• Title/Summary/Keyword: Map based navigation

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Simulation of Mobile Robot Navigation based on Multi-Sensor Data Fusion by Probabilistic Model

  • Jin, Tae-seok
    • Journal of the Korean Society of Industry Convergence
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    • v.21 no.4
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    • pp.167-174
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    • 2018
  • Presently, the exploration of an unknown environment is an important task for the development of mobile robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, In mobile robotics, multi-sensor data fusion(MSDF) became useful method for navigation and collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within indoor environments. Simulation results with a mobile robot will demonstrate the effectiveness of the discussed methods.

3-D Indoor Navigation and Autonomous Flight of a Micro Aerial Vehicle using a Low-cost LIDAR (저가형 LIDAR를 장착한 소형 무인항공기의 3차원 실내 항법 및 자동비행)

  • Huh, Sungsik;Cho, Sungwook;Shim, David Hyunchul
    • The Journal of Korea Robotics Society
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    • v.9 no.3
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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.

PC controlled Autonomous Navigation System for GPS Guided Field Robot (GPS를 이용한 필드로봇의 PC기반 자율항법 제어 시스템)

  • Han, Jae-Won;Park, Jae-Ho;Hong, Sung-Kyung;Ryuh, Young-Sun
    • Journal of Biosystems Engineering
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    • v.34 no.4
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    • pp.278-285
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    • 2009
  • Navigation system is applied in variety of fields including the simple location positioning, autopilot navigation of unmanned robot tractor, autonomous guidance systems for agricultural vehicles, construction of large field works that require high precision and map making process. Particularly utilization of GPS (Global Positioning System) is very common in the present navigation system. This study introduces a navigation system for autonomous field robot that travels to the pre-input path using GPS information. Performance of the GPS- based navigation is highly depended on its receiving rate because GPS receivers do not acquire any navigation information in the period between the refresh intervals. So this study presents an algorithm that improves an accuracy of the navigation by estimation the positional information during the blind period of a low rate GPS receiver. In fact the algorithm calculated the robot's heading in a 50 Hz rate, so the blind period of an 1 Hz GPS receiver is extensively covered. Consequently implementation of the algorithm to the GPS based navigation showed an improvement in guidance accuracy. The conventional field robot directly carried an expensive control computer and sensors onboard, therefore the miniaturization and weight reduction of the robot was limited. In this paper, the field robot carried only communication equipments such as GPS module, normal RC receiver, and bluetooth modem. This enabled the field robot to be built in an economic cost and miniature size.

Design and Implementation of Mind map program using Open API (오픈 API를 이용한 마인드맵 프로그램의 설계 및 구현)

  • Lee, Seon-Ung;Lee, Hye-Rim;Kim, Yoo-Doo;Moon, Il-Young
    • Journal of Advanced Navigation Technology
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    • v.13 no.1
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    • pp.134-141
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    • 2009
  • In this paper, it is proposed a mind map program using open API to provide mashup function. Web paradigm is changing to Web 2.0. So mashup using open API is much applied. Mashup is good method for not only web service, but making new ideas or informations. It is mind map that was made systematical like this method. In this paper, a mind map application based on mobile that provides mashup function implemented for modern people that mostly process their business during movement.

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Annual Prediction of Multi-GNSS Navigation Performance in Urban Canyon (도심지역에서의 연도별 다중위성항법 통합성능 예측)

  • Seok, Hyo Jeong;Park, Byung Woon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.1
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    • pp.71-78
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    • 2016
  • In the paper, we predict the number of multi-GNSS satellites and visible satellites with the navigation satellite launch plans and their nominal orbit parameters. Based on the methodology, the multi-GNSS navigation performance and DOP (Dilution of Precision) variation from 2015 to 2020 were forecasted by the Matlab simulation. To calculate the position using the multi-GNSS constellation, we determined the time-offset between the two different systems. Two different algorithms were considered for the sake of time-offset determination; that of each was applied to system level and user side. Also, the results from two algorithms were compared for evaluating each performance. For the reality, we applied the 3D map information to the simulation, which is expected to contribute for predicting the future navigation performance in urban canyon.

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.

Multi-Object Goal Visual Navigation Based on Multimodal Context Fusion (멀티모달 맥락정보 융합에 기초한 다중 물체 목표 시각적 탐색 이동)

  • Jeong Hyun Choi;In Cheol Kim
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.9
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    • pp.407-418
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    • 2023
  • The Multi-Object Goal Visual Navigation(MultiOn) is a visual navigation task in which an agent must visit to multiple object goals in an unknown indoor environment in a given order. Existing models for the MultiOn task suffer from the limitation that they cannot utilize an integrated view of multimodal context because use only a unimodal context map. To overcome this limitation, in this paper, we propose a novel deep neural network-based agent model for MultiOn task. The proposed model, MCFMO, uses a multimodal context map, containing visual appearance features, semantic features of environmental objects, and goal object features. Moreover, the proposed model effectively fuses these three heterogeneous features into a global multimodal context map by using a point-wise convolutional neural network module. Lastly, the proposed model adopts an auxiliary task learning module to predict the observation status, goal direction and the goal distance, which can guide to learn the navigational policy efficiently. Conducting various quantitative and qualitative experiments using the Habitat-Matterport3D simulation environment and scene dataset, we demonstrate the superiority of the proposed model.

Performance Enhancing Technique for Terrain Referenced Navigation Systems using Terrain Roughness and Information Gain Based on Information Theory (정보이론기반 지형 험준도 및 정보이득을 이용한 지형대조항법 성능 향상 기법)

  • Nam, Seongho
    • Journal of the Korea Institute of Military Science and Technology
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    • v.20 no.3
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    • pp.307-314
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    • 2017
  • Terrain referenced navigation(TRN) system is an attractive method for obtaining position based on terrain measurements and a terrain map. We focus on TRN systems based on the point mass filter(PMF) which is one of the recursive Bayesian method. In this paper, we propose two kinds of performance index for Bayesian filter. The proposed indices are based on entropy and mutual information from information theory. The first index measures roughness of terrain based on entropy of likelihood. The second index named by information gain, which is the mutual information between priori and posteriori distribution, is a quantity of information gained by updating measurement at each step. The proposed two indices are used to determine whether the solution from TRN is adequate for TRN/INS integration or not, and this scheme gives the performance improvement. Simulation result shows that the proposed indices are meaningful and the proposed algorithm performs better than normal TRN algorithm.

A Development of AIS Vessel Monitoring System on online map using HTML5 (HTML5를 활용한 온라인 지도 기반 AIS선박 모니터링 시스템 구현)

  • Lee, Seo-Jeong;Lee, Jae-Wook
    • Journal of Navigation and Port Research
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    • v.35 no.6
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    • pp.463-467
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    • 2011
  • As the increasing of requirement for safety navigation, IMO has enforced the mandatory installation of vessel AIS equipment by SOLAS regulation. The AIS transceiver broadcasts various vessel information which can be gathered by the receivers on-board or on-shore. And, recently, as web-based application developments on various devices have been increased, there are more and more requirements of AIS information presentation on internet. To meet these web-based application requirements, this paper shows the practical implementation of the AIS display system, which is on the Google maps as online commercial map and adopts the HTML5 as a web standard.

A Technique for Building Occupancy Maps Using Stereo Depth Information and Its Application (스테레오 깊이 정보를 이용한 점유맵 구축 기법과 응용)

  • Kim, Nak-Hyun;Oh, Se-Jun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.3
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    • pp.1-10
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    • 2008
  • An occupancy map is a representation methodology describing the region occupied by objects in 3D space, which can be utilized for autonomous navigation and object recognition. In this paper, we describe a technique for building an occupancy map using depth data extracted from stereo images. In addition, some techniques are proposed for utilizing the occupancy map for the segmentation of object regions. After the geometric information on the ground plane is extracted from a disparity image, the occupancy map is constructed by projecting each matched point to the ground plane-based 3D space. We explain techniques for extracting moving object regions using the occupancy map and present experimental results using real stereo images.