• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2588-2590
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• 2003

The part of manipulators is normally studied with regularized environmental conditions. however, it is the most difficult that the part of AMR must be studied with uncertainty in the environmental conditions. The part of AMR has skelton, sensor fusion, path planning etc. This paper is the research of the local pass planning that gathers information about external environment using neural network from each sensors and designs the algorithm which can determine which correct direction the robot can find. As the result of the research, AMR has been able to drive similarly as if the expert does and has been able to observe it acting without any control.

• Journal of KIBIM
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• v.6 no.2
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• pp.19-28
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• 2016

Social costs analysis seeks to reveal the environmental effects of transportation policy. It delivers a sense of the effects of the public's daily travel and the costs that are or would be incurred from individual trips. Moreover, the accumulated total number of trips will uncover the effects of travel on society. This article shows the quantitative analysis of the economic outcomes of travel using social costs estimation methods. In order to support urban planning tasks, this research implemented analysis tool for social costs estimation by travel behavior. For a case study, a jave based application which can convert people's trip data into social costs is developed. the application used for simulating student-housing effects by estimating social costs changes. The analysis included the attributes, building scale and locational changes of the student housing as well as transforms of the students' trips.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.314-319
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• 2005

When a robot navigates in the real environment, it frequently meets various environments that can be expressed by simple geometrical shapes such as fiat floor, uneven floor, floor with obstacles, slopes, concave or convex corners, etc. Among them, the convex corner composed of two plain surfaces is the most difficult one for the robot to negotiate. In this paper, we propose a gait planning algorithm to help the robot overcome the convex environment. The trajectory of the body is derived from the maximum distance between the edge boundary of the corner and the bottom of the robot when it travels in the convex environment. Additionally, we find the relation between kinematical structure of the robot and its ability of avoiding collision. The relation is realized by considering the workspace and the best posture of the robot in the convex structure. To provide necessary information for the algorithm, we use an IR sensor attached in the leg of the robot to perceive the convex environment. The validity of the gait planning algorithm is verified through simulations and the performance is demonstrated using a quadruped walking robot, called "MRWALLSPECT III"( Multifunctional Robot for WALL inSPECTion version 3).

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.16-22
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• 2023

This paper presents a proactive longitudinal motion planning algorithm for improving the safety of an automated bus. Since the field of view (FOV) of the autonomous vehicle was limited depending on onboard sensors' performance and surrounding environments, it was necessary to implement vehicle-to-vehicle (V2V) communication for overcoming the limitation. After a virtual V2V-equipped target was constructed considering information obtained from V2V communication, the reference motion of the ego vehicle was determined by considering the state of both the V2V-equipped target and the sensor-detected target. Model predictive control (MPC) was implemented to calculate the optimal motion considering the reference motion and the chance constraint, which was deduced from manual driving data. The improvement in driving safety was confirmed through vehicle tests along actual urban roads.

• 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 Institute of Intelligent Systems
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• v.19 no.3
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• pp.381-387
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• 2009

This paper is presented simultaneous localization and mapping (SLAM) based on feature map and path-planning using modified genetic algorithm for efficient driving of autonomous vehicle. The biggest problem for autonomous vehicle from now is environment adaptation. There are two cases that its new location is recognized in the new environment and is identified under unknown or new location in the map related kid-napping problem. In this paper, SLAM based on feature map using ultrasonic sensor is proposed to solved the environment adaptation problem in autonomous driving. And a modified genetic algorithm employed to optimize path-planning. We designed and built an autonomous vehicle. The proposed algorithm is applied the autonomous vehicle to show the performance. Experimental result, we verified that fast optimized path-planning and efficient SLAM is possible.

• Journal of Sensor Science and Technology
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• v.15 no.2
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• pp.102-105
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• 2006

In-vivo dosimetry is an essential tool of quality assurance programs in radiotherapy. The most commonly used techniques to verify dose are thermoluminescence dosimeter (TLD) and diode detectors. Metal oxide semiconductor field-effect transistor (MOSFET) has been recently proposed for using in radiation therapy with many advantages. The reproducibility, linearity, isotropy, dose rate dependence of the MOSFET dosimeter were studied and its availability was verified. Consequently the results can be used to improve therapeutic planning procedure and minimize treatment errors in radiotherapy.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.108-115
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• 2011

This paper describes a new sensor system for mobile robot motion estimation using stereo infrared light sources and a camera. Visibility is being applied to robotic obstacle avoidance path planning and localization. Using simple visibility computation, the environment is partitioned into many visibility sectors. Based on the recognized edges, the sector a robot belongs to is identified and this greatly reduces the search area for localization. Geometric modeling of the vision system enables the estimation of the characteristic pixel position with respect to the robot movement. Finite difference analysis is used for incremental movement and the error sources are investigated. With two characteristic points in the image such as vertices, the robot position and orientation are successfully estimated.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.138.4-138
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• 2001

The purpose of this research is to build a quality-improved occupancy grid map for path-planning of an autonomous mobile robot(AMR) based on the measurements from a single ultrasonic sensor, which are acquired when the autonomous mobile robot explores unknown indoor environment. The AMR navigates in the unknown space by following the wall and gathers the range data using the ultrasonic sensor, from which the occupancy grid map is constructed by associating the range data with occupancy certainties. In order to increase the quality of the map we modify the Bayesian probability updating rule, reject non-systematic measurement errors and correct the predictable error of the AMR itself. These procedures are implemented and tested using an AMR, and primary results are presented in this paper.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.10a
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• pp.198-203
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• 1998

To acquire the high precision of profile for standard electrode of loss angle, it is needed ultraprecision machining technology like MEAP(Magnetic Electronic Abrasive Polishing) and the very high profile measurement technology which can measure a micro unit about the workpiece. So, in this paper, it was developed the measurement system of precision of profile using non-contactable sensor that was approximate sensor of capacitance type, because that is better than others in the electrical characteristics. And standard electrode of loss angle was machined by the MEAP machining technology. In this study, it was development of precision measurement system. This system could be used measure the workpiece of roundness and straightness much more precise and faster than general mechanical measurement system done before. And it could be helped to minimize machining time and planning by very fast and precise measurement about the workpiece.