• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.333-343
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• 2000

An automatic guidance system for combine was designed to harvest paddy rice by following a predetermined path. The automatic guidance system consisted of DGPS to locate position of combine, a gyro sensor system to measure heading angle, ultrasonic sensors to detect obstacles, a hydraulic system, microcomputer as a controller, and I/O interface system. Hydraulic cylinders and valves were installed to control movement of the combine. The heading angle and the position of the combine, and ultrasonic measurements from edge were used as the inputs of the controller. The operating position of hydraulic cylinder was determined as output of the controller. The automatic guidance system was evaluated at the 45-m straight path by changing the posture of the combine. The average RMS errors were 14.0 cm without offset and 15.0 cm with 1-m offset. The DGPS provided accurate position information within the limited error to guide the combine in the field. The results showed that the automatic guidance system could guide the combine autonomously in the paddy field when the posture of the combine was changed.

• Journal of the Society of Naval Architects of Korea
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• v.30 no.4
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• pp.8-16
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• 1993

Auto-Pilot System uses heading angle information via the position sensor and the rudder device to control the ship direction. Most of the control logics are composed of the state estimation and control algorithms assuming that the measurement device and the actuator have no fault except the measurement noise. But such asumptions could bring the danger in real situation. For example, if the heading angle measuring device is out of order the control action based on those false position information could bring serious safety problem. In this study, the control system including improved method for processing the position information is applied to the Auto-Pilot System. To show the difference between general state estimator and F.D.F., BJDFs for the sensor and the actuator failure detection are designed and the performance are tested. And it is shown that bias error in sensor could be detected by state-augmented estimator. So the residual confined in the 2-dim in the presence of the sensor failure could be unidirectional in output space and bias sensor error is much easier to be detected.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.2
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• pp.145-154
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• 2023

In this study, to control the heading angle of a ship, which is constantly subjected to various internal and external disturbances during the voyage, an LADRC (linear active disturbance rejection control) design that focuses more on improving the disturbance removal performance was proposed. The speed rate of change of the ship's heading angle due to the turn of the rudder angle was selected as a significant factor, and the nonlinear model of the ship's maneuvering equation, including the steering gear, was treated as a total disturbance. It is the similar process with an LADRC design for the first-order transfer function model. At this time, the gains of the controller included in LADRC and the gains of the extended state observer were tuned to RCGAs (real-coded genetic algorithms) to minimize the integral time-weighted absolute error as an evaluation function. The simulation was performed by applying the proposed GA-LADRC controller to the heading angle control of the Mariner class vessel. In particular, it was confirmed that the proposed controller satisfactorily maintains and follows the set course even when the disturbances such as nonlinearity, modelling error, uncertainty and noise of the measurement sensor are considered.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.67-75
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• 2010

This paper presents localization algorithm for mobile robot in outdoor environment. Outdoor environment includes the uncertainty on the ground. Magnetic sensor or IMU(Inertial Measurement Unit) has been used to estimate robot's heading angle. Two sensor is unavailable because mobile robot is electric car affected by magnetic field. Heading angle estimation algorithm for mobile robot is implemented using gyro sensor module consisting of 1-axis gyro sensors. Localization algorithm applied Extended Kalman filter that utilized GPS and encoder, gyro sensor module. Experiment results show that proposed localization algorithm improve considerably localization performance of mobile robots.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.744-749
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• 2012

In this paper, we suggest that how to improve an accuracy of mobile robot's localization by using the sensor network information which fuses the machine vision camera, encoder and IMU sensor. The heading value of IMU sensor is measured using terrestrial magnetism sensor which is based on magnetic field. However, this sensor is constantly affected by its surrounding environment. So, we isolated template of ceiling using vision camera to increase the sensor's accuracy when we use IMU sensor; we measured the angles by pattern matching algorithm; and to calibrate IMU sensor, we compared the obtained values with IMU sensor values and the offset value. The values that were used to obtain information on the robot's position which were of Encoder, IMU sensor, angle sensor of vision camera are transferred to the Host PC by wireless network. Then, the Host PC estimates the location of robot using all these values. As a result, we were able to get more accurate information on estimated positions than when using IMU sensor calibration solely.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.571-578
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• 2012

In the paper, we proposed a ring type structured light image based embedded ranging sensor for a mobile robot. Since the proposed ranging sensor obtains omnidirectional object distance, it is useful for autonomous navigation of a mobile robot. By matching the local omnidirectional distance map with a given global object map, it is possible to get position and heading angle of mobile robot in the global coordinates. Experiments for matching and navigation were carried out to verify the performance of the proposed ranging sensor.

• International Journal of Ocean System Engineering
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• v.1 no.3
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• pp.165-170
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• 2011

In this paper, for the accurate estimation of the position and orientation of the UUV (unmanned underwater vehicle), an AHRS (Attitude Heading Reference System) was developed using the IMU (inertial measurement unit) sensor which provides information on acceleration and orientation in the object coordinate and the initial alignment algorithm and the E-KF (extended Kalman Filter). The initial position and orientation of the UUV are estimated using the initial alignment algorithm with 3-axis acceleration and geomagnetic information of the IMU sensor. The position and orientation of the UUV are estimated using the AHRS composed of 3-axis acceleration, velocity, and geomagnetic information and the E-KF. For the performance test of the orientation estimation of the AHRS, a testbed using IMU sensor(ADIS16405) and DSP28335 coded with an E-KF algorithm was developed and its performance was verified through tests.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.186-186
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• 2000

In the GPS/DR integrated system, the GPS position(or velocity) is used to compensate the DR output and to calibrate errors in the DR sensor. This synergistic relationship ensures that the calibrated DR accuracy can be maintained even when the GPS signal is blocked. Because of the observability problem, however, the DR sensors are not sufficiently calibrated when the vehicle speed is low. This problem can be solved if we use a multi-antenna GPS receiver for attitude determination instead of conventional one. This paper designs a two-antenna GPS receiver integrated with DR sensors. The proposed integration system has three remarkable features. First, the DR sensor can be calibrated regardless of the vehicle speed with the aid of two-antenna GPS receiver. Secondly, the search space of integer ambiguities in GPS carrier-phase measurements is reduced to a part of the surface of the sphere using DR heading. Thirdly, the detection resolution of cycle-slips in GPS carrier-phase measurements is improved with the aid of DR heading. From the experimental result, it is shown that the search grace is drastically reduced to about 3120 of the non-aided case and the cycle-slips of 1 or half cycle can be detected.

• Journal of the Korean Institute of Navigation
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• v.21 no.3
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• pp.67-74
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• 1997

This paper described the method and the result of making a dynamic fiber optic gyrocompass measuring the heading angles of ships by processing the output signal from a constant rotating fiber optic sensor and also showed the measurement to test the performance of our system. Considerig an economical view we designed and ordered a cheap medium grade fiber densors increased not fiber length but the diameter of a fiber sensing loop. The scale factor and noise was 267mV/deg/s and 2 deg/hr/$\sqrt{Hz}(1{\sigma})$, respectively. We made the dynamic fiber optic gyrocompass by this sensor. We measured the heading angles in an arbitrary direction to evaluate the accuracy of our system and the root mean square error was $0.4^\circ$. Moreover, we measured the angles ineach direction of $45^\circ$. successive rotation to know whether this system has distoritions in a specific direction or not and the root mean square error in this case was $0.5^\circ$.