• International Journal of Aeronautical and Space Sciences
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• v.12 no.3
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• pp.274-282
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• 2011

This paper is focused on dynamic modeling and control system design as well as vision based collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). Multi-rotor UAVs are defined as rotary-winged UAVs with multiple rotors. These multi-rotor UAVs can be utilized in various military situations such as surveillance and reconnaissance. They can also be used for obtaining visual information from steep terrains or disaster sites. In this paper, a quad-rotor model is introduced as well as its control system, which is designed based on a proportional-integral-derivative controller and vision-based collision avoidance control system. Additionally, in order for a UAV to navigate safely in areas such as buildings and offices with a number of obstacles, there must be a collision avoidance algorithm installed in the UAV's hardware, which should include the detection of obstacles, avoidance maneuvering, etc. In this paper, the optical flow method, one of the vision-based collision avoidance techniques, is introduced, and multi-rotor UAV's collision avoidance simulations are described in various virtual environments in order to demonstrate its avoidance performance.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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• pp.366-377
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• 2016

This paper presents a vision-based guidance method that allows a fixed-wing aircraft to orbit around a target at a given radius. The guidance method uses a simple formula that regulates a relative side-bearing angle estimated by a vision system. The global asymptotic stability of the associated guidance law is demonstrated, and a linear analysis is performed to facilitate the proper selection of the relevant control parameters. A flight experiment is presented to demonstrate the feasibility and performance of the proposed guidance method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.3
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• pp.230-237
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• 2004

Lane Sensing techniques based on vision sensors are regarded promising because they require little infrastructure on the highway except clear lane markers. However, they require more intelligent processing algorithms in vehicles to generate the previewed roadway from the vision images. In this paper, a lane sensing algorithm using vision sensors is developed to improve the sensing robustness. The parallel stereo-camera is utilized to regenerate the 3-dimensional road geometry. The lane geometry models are derived such that their parameters represent the road curvature, lateral offset and heading angle, respectively. The parameters of the lane geometry models are estimated by the Kalman filter and utilized to reconstruct the lane geometry in the global coordinate. The inverse perspective mapping from the image plane to the global coordinate considers roll and pitch motions of a vehicle so that the mapping error is minimized during acceleration, braking or steering. The proposed sensing system has been built and implemented on a 1/10-scale model car.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.196-196
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• 2021

상수관망은 많은 관을 통해 물의 수요가 있는 곳으로 물을 공급해주는 역할을 하는 사회기반 시설물이다. 상수관망 설계의 요점은 두 가지로 구분할 수 있다. 첫 번째 요점은 다양한 종류의 관배치로 인한 상수관망 설계안의 많은 경우의 수이다. 두 번째 요점은 상수관망 내 절점의 최저 요구수압 등의 제약조건이다. 두 가지 요점이 있는 상황에서 상수관망 설계비용의 최소화를 위한 상수관망 최적설계는 많은 계산이 요구된다. 많은 계산이 요구되기 때문에 상수관망 최적설계에 최적화 기법을 적용할 수 있다. 본 연구에서 상수관망 최적설계를 위해 적용된 최적화 기법은 Hybrid Rate(HR)를 개선한 Hybrid Vision Correction Algorithm(HVCA)이다. HVCA는 Vision Correction Algorithm(VCA)을 기반으로 추가적인 전역탐색을 실행하는 Centralized Global Search(CGS)의 적용 및 자가적응형 매개변수인 Hybrid Rate(HR)를 적용하여 사용성과 성능을 개량한 알고리즘이다. HVCA의 기존 HR은 선형적으로 증가하는 형태이다. 선형적으로 증가하는 HR로 인해 HVCA는 최적해 탐색과정에서 지역해에 빠지는 문제가 발생하였다. HVCA의 문제를 해결하기 위해 HR을 비선형적으로 증가하는 형태로 개량하였다. HR이 개량된 HVCA를 수자원공학 문제인 상수관망 최적설계 문제에 적용하여 결과를 비교하였다. 적용결과 HR이 개량된 HVCA가 기존의 HVCA보다 낮은 설계 비용을 나타내었다. 상수관망 최적설계 적용결과를 바탕으로 HR이 개량된 HVCA는 상수관망 최적설계 이외의 수자원공학 문제에도 적용가능할 것이다.

• Electronics and Telecommunications Trends
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• v.36 no.2
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• pp.56-64
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• 2021

Many computer vision algorithms are computationally expensive and require a lot of computing resources. Recently, owing to machine learning technology and high-performance embedded systems, vision processing applications, such as object detection, face recognition, and visual inspection, are widely used. However, on-devices need to use their resources to handle powerful vision works with low power consumption in heterogeneous environments. Consequently, global manufacturers are trying to lock many developers into their ecosystem, providing integrated low-power chips and dedicated vision libraries. Khronos Group-an international standard organization-has released the OpenVX standard for high-performance/low-power vision processing in heterogeneous on-device systems. This paper describes vision libraries for the embedded systems and presents the OpenVX standard along with related trends for on-device vision system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.8
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• pp.1666-1671
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• 2002

A lane sensing algorithm using vision sensors is developed based on lane geometry models. The parameters of the lane geometry models are estimated by a Kalman filter and utilized to reconstruct the lane geometry in the global coordinate. The inverse perspective mapping from image plane to global coordinate assumes earth to be flat, but roll and pitch motions of a vehicle are considered from the perspective of the lane sensing. The proposed algorithm shows robust lane sensing performance compared to the conventional algorithms.

• Electronics and Telecommunications Trends
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• v.39 no.4
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• pp.1-9
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• 2024

As Advanced Air Mobility (AAM) technologies evolve, ensuring accurate navigation and localization in complex urban airspaces has become crucial. Because the Global Navigation Satellite System (GNSS) is prone to vulnerabilities in urban flight environment, an alternative localization technique is required. This paper examines vision-based localization technologies to enhance GNSS-free navigation. In addition, we explore various geo-referencing studies that utilize pre-existing spatial databases to improve the accuracy of vision-based localization under GNSS-denied conditions. This paper discusses the various types of onboard vision camera sensors, vision-based localization, spatial information databases, feature extraction methods, and matching techniques that contribute to the development of a vision-based localization and geo-referencing system for AAM, ensuring safety and reliability in urban operations.

• Proceedings of the CALSEC Conference
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• 1998.10a
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• pp.283-286
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• 1998

CALS： “...to share integrated digital product data through a set of standards to achieve efficiencies in business...” This Conference: “The realization of global electronic commerce by restructuring” This Presentation: Give the participants a vision that will aid them in the achievement of the above goals.(omitted)

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.117-126
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• 2016

In this study, a new meta-heuristic optimization algorithm, Vision Correction Algorithm (VCA), designed according to the optical properties of glasses was developed. The VCA is a technique applying optometry and vision correction procedure to optimization algorithm through the process of myopic/hyperopic correction-brightness adjustment-compression enforcement-astigmatism adjustment. The proposed VCA unlike the conventional meta-heuristic algorithm is an automatically adjusting global/local search rate and global search direction based on accumulated optimization results. The proposed algorithm was applied to the representative optimization problem (mathematical and engineering problem) and results of the application are compared with that of the present algorithms.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.182-188
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• 2011

This paper describes a method of road tracking by using a vision and laser with extracting road boundary (road lane and curb) for navigation of intelligent transport robot in structured road environments. Road boundary information plays a major role in developing such intelligent robot. For global navigation, we use a global positioning system achieved by means of a global planner and local navigation accomplished with recognizing road lane and curb which is road boundary on the road and estimating the location of lane and curb from the current robot with EKF(Extended Kalman Filter) algorithm in the road assumed that it has prior information. The complete system has been tested on the electronic vehicles which is equipped with cameras, lasers, GPS. Experimental results are presented to demonstrate the effectiveness of the combined laser and vision system by our approach for detecting the curb of road and lane boundary detection.