• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.3876-3881
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• 2012

In typical master/slave teleoperation systems, a human operator generally manipulates the master to control the slave through the visual information like camera image. However, the operator may get into trouble due to the limited visual information depending on the camera positions and the delay on the visual information because of low communication bandwidth. To cope with this inherit problem in the camera-based teleoperation system, this paper presents a teleoperation system using a reconstructed graphic model instead of the camera image. The proposed teleoperation system consists of a robot control module, a master module using a force-reflective joystick, and a graphic user interface (GUI) module. The graphic user interface module provides the operator with a 3D model reconstructed using a small set of sensing data received from the remote site. The proposed teleoperation system is evaluated through a peg-in-hole assembly task.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5440-5445
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• 2014

Many studies have examined robot control using human bio signals but complicated signal processing and expensive hardware are necessary. This study proposes a method to recognize a human's hand motion using a low-cost EMG sensor and Flex sensor. The method to classify movement of the hand and finger is determined from the change in output voltage measured through MCU. The analog reference voltage is determined to be 3.3V to increase the resolution of movement identification through experiment. The robotic hand is designed to realize the identified movement. The hand has four fingers and a wrist that are controlled using pneumatic cylinders and a DC servo motor, respectively. The results show that the proposed simple method can realize human hand motion in a remote environment using the fabricated robotic hand.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6446-6451
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• 2014

Pneumatic motors are quite attractive for many applications because of their competitive price, light-weight, easy assembly, safety in hazardous areas as well as other features, such as a good force/weight ratio and operation in exceptionally harsh environments. In contrast to these advantages, pneumatic motors have limited use in applications, particularly those requiring a fast and precise response. These undesirable characteristics are due to the high compressibility of air and from the nonlinearities in pneumatic systems. This paper presents the sliding mode controller based on 3-loop(SMCB3L), which increases the load stiffness to control the rotation angle of a pneumatic motor. The characteristics for the step responses and load disturbances of the proposed controller were compared with the conventional PID controller. The experimental results showed that a properly designed SMCB3L is capable of high positioning accuracy within ${\pm}0.05mm$. Furthermore, the load stiffness of the SMCB3L can be improved 3.5 fold compared to that of PID controllers.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.868-874
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• 2014

This paper proposes a novel mapping algorithm in Omni-directional Vision SLAM based on an obstacle's feature extraction using Lucas-Kanade Optical Flow motion detection and images obtained through fish-eye lenses mounted on robots. Omni-directional image sensors have distortion problems because they use a fish-eye lens or mirror, but it is possible in real time image processing for mobile robots because it measured all information around the robot at one time. In previous Omni-Directional Vision SLAM research, feature points in corrected fisheye images were used but the proposed algorithm corrected only the feature point of the obstacle. We obtained faster processing than previous systems through this process. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we remove the feature points of the floor surface using a histogram filter, and label the candidates of the obstacle extracted. Third, we estimate the location of obstacles based on motion vectors using LKOF. Finally, it estimates the robot position using an Extended Kalman Filter based on the obstacle position obtained by LKOF and creates a map. We will confirm the reliability of the mapping algorithm using motion estimation based on fisheye images through the comparison between maps obtained using the proposed algorithm and real maps.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.210-216
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• 2016

This paper presents a novel collision avoidance technique for mobile robots based on omni-directional vision simultaneous localization and mapping (SLAM). This method estimates the avoidance path and speed of a robot from the location of an obstacle, which can be detected using the Lucas-Kanade Optical Flow in images obtained through fish-eye cameras mounted on the robots. The conventional methods suggest avoidance paths by constructing an arbitrary force field around the obstacle found in the complete map obtained through the SLAM. Robots can also avoid obstacles by using the speed command based on the robot modeling and curved movement path of the robot. The recent research has been improved by optimizing the algorithm for the actual robot. However, research related to a robot using omni-directional vision SLAM to acquire around information at once has been comparatively less studied. The robot with the proposed algorithm avoids obstacles according to the estimated avoidance path based on the map obtained through an omni-directional vision SLAM using a fisheye image, and returns to the original path. In particular, it avoids the obstacles with various speed and direction using acceleration components based on motion information obtained by analyzing around the obstacles. The experimental results confirm the reliability of an avoidance algorithm through comparison between position obtained by the proposed algorithm and the real position collected while avoiding the obstacles.

• Journal of Auto-vehicle Safety Association
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• v.9 no.4
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• pp.38-47
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• 2017

With automobiles sharply increasing worldwide, we are faced with serious social problems such as traffic accidents, traffic jams, environmental pollution, and economic inefficiency. In response, research on ITS is promoted mainly by regions with advanced automotive industry such as the US, Europe, and Japan. While Korea is working to get ahead to take global market through developing and turning into global standards systems related to ASV(Advanced Safety Vehicle), the country is not excellently prepared for such projects. The purpose of ACC is to control the vehicle's longitudinal speed and distance and minimize driver workload. Such a system should be useful in preventing accidents, as it reduces driver workload in the 21st-century world of telematics created by the development of automobile culture industry. In this light, the thesis presents a method to test and evaluate ACC system and a mathematical method to assess distance. Furthermore, for the proposed test and evaluation, theoretical values are tested with vehicle test and a database is acquired, by using vehicles equipped with an ACC system. We proposed the scenarios suitable for the domestic environment and conducted the actual road test. Theoretical evaluation criteria for developing ACC system may be employed and scenario-specific evaluation methods may find their useful application through testing the formula proposed by comparing the database and the mathematical method. and, many companies are expected to utilize the scenario in the developing stage of ACC, and be able to employ as a verification method by harnessing theoretical formula before a road test.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.70-77
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• 2014

This paper proposes a novel localization algorithm based on ego-motion which used Lucas-Kanade Optical Flow and warping image obtained through fish-eye lenses mounted on the robots. The omnidirectional image sensor is a desirable sensor for real-time view-based recognition of a robot because the all information around the robot can be obtained simultaneously. The preprocessing (distortion correction, image merge, etc.) of the omnidirectional image which obtained by camera using reflect in mirror or by connection of multiple camera images is essential because it is difficult to obtain information from the original image. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we extract motion vectors using Lucas-Kanade Optical Flow in preprocessed image. Third, we estimate the robot position and angle using ego-motion method which used direction of vector and vanishing point obtained by RANSAC. We confirmed the reliability of localization algorithm using ego-motion based on fisheye warping image through comparison between results (position and angle) of the experiment obtained using the proposed algorithm and results of the experiment measured from Global Vision Localization System.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.6
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• pp.731-738
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• 2013

This paper describes a fault-tolerant driving control strategy for an independent steer-by-wire system in sixwheel-drive/six-wheel-steering vehicles. An algorithm has been designed to realize vehicle maneuverability that is as close as possible to that of non-faulty vehicles by inducing high slip ratio of the wheel through a faulty steer-by-wire system in order to reduce the lateral tire force, which is resistant to the yaw motion. Considering the transition of the longitudinal tire force of a wheel with a faulty steer-by-wire component, the longitudinal tire forces are optimally distributed to the other wheels. Fault-tolerant driving performance has been investigated via computer simulations. Simulation studies show that the proposed algorithm can significantly improve the maneuverability of a vehicle with a faulty steer-by-wire system as compared to the optimal traction distribution method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1229-1235
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• 2014

At the LPG vehicle air intake system, most of dust particles in the air cleaner are removed. However very small particles are not removed and accumulated. The accumulation of carbon in air intake system is going to affect the idle speed control and sensor signal. It also causes engine chattering and transmission troubles of automatic transmission. This is study about cleaning up intake system using cleaning chemical. We can clean up the intake system by spraying cleaning liquid onto intake device when the engine is idling after intake hose is removed from warmed up vehicle. We can obtain the following experimental results by cleaning up ISC, surge tank, intake manifold, intake valves and combustion chamber. According to this results, the stroll valve works correctly and power rate of engine is up to the standard, it is smoothy to control the idling speed when a vehicle pulls up. After cleaning up CO grow down about 0.15%, HC does about 20~100 ppm.

• Journal of the Korean Society for Railway
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• v.11 no.3
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• pp.225-232
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• 2008

AWS (all wheel steering) is applied to improve the stability and the turning performance. Most automotive cars are mainly controlled by FWS (front wheel steering) system except some cars which are made to improve their stability by using AWS. Articulated vehicles with a pivoting joint for easy turn are difficult to make a sharp turn because of the long body and long wheelbase. Therefore applying AWS to the articulated vehicles is effective to reduce the turning radius. The AWS control method for the articulated vehicles is currently applied to only Phileas vehicles which were developed by APTS. The paper on the design of a controller to guide an articulated vehicle along the path was published but control algorithm for manual driving has not been reported. In the present paper, steering, characteristics of the Phileas vehicles have been analyzed and then new algorithm has been proposed. To verify the AWS algorithm, Commercial S/W, ADAMS was used for validity of the dynamic model and algorithm.