• 자동차안전학회지
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• 제12권1호
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• pp.15-25
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• 2020

This paper presents a longitudinal control algorithm for ensuring takeover time of autonomous vehicle using V2V communication. In the autonomous driving of more than level 3, autonomous systems should control the vehicles by itself partially. However if the driver's intervention is required for functional safety, the driver should take over the control reasonably. Autonomous driving system has to be designed so that drivers can take over the control from autonomous vehicle reasonably for driving safety. In this study, control algorithm considering takeover time has been developed based on computation method of takeover time. Takeover time is analysed by conditions of longitudinal velocity of preceding vehicle in time-velocity plane. In addition, desired clearance is derived based on takeover time. The performance evaluation of the proposed algorithm in this study was conducted using 3D vehicle model with actual driving data in Matlab/Simulink environment. The results of the performance evaluation show that the longitudinal control algorithm can control while securing takeover time reasonably.

• 전기전자학회논문지
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• 제22권4호
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• pp.970-977
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• 2018

자율 주행 차량은 주변 환경의 정보를 수집하는 센서, 측정된 데이터를 판단하는 제어 모듈로 구성된 첨단 운전자 지원 시스템(ADAS)을 기반하고 있다. 최근에 자율주행 기술에 대한 관심이 증가함에 따라 ADAS 입문 개발자들 및 학습자들을 위한 손쉬운 개발프레임워크가 필요하다. 그러나, 기존 개발 및 검증 방식은 고성능 자동차 시뮬레이터를 기반하기 때문에 검증 방법의 복잡성 및 고비용 등의 단점이 있다. 또한, 대부분의 방식은 시뮬레이터로부터 ADAS에서 필요로 하는 센싱 데이터를 직접 제공하지 않으므로 검증 신뢰성의 한계가 있다. 본 논문에서는 기존 방식들의 문제점들을 극복하는 3D 자동차 시뮬레이터를 활용한 상호작용형 ADAS 개발 및 검증 프레임워크를 제시한다. 영상인지 기반의 인공지능을 적용한 ADAS를 3D 자동차 시뮬레이터에서의 가상센서로 구현하고, 실제 시나리오에 자율주행 검증을 진행하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권1호
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• pp.33-40
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• 2000

In this paper, an integrated method for the path planning and motion control of wheeled mobile robots using a hybrid system model and control is presented. The hybrid model including the continuous dynamics and discrete dynamics with the continuous and discrete state vector is derived for a two wheel driven mobile robot. The architecture of the hybrid control system for real time path planning and following is designed which has the 3-layered hierarchical structure : the discrete event system using the digital automata as the higher process, the continuous state system for the wheel velocity controls as the lower process, and the interface system as the interaction process between the continuous system as the low level and the discrete event system as the high level. The reference motion commands for autonomous navigation are generated by the abstracted motion in the discrete event system. The motion control tasks including the feasible path planning and autonomous motion control with various initial conditions are investigated as the applications by the simulation studies.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권3호
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• pp.213-218
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• 2009

This paper describes a classical algorithm carrying out dynamic 3D obstacle recognition for autonomous underwater vehicles (AUVs), Support Vector Machines (SVMs). SVM is an efficient algorithm that was developed for recognizing 3D object in recent years. A recognition system is designed using Support Vector Machines for applying the capabilities on appearance-based 3D obstacle recognition. All of the test data are taken from OpenGL Simulation. The OpenGL which draws dynamic obstacles environment is used to carry out the experiment for the situation of three-dimension. In order to verify the performance of proposed SVMs, it compares with Back-Propagation algorithm through OpenGL simulation in view of the obstacle recognition accuracy and the time efficiency.

• 한국통신학회논문지
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• 제41권11호
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• pp.1557-1565
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• 2016

인간이 개입하지 않는 UAV 시스템은 다양한 행동을 자율적으로 수행하여 임무를 달성해야하는 어려움이 있다. 그러나 인간이 개입하지 않는 환경에서의 실제 실험은 많은 위험과 비용이 발생한다. 따라서 실제 환경 실험에 앞서 시뮬레이션 실험을 통한 검증이 필요함은 자명하다. 본 논문에서는 에이전트 기반 자율 UAV의 실험을 위한 3차원 가상환경과 이산사건 시뮬레이션 환경 구축하고 연동한 시스템을 제안한다. 재난 상황에서의 UAV 3기를 이용한 구조임무 시뮬레이션을 통해 그 유효성을 검증 하였다.

• 로봇학회논문지
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• 제13권3호
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• pp.190-197
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• 2018

Geomagnetic field signals have potential for use in underwater navigation and geophysical surveys. To map underwater geomagnetic fields, we propose a method that exploits an autonomous surface vehicle. In our system, a magnetometer is rigidly attached to the vehicle and not towed by a cable, minimizing the system's size and complexity but requiring a dedicated calibration procedure due to magnetic distortion caused by the vehicle. Conventional 2D methods can be employed for the calibration by assuming the horizontal movement of the magnetometer, whereas the proposed 3D approach can correct for horizontal misalignment of the sensor. Our method does not require a supporting crane system to rotate the vehicle, and calibrates and maps simultaneously by exploiting data obtained from field operation. The proposed method has been verified experimentally in inland waters, generating a magnetic field map of the test area that is of much higher resolution than the public magnetic field data.

• 로봇학회논문지
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• 제17권3호
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• pp.245-254
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• 2022

Sensor dataset for autonomous driving is one of the essential components as the deep learning approaches are widely used. However, most driving datasets are focused on typical environments such as sunny or cloudy. In addition, most datasets deal with color images and lidar. In this paper, we propose a driving dataset with multi-spectral images and lidar in adverse weather conditions such as snowy, rainy, smoky, and dusty. The proposed data acquisition system has 4 types of cameras (color, near-infrared, shortwave, thermal), 1 lidar, 2 radars, and a navigation sensor. Our dataset is the first dataset that handles multi-spectral cameras in adverse weather conditions. The Proposed dataset is annotated as 2D semantic labels, 3D semantic labels, and 2D/3D bounding boxes. Many tasks are available on our dataset, for example, object detection and driveable region detection. We also present some experimental results on the adverse weather dataset.

• 로봇학회논문지
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• 제9권3호
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• pp.154-159
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• 2014

The Global Positioning System (GPS) is widely used to aid the navigation of aerial vehicles. However, the GPS cannot be used indoors, so alternative navigation methods are needed to be developed for micro aerial vehicles (MAVs) flying in GPS-denied environments. In this paper, a real-time three-dimensional (3-D) indoor navigation system and closed-loop control of a quad-rotor aerial vehicle equipped with an inertial measurement unit (IMU) and a low-cost light detection and ranging (LIDAR) is presented. In order to estimate the pose of the vehicle equipped with the two-dimensional LIDAR, an octree-based grid map and Monte-Carlo Localization (MCL) are adopted. The navigation results using the MCL are then evaluated by making a comparison with a motion capture system. Finally, the results are used for closed-loop control in order to validate its positioning accuracy during procedures for stable hovering and waypoint-following.

• Journal of Veterinary Science
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• 제24권1호
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• pp.4.1-4.16
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• 2023

Background: In vitro culture of preantral follicles is a promising technology for fertility preservation. Objectives: This study aims to investigate an optimized three-dimensional (3D) fetal bovine serum (FBS)-free preantral follicle culture system having a simple and easy operation. Methods: The isolated follicles from mouse ovaries were randomly divided in an ultra-low attachment 96-well plates supplement with FBS or bovine serum albumin (BSA) culture or encapsulated with an alginate supplement with FBS or BSA culture. Meanwhile, estradiol (E₂) concentration was assessed through enzyme-linked immunosorbent assay of culture supernatants. The diameter of follicular growth was measured, and the lumen of the follicle was photographed. Spindle microtubules of oocytes were detected via immunofluorescence. The ability of oocytes to fertilize was assessed using in vitro fertilization. Results: The diameters were larger for the growing secondary follicles cultured in ultra-low attachment 96-well plates than in the alginate gel on days 6, 8, and 10 (p < 0.05). Meanwhile, the E2 concentration in the BSA-supplemented medium was significantly higher in the alginate gel than in the other three groups on days 6 and 8 (p < 0.05), and the oocytes in the FBS-free system could complete meiosis and fertilization in vitro. Conclusions: The present study furnishes insights into the mature oocytes obtained from the 3D culture of the preantral follicle by using ultra-low attachment 96-well plate with an FBS-free system in vitro and supports the clinical practices to achieve competent, mature oocytes for in vitro fertilization.

• 로봇학회논문지
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• 제14권2호
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• pp.122-130
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• 2019

Collecting a rich but meaningful training data plays a key role in machine learning and deep learning researches for a self-driving vehicle. This paper introduces a detailed overview of existing open-source simulators which could be used for training self-driving vehicles. After reviewing the simulators, we propose a new effective approach to make a synthetic autonomous vehicle simulation platform suitable for learning and training artificial intelligence algorithms. Specially, we develop a synthetic simulator with various realistic situations and weather conditions which make the autonomous shuttle to learn more realistic situations and handle some unexpected events. The virtual environment is the mimics of the activity of a genuine shuttle vehicle on a physical world. Instead of doing the whole experiment of training in the real physical world, scenarios in 3D virtual worlds are made to calculate the parameters and training the model. From the simulator, the user can obtain data for the various situation and utilize it for the training purpose. Flexible options are available to choose sensors, monitor the output and implement any autonomous driving algorithm. Finally, we verify the effectiveness of the developed simulator by implementing an end-to-end CNN algorithm for training a self-driving shuttle.