• 한국항공우주학회지
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• 제50권9호
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• pp.639-646
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• 2022

본 논문은 사전에 알려지지 않은 환경에서 깊이지도를 이용하여 정보를 획득하고, 이를 기반으로 쿼드로터의 착륙 선택 알고리즘 성능을 분석한다. 무인항공기의 유도 및 제어시스템은 궤적 계획 유도시스템과 위치 및 자세 제어기로 구성된다. 아래를 향하는 짐벌 시스템에 부착된 스테레오 비전 센서가 획득한 깊이 정보를 이용하여 착륙 지점을 선정한다. 평탄도 정보는 사전 정의된 깊이지도 영역의 최대 깊이 차이 및 UAV와의 거리를 고려하여 산출한다. 본 논문에서는 3가지 착륙 방법을 제안하며 다양한 성능지수들을 활용하여 성능을 비교한다. 성능지수로는 UAV 이동 거리, 지도 정확도, 장애물 대응 시간 등을 고려한다.

• 한국정밀공학회지
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• 제20권12호
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• pp.73-79
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• 2003

Recently, the tole-robot operations to an unstructured environment have been widely researched. The human's interaction with the tole-robot system can be used to improve robot operation and performance for an unknown environment. The exact modeling based on real environment is fundamental and important process for this interaction. In this paper, we propose an extrinsic parameter calibration and data augmentation method that only uses a circular jig in the hand-eye laser virtual environment. Compared to other methods, easier estimation and overlay can be done by this algorithm. Experimental results using synthetic graphic demonstrate the usefulness of the proposed algorithm.

• 로봇학회논문지
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• 제4권4호
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• pp.305-311
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• 2009

FastSLAM is a factored solution to SLAM problem using a Rao-Blackwellized particle filter. In this paper, we propose a practical FastSLAM implementation method using an infrared camera for indoor environments. The infrared camera is equipped on a Pioneer3 robot and looks upward direction to the ceiling which has infrared tags with the same height. The infrared tags are detected with theinfrared camera as measurements, and the Nearest Neighbor method is used to solve the unknown data association problem. The global map is successfully built and the robot pose is predicted in real time by the FastSLAM2.0 algorithm. The experiment result shows the accuracy and robustness of the proposed method in practical indoor environment.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.378-380
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• 2009

For the autonomous movement, the optimal pat]1 planning connecting between current and target positions is essential, and the optimal path of mobile robot means obstacle-free and the shortest length path to a target position. Many actual mobile robots should move without any information of surrounded obstacles. This paper suggests a new method of obstacle avoidment which is suitable in unknown environments. This method of obstacle avoidance is designed with a distributed fuzzy control system, and imitates a Potential Field method. A simulation confirms the performance and correctness of the obstacle avoidance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.1234-1239
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• 1990

In this paper, we propose a new type of decentralized learning automata for the control finite state Markov chains with unknown transition probabilities and rewards. In our scheme a .betha.-type learning automaton is associated with each state in which two or more actions(desisions) are available. In this decentralized learning automata system, each learning automaton operates, requiring only local information, to improve its performance under local environment. From simulation results, it is shown that the decentralized learning automata will converge to the optimal policy that produces the most highly total expected reward with discounting in all initiall states.

• 한국정밀공학회지
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• 제25권7호
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• pp.72-78
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• 2008

The line-of-sight(LOS) stabilization system is a precision electro-mechanical gimbals assembly for suppressing vibration due to its environment and tracking the target in a desired direction. This paper describes the design of gimbals system to reject the disturbance and to improve stabilization. The controller consists of a DSP with transducer and actuator interfaces. Unknown parameters of the gimbals are estimated by the signal compression method. The cross-correlation coefficient between the impulse response from the assumed model and the one from model of the gimbals is used to obtain the better estimation. The quasi-impulse response through linear element included in the gimbals could be obtained by the signal compression method. The unknown parameter of the linear element could be estimated as comparing the bode plots for impulse response from gimbals with them from model's response.

• ETRI Journal
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• 제33권2호
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• pp.283-286
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• 2011

Path loss plays fundamental roles in system design, spectrum management, and performance evaluation. The traditional path loss model has a slight inconvenience; it depends on the unknown distance. In this letter, we explore the probability distribution function (PDF) of path loss in an indoor office environment by randomizing out the distance variable. It is shown that the resulting PDF is not Gaussian-like but is skewed to the right, and both the PDF and the moments are related to the size of the office instead of the unknown distance. To be specific, we incorporate the IEEE 802.15.4a channel parameters into our model and tabulate the cumulative distribution function with respect to different room sizes. Through a simple example, we show how our model helps a cognitive spectrum user to infer path loss information of primary users without necessarily knowing their transmitter-receiver distance.

• 대한전기학회논문지
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• 제40권2호
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• pp.200-206
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• 1991

In this paper, an output feedback is used to reduce the effect of the vibration in the control of a flexible one-link robot arm. A PD control method with a time varying gain is proposed to improve the performance of the system in tip deflection and settling time for the step reference input. By making the change of feedback gain smoothly, th input torque can be made smooth. When there is a payload with unknown mass, an interpolation method which uses the inrehgrated value of the transient response of the hub angle is proposed for the estimation of teh payload mass. This method can be used when the reference input is known and we can get highly accurate estimate for the unknown payload. It is also demonstrated that flexible one-link arm can be controlled prettry accurately by an output feedback in a noisy environment without knowing the mass of the payload.

• ETRI Journal
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• 제43권4호
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• pp.580-593
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• 2021

When operating in confined spaces or near obstacles, collision-free path planning is an essential requirement for autonomous exploration in unknown environments. This study presents an autonomous exploration technique using a carefully designed collision-free local planner. Using LiDAR range measurements, a local end-point selection method is designed, and the path is generated from the current position to the selected end-point. The generated path showed the consistent collision-free path in real-time by adopting the Euclidean signed distance field-based grid-search method. The results consistently demonstrated the safety and reliability of the proposed path-planning method. Real-world experiments are conducted in three different mines, demonstrating successful autonomous exploration flights in environment with various structural conditions. The results showed the high capability of the proposed flight autonomy framework for lightweight aerial robot systems. In addition, our drone performed an autonomous mission in the tunnel circuit competition (Phase 1) of the DARPA Subterranean Challenge.