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UAV Guidance Laws to Arrival at Desired Position and Time from Desired Direction
Seunghan Lim,Hyochoong Bang 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
Many guidance laws for UAVs focus on path following. And trajectory tracking problem is enough when it satisfies path and time constrains. One more constraint will be considered in this research, that is, approaching direction to a terminal position. Two methods will be introduced; they are based on Pythagorean-Hodograph curve, and the Lyapunov vector field, respectively. The first algorithm consists of two steps. The first step is trajectory-planning using PH curve, and the second step is tracking algorithm for that curve. The second algorithm is based on vector field including a variable parameter. Using this parameter, contraction vectors toward the origin are tuned, and a desired terminal approaching condition is achieved.
Sensor Fusion for Obstacle Detection and Its application to an Unmanned Ground Vehicle
Seunghan Yang,Hyung-Suk Lho,Bongsob Song 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
this paper presents a method for the detection of obstacles in the trajectory of unmanned ground vehicle (UGV). To detect obstacles, two different sensors are used, i.e., a vision sensor and a scanning lidar. While lidar measures the precise distance of the object, it cannot detect low objects due to its constant scanning height and angle. In contrast, vision sensor provides 2-D scenery information with relatively poor distance information. To compensate for the drawbacks of these two sensors, the sensor fusion method for obstacle detection of UGV is proposed. Finally the proposed method is validated experimentally.
Waypoint Planning Algorithm Using Cost Functions for Surveillance
Seunghan Lim,Hyochoong Bang 한국항공우주학회 2010 International Journal of Aeronautical and Space Sc Vol.11 No.2
This paper presents an algorithm for planning waypoints for the operation of a surveillance mission using cooperative unmanned aerial vehicles (UAVs) in a given map. This algorithm is rather simple and intuitive; therefore, this algorithm is easily applied to actual scenarios as well as easily handled by operators. It is assumed that UAVs do not possess complete information about targets; therefore, kinematics, intelligence, and so forth of the targets are not considered when the algorithm is in operation. This assumption is reasonable since the algorithm is solely focused on a surveillance mission. Various parameters are introduced to make the algorithm flexible and adjustable. They are related to various cost functions, which is the main idea of this algorithm. These cost functions consist of certainty of map, waypoints of co-worker UAVs, their own current positions, and a level of interest. Each cost function is formed by simple and intuitive equations, and features are handled using the aforementioned parameters.
Seunghan Lee(이승한),Kyungtae Kang(강경태),Dong Kun Noh(노동건) 한국컴퓨터정보학회 2017 韓國컴퓨터情報學會論文誌 Vol.22 No.2
Nowadays wine is increasingly enjoyed by a wider range of consumers, and wine certification and quality assessment are key elements in supporting the wine industry to develop new technologies for both wine making and selling processes. There have been many attempts to construct a more methodical approach to the assessment of wines, but most of them rely on objective decision rather than subjective judgement. In this paper, we propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. We used sequential forward selection and decision tree for this purpose. Experiments with the wine quality dataset from the UC Irvine Machine Learning Repository demonstrate the accuracies of 76.7% and 78.7% for red and white wines respectively.