• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.5
• /
• pp.429-435
• /
• 2011

This paper presents a sensor fusion-based estimation of heading and a Bezier curve-based motion planning for unmanned ground vehicle. For the vehicle to drive itself autonomously and safely, it should estimate its pose with sufficient accuracy in reasonable processing time. The vehicle should also have a path planning algorithm that enables to adapt to various situations on the road, especially at intersections. First, we address a sensor fusion-based estimation of the heading of the vehicle. Based on extended Kalman filter, the algorithm estimates the heading using the GPS, IMU, and wheel encoders considering the reliability of each sensor measurement. Then, we propose a Bezier curve-based path planner that creates several number of path candidates which are described as Bezier curves with adaptive control points, and selects the best path among them that has the maximum probability of passing through waypoints or arriving at target points. Experiments under various outdoor conditions including at intersections, verify the reliability of our algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.13 no.2
• /
• pp.27-33
• /
• 2014

This paper proposes a gradation image processing method for the development of a Road Sign Recognition Platform (RReP), which aims to facilitate the rapid and accurate management and surveying of approximately 160,000 road signs installed along the highways, national roadways, and local roads in the cities, districts (gun), and provinces (do) of Korea. RReP is based on GPS(Global Positioning System), IMU(Inertial Measurement Unit), INS(Inertial Navigation System), DMI(Distance Measurement Instrument), and lasers, and uses an imagery information collection/classification module to allow the automatic recognition of signs, the collection of shapes, pole locations, and sign-type data, and the creation of road sign registers, by extracting basic data related to the shape and sign content, and automated database design. Image division and merging, which were applied in this study, produce superior results compared with local binarization method in terms of speed. At the results, larger texts area were found in images, the accuracy of text recognition was improved when images had been gradated. Multi-threshold values of natural scene images are used to improve the extraction rate of texts and figures based on pattern recognition.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.28 no.11
• /
• pp.894-901
• /
• 2017

In the existence of motion, azimuth phase error due to accuracy limitation of GPS/IMU and system delay is unavoidable and it is essential to apply autofocus to estimate and compensate the azimuth phase error. In this paper, autofocus algorithm using MWLS(Modified WLS) is proposed. It shows the robust performance compared with original WLS using new target selection/sorting metric and iterative azimuth phase estimation technique. SAR raw data obtained in a captive flight test is used to validate the performance of the proposed algorithm.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.169-174
• /
• 2002

In this paper, we suggest a new spatial information system called video GIS where video is used for spatial data construction and is integrated with map. We develop a prototype system of video GIS and apply it to roadside facility management. The main functions supported by the suggested system are data collection, coordinate calculation and conversion, data construction, analysis, searching, and browsing. The stereo images and corresponding position data are collected by a vehicle named 4S-Van that has GPS, IMU, and cameras. The 3-D coordinates of the objects in the images, such as road sign, signal lamp, and building, can be calculated and constructed from the collected data. The spatial objects are displayed on both image and map, and can be searched and browsed, which enables visual and realistic browsing and management of spatial objects. Compared to conventional field survey used in roadside facility management, the method enables faster, easier, and more efficient construction of spatial data. The suggested video GIS can be applied not only to roadside facility management but also to many similar projects of central or local governments that are related to GIS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.5
• /
• pp.535-544
• /
• 2016

Even though existing methods for orthophoto production using expensive aircraft are effective in large areas, they are drawbacks when dealing with renew quickly according to geographic features. But, as UAV(Unmanned Aerial Vehicle) technology has advanced rapidly, and also by loading sensors such as GPS and IMU, they are evaluates that these UAV and sensor technology can substitute expensive traditional aerial photogrammetry. Orthophoto production by using UAV has advantages that spatial information of small area can be updated quickly. But in the case of existing researches, images of same altitude are used in orthophoto generation, they are drawbacks about repetition of data and renewal of data. In this study, we targeted about small slope area, and by using low-end UAV, generated orthophoto and DEM(Digital Elevation Model) through different altitudinal images. The RMSE of the check points is σ_h = 0.023m on a horizontal plane and σ_v = 0.049m on a vertical plane. This maximum value and mean RMSE are in accordance with the working rule agreement for the aerial photogrammetry of the National Geographic Information Institute(NGII) on a 1/500 scale digital map. This paper suggests that generate orthophoto of high accuracy using a different altitude images. Reducing the repetition of data through images of different altitude and provide the informations about the spatial information quickly.

• Journal of Korean Society of Transportation
• /
• v.30 no.3
• /
• pp.43-55
• /
• 2012

Bicycle is an environment-friendly transport mode contributing to a more sustainable transportation systems. To innovatively increase the use of bicycle as a significant transport mode, bicycle-friendly roadway environment should be provided. This study proposes a method to evaluate cycling environment based on the analysis of data collected from an specially equipped probe bicycle. The inertial measurement unit(IMU) consisting of a gyro sensor, accelerometer, and a global positioning systems(GPS) receiver was installed on the probe bicycle. Cycling stability index(CSI) and bicycle speed data were used as inputs of the proposed evaluation framework adopting the Fault Tree Analysis, which is a well-known technique for the risk analysis. The outcomes of this study will serve as an intelligent assesment tool for cycling environment.

• The Journal of Korea Robotics Society
• /
• v.8 no.1
• /
• pp.51-57
• /
• 2013

Recently, the number of jellyfish has been rapidly grown because of the global warming, the increase of marine structures, pollution, and etc. The increased jellyfish is a threat to the marine ecosystem and induces a huge damage to fishery industries, seaside power plants, and beach industries. To overcome this problem, a manual jellyfish dissecting device and pump system for jellyfish removal have been developed by researchers. However, the systems need too many human operators and their benefit to cost is not so good. Thus, in this paper, the design, implementation, and experiments of autonomous jellyfish removal robot system, named JEROS, have been presented. The JEROS consists of an unmanned surface vehicle (USV), a device for jellyfish removal, an electrical control system, an autonomous navigation system, and a vision-based jellyfish detection system. The USV was designed as a twin hull-type ship, and a jellyfish removal device consists of a net for gathering jellyfish and a blades-equipped propeller for dissecting jellyfish. The autonomous navigation system starts by generating an efficient path for jellyfish removal when the location of jellyfish is received from a remote server or recognized by a vision system. The location of JEROS is estimated by IMU (Inertial Measurement Unit) and GPS, and jellyfish is eliminated while tracking the path. The performance of the vision-based jellyfish recognition, navigation, and jellyfish removal was demonstrated through field tests in the Masan and Jindong harbors in the southern coast of Korea.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.2
• /
• pp.390-396
• /
• 2015

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalizations of LBS is the accurate estimating position for mobile object. Focusing on an image sensor deployed in smart phone, we develop a LED based positioning estimation framework. The developed approaches can strengthen the advantages of independent indoor applicability of LED. The estimation of LED based positioning is effectively applied to any indoor environment. We put a focus especially on the algorithmic framework. of image processing of smart phone. From LED lighting, we can obtain a typical signal image which contains the unique positioning information. Furthermore test-bed based on smart phone platform is practically developed and all data have been harvested from the actual measurement of test indoor area. This can approve the practical usefulness of proposed framework.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1125-1139
• /
• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.