• The Journal of Korea Robotics Society
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• v.7 no.2
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• pp.92-100
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• 2012

A map of complex environment can be generated using a robot carrying sensors. However, representation of environments directly using the integration of sensor data tells only spatial existence. In order to execute high-level applications, robots need semantic knowledge of the environments. This research investigates the design of a system for recognizing objects in 3D point clouds of urban environments. The proposed system is decomposed into five steps: sequential LIDAR scan, point classification, ground detection and elimination, segmentation, and object classification. This method could classify the various objects in urban environment, such as cars, trees, buildings, posts, etc. The simple methods minimizing time-consuming process are developed to guarantee real-time performance and to perform data classification on-the-fly as data is being acquired. To evaluate performance of the proposed methods, computation time and recognition rate are analyzed. Experimental results demonstrate that the proposed algorithm has efficiency in fast understanding the semantic knowledge of a dynamic urban environment.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.521-525
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• 2011

Lane marking detection is one of important issues in the field of autonomous mobile robot. Especially, in urban environment, like pavement roads of downtown or tour tracks of Science Park, which have continuous patterns on the surface of the road, the lane marking detection becomes more important ability. Although there were many researches about lane detection and lane tracing, many of them used vision sensors mainly to detect lane marking. In this paper, we obtain 2 dimensional library data of 'Intensity' and 'Distance' using one laser rangefinder only. We design a simple classifier and filtering algorithm for the lane detection which uses only one LRF (Laser Range Finder). Allowing extended usage of LRF, this research provides more functionality not only in range finding but also in lane detecting to mobile robots. This work will be technically helpful for robot developers to design more simple and efficient autonomous driving system using LRF.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.160-167
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• 2016

This paper reports a localization method of a mobile robot using ceiling image. The ceiling has landmarks which are not distinguishablefrom one another. The location of every landmark in a map is given a priori while correspondence is not given between a detected landmark and a landmark in the map. Only the initial pose of the robot relative to the landmarks is given. The method uses particle filter approach for localization. Along with estimating robot pose, the method also associates a landmark in the map to a landmark detected from the ceiling image. The method is tested in an indoor environment which has circular landmarks on the ceiling. The test verifies the feasibility of the method in an environment where range data to walls or to beacons are not available or severely corrupted with noise. This method is useful for localization in a warehouse where measurement by Laser range finder and range data to beacons of RF or ultrasonic signal have large uncertainty.

• Journal of Advanced Navigation Technology
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• v.3 no.2
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• pp.97-107
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• 1999

Passive sensors such as Laser Range Finder(LRF) and Forward Looking Infrared(FLIR) camera frequently used for tracking aircraft landing produce the measurements of elevation angle contaminated by large noise due to the exhaust plume disturbance. This results in poor tracking performance if the extended Kalman filter is used for estimation of the range and elevation which are corrupted by the non-Gaussian noise such as plume disturbance. In this paper, an adaptive estimation filter and the extended Kalman filter is combined to produce a combination-type filter. In this approach the adaptive filter is used for the plume-type disturbance noise and the extended Kalman filter is utilized for the measurement of Gaussian type. The proposed combination filter is effective for the trajectory estimation of landing aircraft under the influence of unknown bias and numerical simulations illustrate the performance of the proposed filter.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.2
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• pp.202-209
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• 2014

In this paper, a developed device for detecting target's location and avoiding collision is proposed. Velocity and acceleration model of target are derived to estimate target's information, i.e. position, velocity and acceleration considering process and measurement noise. Kalman filtering method applied to the estimation process and its results was confirmed by simulation. The distance measurements system using laser sensor for moving target system is also developed to confirm the effectiveness of the proposed scheme. Experiments to get information of moving target with velocity and acceleration model was executed. The data with filtering and without filtering was compared by experiments. Discontinuous measured data was changed to smooth and continuous data by Kalman filtering. It is confirmed that desired data was obtained by applying proposed scheme. UI for measuring and monitoring the target data is developed and visual and auditory alarm function is attached on the system Finally, position estimation system of moving target with good performance is achieved by low price equipments.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.217-222
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• 2017

Recent studies for working robot in dangerous places have been carried out on large unmanned ground vehicles or 4-legged robots with the advantage of long working time, but it is difficult to apply in practical dangerous fields which require the real-time system with high locomotion and capability of delicate working. This research shows the collaborated docking system of drone and ground vehicles which combines image processing algorithm and laser sensors for effective detection of docking markers, and is finally capable of moving a long distance and doing very delicate works. We proposed the docking system of drone and ground vehicles with sensor fusion which also suggests two template matching methods appropriate for this application. The system showed 95% docking success rate in 50 docking attempts.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.453-459
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• 2006

This paper presents an experimental evaluation of wandering effect on asphalt concrete pavement responses. A laser-based wandering system has been developed and its performance is verified under various field conditions. The portable wandering system composed of two laser sensors with Position Sensitive Devices can allow one to measure the distance between laser sensors and tire edges of moving vehicle. Therefore, lateral position of each wheel on the pavement can be determined in a real time manner. Pavement responses due to different loading paths are investigated using a roll over test which is carried out on one of asphalt surfaced pavements in the Korea Highway Corporation test road. The pavement section (A5) consists of 5 cm thick surface course; 7 cm intermediate course; and 18 mm base course, and is heavily instrumented with strain gauges, vertical soil pressure cells and thermo-couples. From the center of wheel paths, seven equally-spaced lateral loading paths are carefully selected over an 140 cm wandering zone. Test results show that lateral horizontal strains in both surface and intermediate courses are mostly compressive right under the loading path and tensile strains start to develop as the loading offset becomes 40 cm from the wheel path. The development of the vertical stresses in the top layers of subbase and anti-frost is found to be minimal once the loading offset becomes 50 cm.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.361-368
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• 2015

This paper reports an unscented Kalman filter approach for localization of a mobile robot in an indoor environment. The method proposes a new model of measurement uncertainty which adjusts the error covariance according to the measured distance. The method also uses non-zero off diagonal values in error covariance matrices of motion uncertainty and measurement uncertainty. The method is tested through experiments in an indoor environment of 100*40 m working space using a differential drive robot which uses Laser range finder as an exteroceptive sensor. The results compare the localization performance of the proposed method with the conventional method which doesn't use adaptive measurement uncertainty model. Also, the experiment verifies the improvement due to non-zero off diagonal elements in covariance matrices. This paper contributes to implementing and evaluating a practical UKF approach for mobile robot localization.

• Journal of Biomedical Engineering Research
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• v.24 no.2
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• pp.83-89
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• 2003

The gas electron multiplier placed in the drift volume of conventional gas detectors, is a conceptually simple device for producing a large gas gain by concentrating the drift electric field over a very short distance to the point that electron avalanching occurs(〉 10$^4$ V/cm), greatly increasing the number of drifting electrons. This device consists of a thin insulating foil of several tens of urn in thickness. covered on each side with a thin metal layer(Cu), with tiny holes, usually 100 ${\mu}{\textrm}{m}$ or less in diameter. and with a spacing of 100-200 ${\mu}{\textrm}{m}$ through the entire foil. perforated by using chemical etching or high-powered laser beam technique In this study, we have investigated its operating properties with various experimental conditions, and demonstrated the possibility of using this device as a digital X-ray imaging sensor, by acquiring X-ray images based on the scintillation properties of the gas electron multiplier with standard CCD camera.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12B
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• pp.1236-1243
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• 2010

The perimeter defense system was created and its characteristics were evaluated. It was designed to utilize the fiber sensing device, namely OTDR(Optical Time Domain Reflectometer) which has been used for the maintenance of the optical communication network. An OTDR was constituted by a pulse laser with the nature of 1310nm, +15dBm for the observation of 400 meter optical fence. The high-speed 32-bit processor(S3C2440) has applied to MPU(Main Processor Unit) which helps to improve the performance of OTDR algorithms. Consequently, the maximum error was 0.84 meter on the performance test of the 10km monitoring and the pass criteria of ${\pm}1m$ satisfied in all the sections. The alarm delay time was under 3 sec after detecting the disorder. For the case of secondary trespassing after primary trespassing, the optical switch was installed in OTDR to monitor the secondary trespassing and to measure the multi-point detection. Therefore, this paper shows that the detections of secondary trespassing and multi-point is possible by means of optical switch.