• Journal of Biosystems Engineering
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• v.22 no.4
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• pp.411-420
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• 1997

The mechanization efficiency using high ability machines such as tractors or combines in a paddy field rice farm is high. Mechanization in harvesting fruits and vegetables is difficult, because they are easy to be damaged. Therefore, Advanced techniques for careful handling fruits and vegetables are necessary in automation and robotization. An apple harvesting robot must have a recognition device to detect the positioning of fruit, manipulators which function like human arms, and hand to take off the fruit. This study is related to the development of a rotatic hand as the first stage in developing the apple harvesting robot. The results are summarized as follows. 1. It was found that a hand that was eccentric in rotatory motion, was better than a hand of semicircular up-and-down motion in harvesting efficiency. 2. The hand was developed to control changes in grasp forces by using tape-type switch sensor which was attatched to fingers' inside. 3. Initial finger positioning was set up to control accurate harvesting by using a tow step fingering position. 4. This study showed the possibility of apple harvesting using the developed robot hand.

• Journal of Sensor Science and Technology
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• v.16 no.4
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• pp.270-276
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• 2007

A location-aware system, which is capable to detect a user's whereabout in a region and provide real-time location information in outdoor environment is designed and fabricated, specifically using the GPS (global positioning system) as key technology in view of its stability and high precision in outdoor environment. Experiment is conducted to test this application in campus-based environment. Once GPS receiver detects specific location which is tagged with GPS coordinates, the system provides information relevant to that context and user can operate and react accordingly. Besides, this location-aware system is able to provide user with the route in order to get to a desired place by detecting the direction that the user is moving towards from his/her initial location. The mapping data is transferred via wireless LAN to PDA carried by the user as well as to the back-end system on real-time basis. The test result is analyzed and discussed to validate the effectiveness of using GPS in implementing this system and indicates future works that could be made to improve this prototype to be implemented in other applications, such as theme park, tourist attraction spot or recreational park.

• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.277-284
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• 2016

A new prediction scheme has been proposed for the robust teleoperation in a non-visible environment. The positioning error caused by the time delay in the non-visible environment has been compensated for by the Smith predictor and the sensory data have been estimated by the Grey model. The Smith predictor is effective for the compensation of the positioning error caused by the time delay with a precise system model. Therefore the dynamic model of a mobile robot has been used in this research. To minimize the unstable and erroneous states caused by the time delay, the estimated sensor data have been sent to the operator. Through simulations, the possibility of compensating the errors caused by the time delay has been verified using the Smith predictor. Also the estimation reliability of the measurement data has been demonstrated. Robust teleoperations in a non-visible environment have been performed with a mobile robot to avoid the obstacles effective to go to the target position by the proposed prediction scheme which combines the Smith predictor and the Grey model. Even though the human operator is involved in the teleoperation loop, the compensation effects have been clearly demonstrated.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.2
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• pp.49-58
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• 2019

A number of techniques have been studied to estimate the position of pedestrians in indoor space. Among them, the technique of estimating the position using only the sensors attached to the body of the pedestrian without using the infrastructure is regarded as a very important technology for special purpose pedestrians such as the firefighters. In particular, it forms a research field under the name of Pedestrian Dead Reckoning (PDR). In this paper, we focus on a method for step detection which is essential when performing PDR using Inertial Measurement Unit (IMU) mounted on a shoe. Many researches have been done to detect the stance phase where the foot contacts the ground. Most of these methods, however, have a way to detect the specific size of the sensor signal and require thresholds for these methods. This has the difficulty of changing these thresholds if the user is different. To solve this problem, we propose a stance phase detection method that does not require any threshold value. It is expected that this result will make it easier to commercialize the technology because PDR can be implemented without user-dependent parameter setting.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.279-286
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• 2022

In this paper, we designed a software library that produces integrated Global Navigation Satellite System (GNSS) / Inertial Navigation System (INS) navigation information using the raw measurements provided by the GNSS chipset, gyroscope, accelerometer and magnetometer embedded in android smartphone. Loosely coupled integration method was used to derive information of GNSS /INS integrated navigation. An application built in the designed library was developed and installed on the android smartphone. And we conducted field experiments. GNSS navigation messages were collected in the Radio Technical Commission for Maritime Service (RTCM 3.0) format by the Network Transport of RTCM via Internet Protocol (NTRIP). As a result of experiments, it was confirmed that design requirements were satisfied by deriving navigation such as three-dimensional position and speed, course over ground (COG), speed over ground (SOG), heading and protection level (PL) using the designed library. In addition, the results of this experiment are expected to be applicable to maritime navigation applications using smart device.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.351-360
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• 2022

Autonomous vehicles require precise knowledge of their position, velocity and orientation in all weather and traffic conditions in any time. And, these information is effectively used for path planning, perception, and control that are key factors for safety of vehicle driving. For this purpose, a high precision GNSS technology is widely adopted in autonomous vehicles as a core localization and navigation method. However, due to the lack of infrastructure as well as cost issue regarding GNSS correction data communication, only a few high precision GNSS technology will be available for future commercial autonomous vehicles. Recently, a high precision GNSS sensor that is based on a Broadcast-RTK system to dramatically reduce network maintenance cost by utilizing the existing broadcasting network is released. In this paper, we present the performance test result of the broadcast-RTK-based commercial high precision GNSS receiver to test the feasibility of the system for autonomous driving in Korea. Massive measurement campaigns covering of Korea region were performed, and the obtained measurements were analyzed in terms of ambiguity fixing rate, integer ambiguity loss recovery, time to retry ambiguity fixing, average correction information update rate as well as accuracy in comparison to other high precision systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1856-1864
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• 2015

In this paper, the localization algorithm for improving the accuracy of the positioning using the Wi-Fi fingerprint using the normal distribution probability and the built-in typed accelerometer sensor, the gyroscope sensor of smartphone in the indoor environment is proposed. The experiments for analyzing the performance of the proposed algorithm were carried out at the region of the horizontal and vertical 20m * 10m in the engineering school building of our university, and the performance of the proposed algorithm is compared with the fingerprint and the DR (dead reckoning) while user is moving according to the assigned region. As a result, the maximum error distance in the proposed algorithm was decreased to 2cm and 36cm compared with two algorithms, respectively. In addition to this, the maximum error distance was also less than compared with two algorithms as 16.64cm and 36.25cm, respectively. It can be seen that the fingerprint map searching time of the proposed algorithm was also reduced to 0.15 seconds compared with two algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.121-130
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• 2009

In this paper, Gaussian probability distribution model based multi-sensor data fusion algorithm is proposed for a vehicular location awareness system. Conventional vehicular location awareness systems are operated by GPS (Global Positioning System). However, the conventional system is not working in the indoor of building or urban area where the receiver is difficult to receive the signal from satellites. A method which is combined GPS and UWB (Ultra Wide-Band) has developed to improve this problem. However, vehicular is difficult to receive seamless location information since the measurement systems by both GPS and UWB convert the vehicle's movement information separately at each sensor. In this paper, normalized probability distribution model based Hybrid UWB/GPS is proposed by utilizing GPS location data and UWB sensor data. Therefore the proposed system provides information with seamless and location flexible properties. The proposed system tested by Ubisense and Asen GPS in the $12m{\times}8m$ outdoor environments. As a result, the proposed system has improved performance for accurateness and connection ability between devices to support various CNS (Car Navigation System).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.529-534
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• 2009

In this study, we investigate the feasibility of modeling entire image strips that has been acquired from the same orbital segments. We tested sensor models based on satellite orbit and attitude with different sets(Type1 ~ Type4) of unknowns. We checked the accuracy of orbit modeling by establishing sensor models of one scene using control points extracted from the scene and by applying the models to adjacent scenes within the same orbital segments. Results indicated that modeling of individual scenes with 1st or 2nd order unknowns was recommended. We tested the accuracy of around control points, digital map using the HIST-DPW (Hanjin Information Systems & Telecommunication Digital Photogrammetric Workstation) As a result, we showed that the orbit-based sensor model is a suitable sensor model for making 1/25,000 digital map.

• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.29-38
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• 2001

A navigation system was developed for autonomous guidance of a combine. It consisted of a DGPS, a machine vision system, a gyro sensor and an ultrasonic sensor. For an autonomous operation of the combine, target points were determined at first. Secondly, heading angle and offset were calculated by comparing current positions obtained from the DGPS with the target points. Thirdly, the fuzzy controller decided steering angle by the fuzzy inference that took 3 inputs of heading angle, offset and distance to the bank around the rice field. Finally, the hydraulic system was actuated for the combine steering. In the case of the misbehavior of the DGPS, the machine vision system found the desired travel path. In this way, the combine traveled straight paths to the traget point and then turned to the next target point. The gyro sensor was used to check the turning angle. The autonomous combine traveled within 31.11cm deviation(RMS) on the straight paths and harvested up to 96% of the whole rice field. The field experiments proved a possibility of autonomous harvesting. Improvement of the DGPS accuracy should be studied further by compensation variations of combines attitude due to unevenness of the rice field.