• Title/Summary/Keyword: Image Navigation

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Mobile Robot Control with Image Tracking (영상 추적을 이용한 이동 로봇 제어)

  • Hong, Seon-Hack
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.42 no.4
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    • pp.33-40
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    • 2005
  • This paper represents the stable path recognition by the ultrasonic sensor which gathers navigation environments and the monocular image sensor which generates the self localization information of mobile robot. The proposed ultrasonic sensor and vision camera system recognizes the target and extracts parameters for generating the world map and self localization. Therefore, this paper has developed an indoor mobile robot and has stably demonstrated in a corridor environment.

Design of StraaS(streaming as a service) based on Cloud Computing (클라우드 컴퓨팅 기반 스트리밍 서비스(StraaS)의 설계)

  • Cha, Byung-Rae;Sim, Su-Jeong;Kim, Yong-Il
    • Journal of Advanced Navigation Technology
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    • v.16 no.2
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    • pp.330-339
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    • 2012
  • In this paper, we define and design the Streaming as a Service (StraaS) to support streaming service based on cloud computing. And we describe the various function and security to StraaS service. Specially, we introduce KS-MMA(Key-generation System for Multilateral Matching Authentication) and SIES(Searchable Image Encryption System) as security function for streaming service and cloud computing.

Fuzzy Navigation Control of Mobile Robot equipped with CCD Camera (퍼지제어를 이용한 카메라가 장착된 이동로봇의 경로제어)

  • Cho, Jung-Tae;Lee, Seok-Won;Nam, Boo-Hee
    • Journal of Industrial Technology
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    • v.20 no.B
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    • pp.195-200
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    • 2000
  • This paper describes the path planning method in an unknown environment for an autonomous mobile robot equipped with CCD(Charge-Coupled Device) camera. The mobile robot moves along the guideline. The CCD camera is used for the detection of the existence of a guideline. The wavelet transform is used to find the edge of guideline. It is possible for us to do image processing more easily and rapidly by using wavelet transform. We make a fuzzy control rule using image data as an input then determined the position and the navigation of the mobile robot. The center value of guideline is the input of fuzzy logic controller and the steering angle of the mobile robot is the fuzzy controller output. Some actual experiments show that the mobile robot effectively moves to target position by means of the applied fuzzy control.

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A Study on the Construction of Omnidirecional Vision System for the Mobile Robot's the Autonomous Navigation (이동로봇의 자율주행을 위한 전방향 비젼 시스템의 구현에 관한 연구)

  • 고민수;한영환;이응혁;홍승홍
    • Proceedings of the IEEK Conference
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    • 2001.06e
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    • pp.17-20
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    • 2001
  • This study is regarding the autonomous navigation of the mobile robot which operates through a sensor, the Omnnidirectional Vision System which makes it possible to retrieve the real-time movements of the objects and the walls accessing the robot from all directions and to shorten the processing time. After attempting to extend the field of view by using the reflection system and then learning the point of all directions of 2$\pi$ from the robot at the distance, robot recognizes three-dimensional world through the simple image process, the transform procedure and constant monitoring of the angle and distance from the peripheral obstacles. This study consists of 3 parts: Part 1 regards the process of designing Omnnidirectional Vision System and part 2 the image process, and part 3 estimates the implementation system through the comparative study process and three-dimensional measurements.

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A Study on the Category Classification of Multispectral Remote Sensing Images Using a New Image Enhancement Method (새로운 영상 향상법을 이용한 인공위성 영상의 카테고리 분류)

  • 조용욱;안명석;조석제
    • Journal of the Korean Institute of Navigation
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    • v.24 no.4
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    • pp.227-234
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    • 2000
  • In general, neural networks are widely used for the category classification of multispectral images. Since the input multispectral images into neural networks we, however, low contrast images, neural networks converge very slowly and are of bad performance. To overcome this problem, we propose a new image enhancement method which consists of smoothing process, finding the main valley and enhancement process. In addition the enhanced images by the proposed method are used as the input of neural networks for the category classification. When the new category classification method is applied to multispectral LANDSAT TM images, we verified that the neural networks converge very lastly and that the overall category classification performance is improved.

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Performance Analysis of TH-BPPM and TH-BPAM UWB System and the Applications in Data and Image Transmission

  • Sung, Tae-Kyung
    • Journal of Navigation and Port Research
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    • v.31 no.2
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    • pp.159-163
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    • 2007
  • In this paper, we mainly analyze the performance of two ultra wideband communication systems, the classical Time Hopping Binary Pulse Position Modulation (TH-BPPM) UWB system and the Time Hopping Bipolar Pulse Amplitude Modulation (TH-BPAM) UWB system. The performance of TH-BPPM and TH-BPAM is analyzed in detail under an ideal AWGN channel and a correlation receiver. We use the power spectral density function to get the expression of BER of these two UWB systems. It yields simple and exact formulas relating the performance to the system parameters. The analysis shows that TH-BPPM suffers performance degradation with respect to TH-BPAM. Furthermore, we give the computer simulation of both data and image transmission and our simulation results also prove our theoretical analysis.

Visual Positioning System based on Voxel Labeling using Object Simultaneous Localization And Mapping

  • Jung, Tae-Won;Kim, In-Seon;Jung, Kye-Dong
    • International Journal of Advanced Culture Technology
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    • v.9 no.4
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    • pp.302-306
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    • 2021
  • Indoor localization is one of the basic elements of Location-Based Service, such as indoor navigation, location-based precision marketing, spatial recognition of robotics, augmented reality, and mixed reality. We propose a Voxel Labeling-based visual positioning system using object simultaneous localization and mapping (SLAM). Our method is a method of determining a location through single image 3D cuboid object detection and object SLAM for indoor navigation, then mapping to create an indoor map, addressing it with voxels, and matching with a defined space. First, high-quality cuboids are created from sampling 2D bounding boxes and vanishing points for single image object detection. And after jointly optimizing the poses of cameras, objects, and points, it is a Visual Positioning System (VPS) through matching with the pose information of the object in the voxel database. Our method provided the spatial information needed to the user with improved location accuracy and direction estimation.

Analysis of Surface Current Measurement Based on X-band Radar Image (X-밴드 레이더 이미지 기반 표층해류 계측 분석)

  • Na-Yun Kang;Yu-Kyung Lee;Young-Jun Yang
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.323-324
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    • 2022
  • This paper explains the comparison results of surface current measurement using X-band Radar image through analysis. Measurements were carried out from February 2022 using the X-band Radar for marin ships installed at Sokcho Beach. Based on the Korea Hydrographic and Oceanographic Agency ocean observation buoys, the accuracy of surface current(current speed) measurement was verified through comparison and analysis of measurement data.

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Forest Fire Detection System using Drone Streaming Images (드론 스트리밍 영상 이미지 분석을 통한 실시간 산불 탐지 시스템)

  • Yoosin Kim
    • Journal of Advanced Navigation Technology
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    • v.27 no.5
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    • pp.685-689
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    • 2023
  • The proposed system in the study aims to detect forest fires in real-time stream data received from the drone-camera. Recently, the number of wildfires has been increasing, and also the large scaled wildfires are frequent more and more. In order to prevent forest fire damage, many experiments using the drone camera and vision analysis are actively conducted, however there were many challenges, such as network speed, pre-processing, and model performance, to detect forest fires from real-time streaming data of the flying drone. Therefore, this study applied image data processing works to capture five good image frames for vision analysis from whole streaming data and then developed the object detection model based on YOLO_v2. As the result, the classification model performance of forest fire images reached upto 93% of accuracy, and the field test for the model verification detected the forest fire with about 70% accuracy.

Mobile Robot Navigation in an Indoor Environment

  • Choi, Sung-Yug;Lee, Jang-Myung
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1456-1459
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    • 2005
  • To compensate the drawbacks, a new localization method that estimates the global position of the mobile robot by using a camera set on ceiling in the corridor is proposed. This scheme is not a relative localization, which decreases the position error through algorithms with noisy sensor data. The effectiveness of the proposed localization scheme is demonstrated by the experiments.

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