• International Journal of Aeronautical and Space Sciences
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• 제14권3호
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• pp.272-281
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• 2013

Traffic Collision Avoidance System (TCAS) is designed to enhance safety in aircraft operations, by reducing the incidences of mid-air collision between aircraft. The current version of TCAS provides only vertical resolution advisory to the pilots, if an aircraft's collision with another is predicted to be imminent, while efforts to include horizontal resolution advisory have been made, as well. This paper introduces a collision resolution algorithm, which includes both vertical and horizontal avoidance maneuvers of aircraft. Also, the paper compares between the performance of the proposed algorithm and that of algorithms with only vertical or horizontal avoidance maneuver of aircraft.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.417-422
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• 1993

Robots working in the multiple robot system can perform the variety of tasks compared to the single robot system, while they are subject to the various tight constraints such as the precise coordination and the mutual collision avoidance during the task execution. In this paper, we provide an algorithm and graphical verification for collision avoidance between two robots working together. The algorithm calculates the minimum time delay for collision avoidance and the graphical verification is performed through the 3-D graphic simulator.

• 항공우주시스템공학회지
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• 제12권5호
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• pp.48-53
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• 2018

본 논문에서는 RTOS과 항공기의 3차원 충돌회피 알고리즘을 세 개의 MCU에 적용하여 각 MCU의 성능을 비교하였다. MCU는 많이 사용되는 Microchip Technology사의 ATmega2560과 STM사의 ARM Cortex-M3, ARM Cortex-M4를 선정하였으며, RTOS는 공개되어 있는 FreeRTOS 를 사용하였다. 성능을 확인하기 위해 적용된 3차원 충돌회피 알고리즘은 수직회피와 수평회피를 통합한 알고리즘이며 C++로 구현하였다. MCU의 성능은 각 MCU의 사용 메모리와 계산 시간을 측정하여 비교하였다. 비교 결과 세 MCU 중, 계산 시간은 ARM Cortex-M4가 빨랐으며, ATmega2560이 적은 메모리를 사용하였다.

• International Journal of Aeronautical and Space Sciences
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• 제9권2호
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• pp.1-8
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• 2008

This paper presents a real-time algorithm for collision detection, collision avoidance and guidance. Three-dimensional point-mass aircraft models are used. For collision detection, conflict probability is calculated by using the Monte-Carlo Simulation. Time at the closest point of approach(CPA) and distance at CPA are needed to determine the collision probability, being compared to certain threshold values. For collision avoidance, one of possible maneuver options is chosen to minimize the collision probability. For guidance to a designated way-point, proportional navigation guidance law is used. Two scenarios on encounter situation are studied to demonstrate the performance of proposed algorithm.

• 한국항공우주학회지
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• 제36권10호
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• pp.996-1002
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• 2008

본 논문에서는 3차원 일대일 충돌 감지, 충돌 회피 및 경로점 유도를 위한 알고리듬에 대해 다룬다. 항공기는 질점 모델로 가정하였다. 충돌 감지는 최근접점까지 남은 시간과 그 때의 거리를 기준 값과 비교하여 수행하였다. 충돌 회피는 최적 제어 이론을 이용하여 최종 시간에서의 상대 거리를 최대화하는 가속도 입력을 계산하여 수행하였다. 경로점 유도는 잘 알려진 비례항법유도를 적용하였다. 제안된 알고리듬의 성능은 두 개의 시나리오를 통하여 검증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1939-1943
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• 1991

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the shortest collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal of this paper, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy[3] and a traveling salesman problem strategy(TSP)[23]. The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Neural Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is proposed to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm[21] and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm[5].

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.79-84
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• 1992

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the optimal collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy and a traveling salesman problem strategy (TSP). The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Hopfield Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is used to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm.

• 항공우주시스템공학회지
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• 제15권1호
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• pp.102-110
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• 2021

최근 멀티콥터는 비행 안정성 향상을 위해 다양한 충돌회피 센서를 탑재하고 있다. LiDAR를 이용해 3차원 위치를 인식하거나 다수 카메라와 실시간 SLAM 기술을 이용해 장애물과의 상대 위치를 계산하기도 한다. 또한 소형 프로세스와 카메라로 구성된 3D 깊이 센서를 사용하기도 한다. 본 연구에서는 충돌회피 소프트웨어 기술 개발을 위한 플랫폼으로써 상용 부품을 활용해 실내 비행이 가능한 소형 충돌회피 멀티콥터 시스템을 개발하였다. 멀티콥터 시스템은 LiDAR, RealSense, GPU 보드를 탑재하였고, 비행시험을 통해 YOLO 알고리즘 기반의 사물 인식 및 충돌회피 기능을 검증하였다. 이 논문에서는 시스템 설계/제작 및 탑재 장비 선정과정, 비행시험 결과에 관해 기술하였다.

• 한국자동차공학회논문집
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• 제21권2호
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• pp.81-86
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• 2013

This paper presents the lane change system for collision avoidance. The proposed algorithm for the collision avoidance consists of path generation and path following. Using a calculated TTC (Time to Collision), partial braking is operated and collision avoidance path is generated considering relative distance, velocity and acceleration. Based on the collision avoidance path, desired yaw angle and yaw rate are calculated for the automated path following. The lateral controller is designed by a Lyapunov function approach using 3 D.O.F vehicle model and vehicle parameters. The required steering angle is determined from wheel velocity, longitudinal and lateral velocity in order to follow the desired yaw angle and yaw rate. This system is developed MATLAB/Simulink and its performance is evaluated using the commercial software CarSim.

• 드라이브 ㆍ 컨트롤
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• 제19권4호
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• pp.62-69
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• 2022

Construction machinery is exposed to accidents such as collisions, narrowness, and overturns during operation. In particular, mobile crane is operated only with the driver's vision and limited information of the assistant worker. Thus, there is a high risk of an accident. Recently, some collision avoidance device using sensors such as cameras and LiDAR have been applied. However, they are still insufficient to prevent collisions in the omnidirectional 3D space. In this study, a rotating LiDAR device was developed and applied to a 250-ton crane to obtain a full-space point cloud. An algorithm that could provide distance information and safety status to the driver was developed. Also, deep-learning segmentation algorithm was used to classify human-worker. The developed device could recognize obstacles within 100m of a 360-degree range. In the experiment, a safety distance was calculated with an error of 10.3cm at 30m to give the operator an accurate distance and collision alarm.