybrid underwater navigation system shows good tracking performance against the circular planar motion. Additionally this paper checked the effects of the sampling ratio of the navigation system and the possibility of the dead reckoning with the DVL and the magnetic compass to estimate the position of the vehicle.

• Journal of Sensor Science and Technology
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• v.16 no.4
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• pp.294-300
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• 2007

Autonomous unmanned vehicle is able to find the path and the way point by itself. For the more precise navigation performance, Extended kalman filter, which is integrated with inertial navigation system and global positioning system is proposed in this paper. Extended kalman filter's performance is evaluated by the simulation and applied to the unmanned vehicle. The test result shows the effectiveness of extended kalman filter for the navigation.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.171-179
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• 2004

Today, the number of vehicle increased rapidly with the development of modem science technology, and it caused serious problems; traffic jam, accident and pollution etc. One of the solve methods these problems it is necessary to develope the vehicle navigation systems and it is already widely used to in field of military etc. Vehicle navigation system can increase the efficiency of traffic flow and offer at a drivers at a best driving conditions. In the vehicle navigation, most important thing is to measure of correct position. There are classifiable as three types. The first is G.P.S., method at artificial satellites which measures the present position and velocity any time, any where in the world at the same time. Secondly, a vehicle can determine its position and path information with a gyroscope and odometer signal, which is called Dead-Reckoning method. Thirdly, hybrid navigation system is the combined of two methods to make utilize the advantage of each navigation system. In the paper, we are analyzed to characteristics at a gyro sensor and introduce at a composition of hybrid navigation system which is combined with the G.P.S., D.R., and map-matching technique. We analyze deeply for the Map-Matching method and explain the coordinate transformation for G.P.S., and the Hybrid navigation algorithm is developed and experimented. Finally, we conclude and comment about our road test results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2311-2316
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• 2009

Lately, in the automotive market appeared keywords such as convenience, safety in presentation and increase importance of pan of vehicle. Accordingly, the use of many electronic devices was required essentially and communication between electronic devices is being highlighted. Various devices such as controllers, sensors and multimedia device(audio, speakers, video, navigation) in-vehicle connected car network such as CAN, MOST. Modem in-vehicle network managed and operated as purpose of each other. In this Paper, intelligent car navigation considering convenience and safety implement on MOST Network and present system to control CAN Network in vehicle.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.82-85
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• 2009

Lately, in the automotive market appeared keywords such as convenience, safety in presentation and increase importance of part of vehicle. Accordingly, the use of many electronic devices was required essentially and communication between electronic devices is being highlighted. Various devices such as controllers, sensors and multimedia device(audio, speakers, video, navigation) in-vehicle connected car network such as CAN, MOST. Modern in-vehicle network managed and operated as purpose of each other. In this Paper, intelligent car navigation considering convenience and safety implement on MOST Network and present system to control CAN Network in vehicle.

• Journal of Ocean Engineering and Technology
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• v.22 no.4
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• pp.106-113
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• 2008

This paper presents an underwater navigation system based on range measurements from a known reference station fixed on the sea bottom or floated at surface with a buoy, for which the system is extended to 3-dimensional coordinates. We formulated a state equation in polar coordinates and constituted an extended Kalman filter for discrete-time implementation of the navigation algorithm. The autonomous underwater vehicle, lSiMl, cruising with a constant speed can estimate its trajectory using just range measurements and additional depth, heading and pitch sensors. Simulation studies were performed to evaluate the underwater navigation of the maneuvering AUV with range measurements. We modulated the sample rate of range measurements to evaluate the effect of the update rate, and changed the initial position error of the AUV to check the robustness to estimation errors. Simulation results illustrates that the extended navigation system provides convergence of the state estimates. The navigation system was conditionally stable when it had initial position errors.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.3
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• pp.7-14
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• 2008

Unmanned vehicle has a performance for finding the path and the way point by itself, so called orientation and direction. For the more precise navigation performance, Extended kalman filter, which is integrated with inertial navigation system and global positioning system is proposed in this paper. Extended kalman filter's performance is evaluated by the simulation and applied to the unmanned vehicle. The test result shows the effectiveness of Extended kalman filter for the navigation.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.451-459
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• 2011

Fundamentally, there are 5 systems are needed for autonomous navigation of unmanned ground vehicle: Localization, environment perception, path planning, motion planning and vehicle control. Path planning and motion planning are accomplished based on result of the environment perception process. Thus, high reliability of localization and the environment perception will be a criterion that makes a judgment overall autonomous navigation. In this paper, via map matching using vehicle dynamic model and LIDAR sensors, replace high price localization system to new one, and have researched an algorithm that lead to robust autonomous navigation. Finally, all results are verified via actual unmanned ground vehicle tests.

• Journal of Biosystems Engineering
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• v.33 no.6
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• pp.423-429
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• 2008

This study was performed to investigate the effects of inertial navigation system (INS) / global positioning system (GPS) sensor fusion for agricultural vehicle navigation. An extended Kalman filter algorithm was adopted for INS/GPS sensor fusion in an integrated mode, and the vehicle dynamic model was used instead of the navigation state error model. The INS/GPS system was consisted of a low-cost gyroscope, an odometer and a GPS receiver, and its performance was tested through computer simulations. When measurement noises of GPS receiver were 10, 1.0, 0.5, and 0.2 m ($1{\sigma}$), RMS position and heading errors of INS/GPS system at 5 m/s straight path were remarkably reduced with 10%, 35%, 40%, and 60% of those obtained from the GPS receiver, respectively. The decrease of position and heading errors by using INS/GPS rather than stand-alone GPS can provide more stable steering of agricultural equipments. Therefore, the low-cost INS/GPS system using the extended Kalman filter algorithm may enable the self-autonomous navigation to meet required performance like stable steering or more less position errors even in slow-speed operation.