• Title/Summary/Keyword: UGV

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Design of Ultra Wide Band Radar Transceiver for Foliage Penetration (수풀투과를 위한 초 광대역 레이더의 송수신기 설계)

  • Park, Gyu-Churl;Sun, Sun-Gu;Cho, Byung-Lae;Lee, Jung-Soo;Ha, Jong-Soo
    • Journal of Satellite, Information and Communications
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    • v.7 no.1
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    • pp.75-81
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    • 2012
  • This study is to design the transmitter and receiver of short range UWB(Ultra Wide Band) imaging radar that is able to display high resolution radar image for front area of a UGV(Unmanned Ground Vehicle). This radar can help a UGV to navigate autonomously as it detects and avoids obstacles through foliage. The transmitter needs two transmitters to improve the azimuth resolution. Multi-channel receivers are required to synthesize radar image. Transmitter consists of high power amplifier, channel selection switch, and waveform generator. Receiver is composed of sixteen channel receivers, receiver channel converter, and frequency down converter, Before manufacturing it, the proposed architecture of transceiver is proved by modeling and simulation using several parameters. Then, it was manufactured by using industrial RF(Radio Frequency) components and all other measured parameters in the specification were satisfied as well.

An Improved Position Estimation Algorithm of Vehicles Using Semantic Information of Maps (지도의 의미 정보를 이용한 개선된 차량 위치 추정 알고리즘)

  • Lee, Chang Gil;Choi, Yoon Ho;Park, Jin Bae
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.9
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    • pp.753-758
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    • 2016
  • In this paper, we propose a novel method for estimating a vehicle's current position, even on roads that have similar patterns. In the proposed method, we classified the semantic information of the nodes in detail and added the semantic information of the link to solve the problem due to similar and repeated patterns. We also improved the mapping method by comparing the result of the duplicated matching with that of the only matching obtained just before corresponding duplicated matching. From the simulation results, we verify that the performance of the proposed method is better than that of the existing method.

A Study for Prediction of Water Contents in Soil by Using the Soil Thermal Conductivity (토양 열전도를 이용한 토양함수비 예측에 관한 연구)

  • Cho, Jin-Woo;Kang, Do-Kyung;Kang, E-Sok
    • Journal of the Korea Institute of Military Science and Technology
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    • v.18 no.2
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    • pp.125-130
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    • 2015
  • Vehicles and UGV(Unmanned Ground Vehicle) need a variety of road informations, such as road profile, soil type and soil water contents, to run a cross country course. Especially, soil water contents are very important factor to judge the vehicle mobility, because it can change soil strength. This paper describes the real-time measuring method of soil water contents by using the soil thermal conductivity.

Development of a TOF LADAR Sensor for Unmanned Vehicle Systems (무인수송체 시스템용 TOF 방식 이차원 라이다 센서 개발)

  • Kim, MinGyu;Park, YongWoon;Won, Mooncheol
    • Journal of the Korea Institute of Military Science and Technology
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    • v.19 no.4
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    • pp.415-423
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    • 2016
  • A TOF type LADAR is utilized for unmanned systems(UGV, UAV, USV, etc.), precision digital elevation maps, and electronic fences. Electronical and optical signal processing techniques are melted in LADAR sensor systems. In this study important factors are examined for high reliability sensor development. By considering those factors, hardwares and softwares of a test LADAR is developed and tested, We report the practical design tips, test results, and future works for better LADAR system development.

A Terrain Analysis System for Global Path Planning of Unmanned Ground Vehicle (무인지상차량의 전역경로계획을 위한 지형정보 분석 시스템)

  • Park, Won-Ik;Lee, Ho-Joo;Kim, Do-Jong
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.5
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    • pp.583-589
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    • 2013
  • In this paper, we proposed a system that efficiently provides support maps which includes the grid based terrain analysis information. To do this, we use the FDB which is defined as a GIS database that contains features with attributes attached to the features. The FDB is composed of a number of features and feature classes. In order to create support maps, it is necessary to classify feature classes that are associated with each support map and to search them in a grid map. The proposed system use a ontology model to classify semantically feature classes and the quad-tree data structure to find them in a grid map quickly. Therefore, our system is expected to be utilized for global path planning of UGV. In this paper, we show the possibility through an experimental implementation.

Developments of a Path Planning Algorithm for Unmanned Vehicle (무인차량을 위한 경로계획 알고리즘 개발)

  • Cho, Kyoung-Hwan;Ahn, Dong-Jun;Kim, Gun-Sik;Kim, Yong-Il
    • Journal of the Korean Society of Industry Convergence
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    • v.14 no.2
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    • pp.53-57
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    • 2011
  • Military and commercial unmanned vehicle navigation systems are being actively studied in the field of robotics. In this study, GPS-based path generation algorithm Film Festival and the system can compensate for the shortcomings of applying a map-based path plan, the unmanned vehicle navigation systems to improve the performance of path planning algorithms are introduced.

Distance Transform Path Planning using DEM and Obstacle Map (DEM과 장애물 지도를 이용한 거리변환 경로계획)

  • Choe, Tok-Son;Jee, Tae-Young;Kim, Jun;Park, Yong-Woon;Ryu, Chul-Hyung
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.92-94
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    • 2005
  • Unmanned ground vehicles(UGVs) are expected to play a key role in the future army. These UGVs would be used for weapons platforms. logistics carriers, reconnaissance, surveillance, and target acquisition in the rough terrain. Most of path planning methodologies for UGVs offer an optimal or sub-optimal shortest-path in a 20 space. However, those methodologies do not consider increment and reduction effects of relative distance when a UGV climbs up or goes down in the slope of rough terrain. In this paper, we propose a novel path planning methodology using the modified distance transform algorithm. Our proposed path planning methodology employs two kinds of map. One is binary obstacle map. The other is the DEM. With these two maps, the modified distance transform algorithm in which distance between cells is increased or decreased by weighting function of slope is suggested. The proposed methodology is verified by various simulations on the randomly generated DEM and obstacle map.

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Terrain Cover Classification Using Wavelet Features and Neural Networks (웨이브릿 특징과 신경망을 이용한 지형분류)

  • Sung, Gi-Yeul;Kwak, Dong-Min;Kim, Do-Jong;Lyou, Joon
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.853-854
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    • 2008
  • The terrain perception technology using passive sensors plays a key role to enhance autonomous mobility for UGV. We present an effective method to classify terrain covers based on the color information. Considering a real-time implementation, neural network is applied for the terrain classifier and wavelet features extracted from the images are used. Test results show that the proposed algorithm has a promising classification performance.

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Smart AGV system using the 2D spatial map

  • Ko, Junghwan;Lee, Jong-Yong
    • International Journal of Internet, Broadcasting and Communication
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    • v.8 no.4
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    • pp.54-57
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    • 2016
  • In this paper, the method for an effective and intelligent route decision of the automatic ground vehicle (AGV) using a 2D spatial map of the stereo camera system is proposed. The depth information and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle detected and the 2D spatial map obtained from the location coordinates, and then the relative distance between the obstacle and the other objects obtained from them. The AGV moves automatically by effective and intelligent route decision using the obtained 2D spatial map. From some experiments on robot driving with 480 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the objects is found to be very low value of 1.57% on average, respectably.

Improvement of Localization Accuracy with COAG Features and Candidate Selection based on Shape of Sensor Data (COAG 특징과 센서 데이터 형상 기반의 후보지 선정을 이용한 위치추정 정확도 향상)

  • Kim, Dong-Il;Song, Jae-Bok;Choi, Ji-Hoon
    • The Journal of Korea Robotics Society
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    • v.9 no.2
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    • pp.117-123
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    • 2014
  • Localization is one of the essential tasks necessary to achieve autonomous navigation of a mobile robot. One such localization technique, Monte Carlo Localization (MCL) is often applied to a digital surface model. However, there are differences between range data from laser rangefinders and the data predicted using a map. In this study, commonly observed from air and ground (COAG) features and candidate selection based on the shape of sensor data are incorporated to improve localization accuracy. COAG features are used to classify points consistent with both the range sensor data and the predicted data, and the sample candidates are classified according to their shape constructed from sensor data. Comparisons of local tracking and global localization accuracy show the improved accuracy of the proposed method over conventional methods.