• Journal of Biosystems Engineering
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• v.20 no.3
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• pp.226-235
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• 1995

An unmanned speed sprayer was developed using a remote control and an inductive cable guidance systems to protect operators and environment from hazardous pesticides. The sprayer consists of a remote control system, an induction system, obstacle detectors, control actuators and an one-chip microcomputer. The sprayer can be operated by the induction guidance and/or remote control. The following summarize characteristics of the developed speed sprayer. 1) Both the remote control and the induction guidance operation were possible with the developed speed sprayer. 2) Sixteen functions of the forwarding, backing, halting, steering, 3-way valve for nozzles and fan operating etc. were utilized on the remote control system. 3) It was concluded that the DTMF method, having less transmitting error, performed better than the FSK method for an agricultural remote controller. A radio station may be necessary. 4) The digital inductive guidance system, consisting of five low-impedance detection coils and a window comparator circuit, performed better than the analog detecting system, guiding route using inductive voltage differential from tow detection coils.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.192-198
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• 2023

This paper proposes an algorithm for autonomous mobile robots to effectively navigate obstacles. In order to detect obstacles infrared sensors and cameras are employed. The infrared sensor is utilized to calculate the distance to obstacles while the captured images from the camera are used to determine the width of obstacles. To compute obstacle width, binary image processing, contour detection, and the minimum area rectangle technique are employed. Using the distance to obstacles and obstacle width, the avoidance angle is calculated, and this angle is incorporated into steering control. The proposed obstacle avoidance algorithm was implemented on an autonomous robot, and experimental results demonstrated a maximum reduction in avoidance time by 8.5 seconds compared to using only infrared sensors when the obstacle width is 30cm.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.84-92
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• 2000

Recently, the progress of industrialization has been taken concern of material handling automation. So for, the conveyor belt has been popular for material handling. However, this system has many disadvantages such as the space, cost, etc. In this paper, a new navigation algorithm using fuzzy is introduced. The mobile robot follows a line installed on the roads. These informations are inputted with three approximate sensors. These obtained informations are analyzed with fuzzy control technique fur autonomous steering. Therefore, unlike existing systems, high reliability is guaranteed under bad environment conditions. The installation and maintenance of a line is easily made at lower cost. This developed mobile robot can be applied to material handling automation in manufacturing system, hospital, inter-office document del ivory.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.67-70
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• 2008

본 논문에서는 자계표식기반 안내시스템을 이용한 차량의 무인주행을 제안한다. 자계기반 안내시스템에서 가장 중요한 것은 자계도로상의 자석의 위치예측이다. 자석의 위치를 예측하기 위하여 자석과 센서의 상관관계를 해석하여 도로에 매설된 자석의 위치를 검출하기 위한 배열형 자계표식위치인식센서를 개발하였다. 또한 자동모드와 수동모드의 동작을 위해 스텝모터를 이용한 조향제어장치를 개발하였다. 자율주행 실험을 위해 자계기반 자계도로를 구성하였다. 그리고 로봇형 차량을 자계도로에서 실험을 통해 실용성을 입증하였다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.735-743
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• 2012

In this paper, we present model predictive control (MPC) applied to lane keeping system (LKS) based on a vision module. Due to a slow sampling rate of the vision system, the conventional LKS using single rate control may result in uncomfortable steering control rate in a high vehicle speed. By applying MPC using multi-rate Kalman filter to active steering control, the proposed MPC-based active steering control system prevents undesirable saturated steering control command. The effectiveness of the MPC is validated by simulations for the LKS equipped with a camera module having a slow sampling rate on the curved lane with the minimum radius of 250[m] at a vehicle speed of 30[m/s].

• Journal of Sensor Science and Technology
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• v.12 no.5
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• pp.211-217
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• 2003

This paper is proposed that roadway recognition performance improvement for autonomous vehicle using magnetic markers that are embedded along the road center and the sensors mounted on a vehicle, and which changing of magnetic field that is measured along with vehicle driving. For Retrenchment of equipment cost, interval of markers is more expensive than existing method. In order to this, This paper is proposed that interval of markers is founded using magnetic field analysis, and which arrangement method of six magnetic sensors and control method of neural network. This paper is carried out magnetic field analysis, the acquiring of the training patterns, the training of the neural network and composition of steering control, and is verified that roadway recognition performance can improve using computer simulation with proposed methods.

• Journal of Drive and Control
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• v.12 no.3
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• pp.36-43
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• 2015

An autonomous vehicle control algorithm based on Ackerman Geometry is known to be reliable in low tire slip situation. However, vehicles at high speed make lateral errors due to high tire slip. In this paper, considering the tire slip of vehicles, the steering angle is determined based on the Ackerman Geometry and is supplemented tire slip angle by the Stanley steering algorithm. In addition, to prevent the tire slip, the algorithm, which restricts steering if a certain level of slip occurs, is used to reduce the lateral error. While many studies have been extended to include vehicle slip, studies also need to be carried out on the tire slip depending on hardware performance. The control algorithm of autonomous vehicles is compensated considering the sensor noise and the performance of steering actuator. Through the various simulations, it was found that the performance of steering actuator was the key factor affecting the performance of autonomous driving. Also, it was verified that the usefulness of steering algorithm considering the tire slip and performance of steering actuator.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.199-209
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• 2015

This paper presents a model predictive control (MPC) approach to control the steering angle in an autonomous vehicle. In designing a highly automated driving control algorithm, one of the research issues is to cope with probable risky situations for enhancement of safety. While human drivers maneuver the vehicle, they determine the appropriate steering angle and acceleration based on the predictable trajectories of surrounding vehicles. Likewise, it is required that the automated driving control algorithm should determine the desired steering angle and acceleration with the consideration of not only the current states of surrounding vehicles but also their predictable behaviors. Then, in order to guarantee safety to the possible change of traffic situation surrounding the subject vehicle during a finite time-horizon, we define a safe driving envelope with the consideration of probable risky behaviors among the predicted probable behaviors of surrounding vehicles over a finite prediction horizon. For the control of the vehicle while satisfying the safe driving envelope and system constraints over a finite prediction horizon, a MPC approach is used in this research. At each time step, MPC based controller computes the desired steering angle to keep the subject vehicle in the safe driving envelope over a finite prediction horizon. Simulation and experimental tests show the effectiveness of the proposed algorithm.

• Korean Journal of Agricultural Science
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• v.37 no.1
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• pp.123-130
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• 2010

A steering control system based on CAN(Controller Area Network) for autonomous tractor was developed to reduce duty of a central processing computer and to improve performance of steering control in terms of reduced control interval and error. The steering control system consisted of a SCU (Steering Control Unit), an EHPS system, and a potentiometer. The SCU consisted of an MCU (Micro Controller unit), an A/D converter, and a DC-DC converter, and a PID controller was used to control steering angle. The steering control system was communicated with the computer by CAN-bus. Each actuator and implement was connected to a multi-function board interfacing with the computer through a USB cable. Without CAN, control interval of the autonomous tractor was 1.5 seconds. When the CAN-based steering control system was combined with the autonomous tractor, however, control interval of the integrated system was reduced to those less than 0.05 seconds. When the autonomous tractor was operated with 1.5-s and 0.05-s control cycles at a 0.63-m/s travelling speed, the trajectories were close to straight lines for both of the control cycles. For a 1.34-m/s traveling speed, tractor trajectory was close to sine wave with a 1.5-s control cycle, but was straight line with a 0.05-s control cycle.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2365-2368
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• 2001

This paper describes a fuzzy steering controller for an autonomous mobile robot with MR sensor. Using the magnetic field($B_{x}$, $B_{y}$, $B_{z}$) obtained from the MR sensor, we designed fuzzy controller for driving on the road center. Fuzzy rule base was built to magnetic field($B_{x}$, $B_{y}$, $B_{z}$). To develop an autonomous mobile robot simulation program, we have done modeling MR sensor, dynamic model of mobile robot and coordinate transformation. A computer simulation of the robot (including mobile robot dynamics and steering) was used to verify the steering performance of the mobile robot controller using the fuzzy logic. Good results were obtained by computer simulation. So, we confirmed the robustness of the proposed fuzzy controller by computer simulation. Also, we know that proposed control algorithm was applied to real autonomous mobile robot.