• ETRI Journal
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• v.45 no.3
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• pp.479-491
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• 2023

The automation of agricultural machines is an irreversible trend considering the demand for improved productivity and lack of labor in handling agricultural tasks. Unstructured working environments and weather often inhibit a seemingly simple task from being fully autonomously performed. In this context, we propose a remote driving system (RDS) to aid agricultural machines designed to operate autonomously. Particularly, we modify a commercial speed sprayer for orchard environments into a robotic speed sprayer to evaluate the proposed RDS's usability and test three sensor configurations in terms of human performance. Furthermore, we propose a confidence error ellipsebased task performance measure to evaluate human performance. In addition, we present field experimental results describing how the sensor configurations affect human performance. We find that a combination of a semiautonomous line tracking device and a wide-angle camera is the most effective for spraying. Finally, we discuss how to improve the proposed RDS in terms of usability and obtain a more accurate measure of human performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.27-40
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• 2013

This study is about development of technology system for an advanced deep-sea unmanned underwater robot of S. Korea analysed by the application of scenario planning. It was developed a 6000m class next-generation deep-sea unmanned underwater vehicle(or robot, UUV) system, soonly ROV 'Hemire' and Depressor 'Henuvy' in 2006 at S. Korea and motion control, adaptive control algolithm, a work-space manipulator control algolithm, especially the underwater inertial-acoustic navigation system robust to initial errors and sensor failures. But there are remained matters on position tracking of the USBL, inertial-acoustic navigation system, attitude sensor, designed sonar sensors. So this study suggest the new idea for settle the matters and then this idea help the development of the underwater inertial-acoustic navigation system robust to initial errors and sensor failures, such as acoustic signal drop-out, by modifying the error covariance of the failed sonar signal when drop-out occurs. As a result, the future policy for deep-sea unmanned underwater robot of S. Korea is to further spur the development of new technology and more improvement of the technology level for deep-sea unmanned underwater robot system with indicator and imaginary wall as external device.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.8
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• pp.631-638
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• 2018

In this paper, we propose a method to improve the performance by guidance technique and applying it to the precision guided ammunition. The proposed method is a technique designed to reduce the target error of ammunition by reducing the projectile error without analyzing the motion characteristics of the shot. This technique is applied to the moving average filter technique which is widely used as signal processing technique to reduce the fluctuation of the output of the inboard mounting inertial sensor caused by the rotation and the coning motion of the ammunition. In order to compare the performance of the applied technique including the simple 3D guided control technique and the proposed improvement technique. It is confirmed that the application of this technique improves the accuracy of impact of the cannon - launched ammunition with severe environmental conditions and irregular motion characteristics unlike the missile.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.700-710
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• 2009

A computer vision technique of estimating the location of an unmanned ground vehicle is proposed. Identifying the location of the unmaned vehicle is very important task for automatic navigation of the vehicle. Conventional positioning sensors may fail to work properly in some real situations due to internal and external interferences. Given a DSM(Digital Surface Map), location of the vehicle can be estimated by the registration of the DSM and multiview range images obtained at the vehicle. Registration of the DSM and range images yields the 3D transformation from the coordinates of the range sensor to the reference coordinates of the DSM. To estimate the vehicle position, we first register a range image to the DSM coarsely and then refine the result. For coarse registration, we employ a fast random sample matching method. After the initial position is estimated and refined, all subsequent range images are registered by applying a pair-wise registration technique between range images. To reduce the accumulation error of pair-wise registration, we periodically refine the registration between range images and the DSM. Virtual environment is established to perform several experiments using a virtual vehicle. Range images are created based on the DSM by modeling a real 3D sensor. The vehicle moves along three different path while acquiring range images. Experimental results show that registration error is about under 1.3m in average.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.843-848
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• 2001

Most of gimballed inertial navigation systems(GNIS) are calibrated periodically to maintain their inherent accuracy. The existing calibration techniques using the conventional schuler test with the least square method and the multiposition test take a long time and have some problems in procedures. To solve this problem, calibration method using a linear Kalman filter is proposed by us. In this paper, the calibration method by the change of Schuler period is studied in order to improve the calibration performance of the gimballed INS. First of all, it is shown that the observability of Kalman filter is also enhanced the Schuler period is decreased. Simulation results show that the calibration performance using the present scheme is improved according to the decrease of the Schuler period and the calibration time is shortened extremely, too. And our proposed technique shows desirable estimation performance for the g-sensitive errors of inertial sensors in particular.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.389-394
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• 2006

Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localization technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.716-722
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• 2016

Coordinate estimation is an essential function for autonomous navigation of a mobile robot. The optical mouse sensor is convenient and cost-effective for the coordinate estimation problem. It is possible to overcome the position estimation error caused by the slip and the model mismatch of robot's motion equation using the optical mouse sensor. One of the simple methods for the position estimation using the optical mouse sensor is integration of the velocity data from the sensor with time. However, the unavoidable noise in the sensor data may deteriorate the position estimation in case of the simple integration method. In general, a mobile robot has ready-to-use motion information from the encoder sensors of driving motors. By combining the velocity data from the optical mouse sensor and the motion information of a mobile robot, it is possible to improve the coordinate estimation performance. In this paper, a coordinate estimation algorithm for an autonomous mobile robot is presented based on the well-known Kalman filter that is useful to combine the different types of sensors. Computer simulation results show the performance of the proposed localization algorithm for several types of trajectories in comparison with the simple integration method.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.695-701
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• 2008

In this paper, we propose the efficient Doppler removal method using map-based partial-time common intermediate frequency removal technique. In the proposed algorithm, the 2-stage carrier removal process was used. First, the component of common intermediate frequency is removed. Next the component of Doppler was removed with averaging and approximation. For the evaluation of the proposed algorithm, The real-time software GPS L1 C/A-code receiver was implemented. When the proposed algorithms are used, 12 tracking channels with 3 track arm(early, prompt, late) is operated real-time on PC using a Intel Pentium-III 1.0GHz CPU. Also, the requirement of memory was less than 2Mbytes. The real-time software GNSS receiver using the proposed algorithms provides the navigation solution with below 10 meter rms error. Especially, in spited of using the various approximations for implementing the algorithms, the high sensitivity capability (able to track the weak signal with -159dBm) was achieved.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.903-909
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• 2007

Mobile Robots are increasingly being used to perform tasks in unknown environment. The potential of robots to undertake such tasks lies in their ability to intelligently and efficiently search in an environment. To achieve autonomous mobile robot navigation, efficient path planner and accurate localization technique are the fundamental issues that should be addressed. This paper presents mobile robot localization using IRID(InfraRed IDentification) as artificial landmarks. IRID has highly deterministic characteristics, different from RFID. By putting several IRID emitters on the ceiling, the floor is divided into many different sectors and each sector is set to have a unique identification. Dead-reckoning provides the estimated robot configuration but the error becomes accumulated as the robot travels. IRID information tells the sector the robot is in, but the size of the uncertainty is too large if only the IRID information is used. This paper presents an algorithm which combines both the encoder and the IRID information so that the size of the uncertainty becomes smaller. It also introduces a framework which can be used with other types of the artificial landmarks. The characteristics of the developed IRID and the proposed algorithm are verified from the simulation results and experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.249-255
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• 2002

Since the stationary alignment process of the SDINS is not completely observable, some furls of the aided alignment have been applied. The purpose of this paper is to propose a new initial alignment algorithm, which utilizes the attitude output from the AGPS(Attitude Determination GPS) receiver and to demonstrate the feasibility of the proposed algorithm with several experimental results. A Kalman filter is designed for utilizing the attitude output as well as the zero velocity information. Also analyzed is the observability of the SDINS error model. To show the feasibility of the proposed scheme, we implement an alignment system where HG1700AE IMU (Inertial Measurement Unit) from Honeywell and an AGPS receiver designed at Chungnam National University are used. Test trials are done to evaluate the performance of the proposed alignment scheme. The proposed algorithm provides as good initial alignment performance as a high accurate navigation system, MAPS(Modular Azimuth Positioning System) INS.