• Title/Summary/Keyword: 충돌 감지

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Simulating Group Movement on a Roadmap-based Path (로드맵 기반 경로에서의 그룹 이동 시뮬레이션)

  • Yu, Kyeon-Ah;Cho, Su-Jin;Kim, Kyung-Hye
    • Journal of the Korea Society for Simulation
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    • v.20 no.4
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    • pp.105-114
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    • 2011
  • The roadmap-based planning is a path planning method which is used widely for a goal-directed movement in Robotics and has been applied to the world of computer animation such as computer games. However it is unnatural for computer characters to follow the path planned by the roadmap method as it is performed in Robotics. Flocking which is used for realistic and natural movements in computer animation enables character's movement by using a few simple rules without planning unlike the roadmap method. However it is impossible to achieve a goal-directed movement with flocking only because it does not keep states. In this paper we propose a simulation method which combines planning based on the road map with reactive actions for natural movements along the path planned. We define and implement steering behaviors for a leader which are needed to follow the trajectory naturally by analysing characteristics of roadmap-based paths and for the rest of members which follow the leader in various manners by detecting obstacles. The simulations are performed and demonstrated by using the implemented steering behaviors on every possible combination of roadmap-based path planning methods and models of configuration spaces. We also show that the detection of obstacle-collisions can be done effectively because paths are planned in the configuration space in which a moving object is reduced to a point.

Comparative Analysis of CNN Deep Learning Model Performance Based on Quantification Application for High-Speed Marine Object Classification (고속 해상 객체 분류를 위한 양자화 적용 기반 CNN 딥러닝 모델 성능 비교 분석)

  • Lee, Seong-Ju;Lee, Hyo-Chan;Song, Hyun-Hak;Jeon, Ho-Seok;Im, Tae-ho
    • Journal of Internet Computing and Services
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    • v.22 no.2
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    • pp.59-68
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    • 2021
  • As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

The Analysis of Bus Traffic Accident to Support Safe Driving for Bus Drivers (버스운전자 안전운행지원을 위한 교통사고 분석 연구)

  • BHIN, Miyoung;SON, Seulki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.18 no.1
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    • pp.14-26
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    • 2019
  • For bus drivers' safe driving, a policy that analyzes the causes of the drivers' traffic accidents and then assists their safe driving is required. Therefore, the Ministry of Land, Infrastructure and Transport set up its plan to gradually expand the equipping of commercial vehicles with FCWS (Forward Collision Warning System) and LDWS(Lane Departure Warning System), from the driver-supporting ADAS(Advanced Driver Assistance Systems). However, there is not much basic research on the analysis of bus drivers' traffic accidents in Korea. As such, the time is appropriate to research what is the most necessary ADAS for bus drivers going forward to prevent bus accidents. The purpose of this research is to analyze how serious the accidents were in the different bus routes and whether the accidents were repetitive, and to give recommendations on how to support ADAS for buses, as an improvement. A model of ordered logit was used to analyze how serious the accidents were and as a result, vehicle to pedestrian accidents which directly affected individuals were statistically significant in all of the models, and violations of regulations, such as speeding, traffic signal violation and violation of safeguards for passengers, were indicated in common in several models. Therefore, the pedestrian-sensor system and automatic emergency control device for pedestrian should be installed to reduce bus accidents directly affecting persons in the future, and education for drivers and ADAS are to be offered to reduce the violations of regulations.

Development of Fender Segmentation System for Port Structures using Vision Sensor and Deep Learning (비전센서 및 딥러닝을 이용한 항만구조물 방충설비 세분화 시스템 개발)

  • Min, Jiyoung;Yu, Byeongjun;Kim, Jonghyeok;Jeon, Haemin
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.2
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    • pp.28-36
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    • 2022
  • As port structures are exposed to various extreme external loads such as wind (typhoons), sea waves, or collision with ships; it is important to evaluate the structural safety periodically. To monitor the port structure, especially the rubber fender, a fender segmentation system using a vision sensor and deep learning method has been proposed in this study. For fender segmentation, a new deep learning network that improves the encoder-decoder framework with the receptive field block convolution module inspired by the eccentric function of the human visual system into the DenseNet format has been proposed. In order to train the network, various fender images such as BP, V, cell, cylindrical, and tire-types have been collected, and the images are augmented by applying four augmentation methods such as elastic distortion, horizontal flip, color jitter, and affine transforms. The proposed algorithm has been trained and verified with the collected various types of fender images, and the performance results showed that the system precisely segmented in real time with high IoU rate (84%) and F1 score (90%) in comparison with the conventional segmentation model, VGG16 with U-net. The trained network has been applied to the real images taken at one port in Republic of Korea, and found that the fenders are segmented with high accuracy even with a small dataset.

A LiDAR-based Visual Sensor System for Automatic Mooring of a Ship (선박 자동계류를 위한 LiDAR기반 시각센서 시스템 개발)

  • Kim, Jin-Man;Nam, Taek-Kun;Kim, Heon-Hui
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.6
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    • pp.1036-1043
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    • 2022
  • This paper discusses about the development of a visual sensor that can be installed in an automatic mooring device to detect the berthing condition of a vessel. Despite controlling the ship's speed and confirming its location to prevent accidents while berthing a vessel, ship collision occurs at the pier every year, causing great economic and environmental damage. Therefore, it is important to develop a visual system that can quickly obtain the information on the speed and location of the vessel to ensure safety of the berthing vessel. In this study, a visual sensor was developed to observe a ship through an image while berthing, and to properly check the ship's status according to the surrounding environment. To obtain the adequacy of the visual sensor to be developed, the sensor characteristics were analyzed in terms of information provided from the existing sensors, that is, detection range, real-timeness, accuracy, and precision. Based on these analysis data, we developed a 3D visual module that can acquire information on objects in real time by conducting conceptual designs of LiDAR (Light Detection And Ranging) type 3D visual system, driving mechanism, and position and force controller for motion tilting system. Finally, performance evaluation of the control system and scan speed test were executed, and the effectiveness of the developed system was confirmed through experiments.

Development of Greenhouse Environment Monitoring & Control System Based on Web and Smart Phone (웹과 스마트폰 기반의 온실 환경 제어 시스템 개발)

  • Kim, D.E.;Lee, W.Y.;Kang, D.H.;Kang, I.C.;Hong, S.J.;Woo, Y.H.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.18 no.1
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    • pp.101-112
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    • 2016
  • Monitoring and control of the greenhouse environment play a decisive role in greenhouse crop production processes. The network system for greenhouse control was developed by using recent technologies of networking and wireless communications. In this paper, a remote monitoring and control system for greenhouse using a smartphone and a computer with internet has been developed. The system provides real-time remote greenhouse integrated management service which collects greenhouse environment information and controls greenhouse facilities based on sensors and equipments network. Graphical user interface for an integrated management system was designed with bases on the HMI and the experimental results showed that a sensor data and device status were collected by integrated management in real-time. Because the sensor data and device status can be displayed on a web page, transmitted using the server program to remote computer and mobile smartphone at the same time. The monitored-data can be downloaded, analyzed and saved from server program in real-time via mobile phone or internet at a remote place. Performance test results of the greenhouse control system has confirmed that all work successfully in accordance with the operating conditions. And data collections and display conditions, event actions, crops and equipments monitoring showed reliable results.

Design of a Displacement and Velocity Measurement System Based on Environmental Characteristic Analysis of Laser Sensors for Automatic Mooring Devices (레이저 센서의 환경적 특성 분석에 기반한 선박 자동계류장치용 변위 및 속도 측정시스템 설계)

  • Jin-Man Kim;Heon-Hui Kim
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.980-991
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    • 2023
  • To prevent accidents near the quay caused by a ship, ports are generally designed and constructed through navigation and berthing safety assessment. However, unpredictable accidents such as ship collisions with the quay or personal accidents caused by ropes still occur sometimes during the ship berthing or mooring process. Automatic mooring systems, which are equipped with an attachment mechanism composed of robotic manipulators and vacuum pads, are designed for rapid and safe mooring of ships. This paper deals with a displacement and velocity measurement system for the automatic mooring device, which is essential for the position and speed control of the vacuum pads. To design a suitable system for an automatic mooring device, we first analyze the sensor's performance and outdoor environmental characteristics. Based on the analysis results, we describe the configuration and design methods of a displacement and velocity measurement system for application in outdoor environments. Additionally, several algorithms for detecting the sensor's state and estimating a ship's velocity are developed. The proposed method is verified through some experiments for displacement and speed measurement targeted at a moving object with constant speed.