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公开(公告)号：KR101694686B1
公开(公告)日：2017-01-10
申请号：KR1020160013460
申请日：2016-02-03
Applicant: 국방과학연구소
IPC: F41H11/12 , F41H11/136 , F41H7/00
Abstract: 본발명의차량용지뢰위치표시세분화타입지뢰탐지장치는센서모듈경계면으로구분되어지뢰탐지영역에서지뢰를검출하는센서모듈(20), 포지션노즐(31)의용액분사로지뢰탐지영역을 3개의지뢰검출구간으로구분하면서동시에디렉션노즐(33-1,33-2)의용액분사로지뢰탐지영역을좌우방향으로구분하는분사노즐모듈(30)을포함함으로써탐지된지뢰에대한위치세분화가이루어지고, 특히탐지지뢰위치세분화에의한신속및 정확한위치판단이이루어짐으로써후방부대의후속처리시 인명혹은재산피해를근본적으로방지하면서지뢰제거작업의신속성도향상되는특징을갖는다.
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公开(公告)号：KR1020160146374A
公开(公告)日：2016-12-21
申请号：KR1020150083568
申请日：2015-06-12
Applicant: 국방과학연구소
IPC: G05D1/02
Abstract: 본발명은무인차량또는주행가능한로봇을위한주행경로계획장치및 이의제어방법에관한것으로서, 관심영역을설정받는단계, 제1 지형정보와관련된제1 데이터베이스를이용하여, 상기설정된관심영역에대한제1 주행비용을산출하는단계, 상기제1 지형정보와다른제2 지형정보와관련된제2 데이터베이스를이용하여, 상기설정된관심영역에대한제2 주행비용을산출하는단계및 상기산출된제1 및제2 주행비용에근거하여, 상기관심영역내의경로맵을생성하는단계를포함하고, 상기제1 지형정보는적어도하나의레이어로분류된 GIS 디지털지형정보로형성되고, 상기제2 지형정보는지표면의속성과관련된정보를포함하는것을특징으로한다.
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公开(公告)号：KR1020150109781A
公开(公告)日：2015-10-02
申请号：KR1020140033070
申请日：2014-03-21
Applicant: 국방과학연구소
CPC classification number: B25J19/02 , B25J9/1694 , B25J19/06
Abstract: 본발명은자신의위치를감지하는항법센서를기본으로하여목표물의위치를감지하는각 센서(1-2)와거리센서(1-3)가분산탑재되고, 센서(1-2,1-3)의움직임을고려한기하학관계에근거하여목표물정보량을최대화할수 있는협업기동전략이수행되는제1 로봇(10) 및제2 로봇(20)이이용되고, 분산탑재된각 센서(1-2)와거리센서(1-3)로부터목표물(100)을감지하고, 추정된목표물과로봇(10,20)과의정규화거리를계산하며, 정규화거리를기반으로해당되는기준에따른전략을선택하고, 전략에따른헤딩값을산출하는이종센서를분산탑재한로봇의목표물위치추정협업방법이구현됨으로써목표물정보량을최대화할수 있는해석적으로제시되는협업기동전략에대한계산로드(Computing Load)없이최적결과가얻어지는특징을갖는다.
Abstract translation: 根据本发明，基于检测用户位置的导航传感器，分散检测目标位置的角度传感器（1-2）和距离传感器（1-3）来加载。 基于考虑传感器（1-2,1-3）的运动的几何关系，使用执行最大化目标信息量的协作机动策略的第一机器人（10）和第二机器人（20）。 从分散加载的角度传感器（1-2）和距离传感器（1-3）检测目标（100）。 计算估计目标与机器人（10,20）之间的归一化距离。 根据标准化距离根据相关标准选择策略。 实现了一种机器人的目标位置估计协作方法，其中根据该策略计算标题值的不同类型传感器被分散以加载，从而获得最佳结果而不计算相对于分析地提供以最大化的协作机动策略的负载 目标信息量。
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公开(公告)号：KR101475240B1
公开(公告)日：2014-12-22
申请号：KR1020140063924
申请日：2014-05-27
Applicant: 국방과학연구소
CPC classification number: F16H55/36 , F16H2055/366
Abstract: 본 발명은 회전축이 고정될 수 있도록 고정홀을 형성하는 회전축 결합부, 상기 회전축 결합부과 이격공간을 형성하도록 상기 회전축 결합부를 감싸며, 제1 폭을 갖도록 형성되는 회전프레임, 상기 회전축 결합부 및 상기 회전프레임 사이를 지지하도록 형성되고, 상기 제1 폭보다 좁은 제2 폭을 갖도록 형성되는 지지프레임, 탄성재질로 이루어지며, 상기 회전축 결합부 및 상기 회전프레임 사이를 탄성 지지하도록 상기 이격공간의 적어도 일부를 메우도록 형성되는 링 형상의 탄성부를 포함하는 탄성형 풀리를 제공한다.
Abstract translation: 弹性滑轮技术领域本发明涉及一种弹性滑轮，包括：旋转轴联接部，其形成适于将旋转轴固定到其上的固定孔; 旋转框架，其适于围绕旋转轴联接部分以形成与具有第一宽度的旋转轴联接部分分离的空间，适于支撑旋转轴联接部分和旋转框架之间的空间的支撑框架，并且每个具有第二 宽度小于第一宽度; 以及由弹性材料制成的环形弹性部件，其适于填充所述空间的一部分以弹性地支撑所述旋转轴联接部分和所述旋转框架之间的空间。
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Patent Agency Ranking
公开(公告)号：KR101416124B1
公开(公告)日：2014-08-06
申请号：KR1020130035649
申请日：2013-04-02
Applicant: 국방과학연구소
IPC: G01J1/02
CPC classification number: G01J1/0242 , A63F9/02 , F41G3/26 , G01J1/42
Abstract: A long distance target maneuver indoor simulator of the present invention comprises a fast steering mirror module (40) which converts the infrared wavelength of a target generated at a close distance into a light source of long distance infrared wavelength suited to an azimuth and a high-angle direction which a relatively long distance target has, and an optical module (20) which makes a reached IR light source of infrared wavelength into a parallel beam with a narrow optical width and then creates a parallel beam magnified three times. Therefore, the long distance target maneuver indoor simulator enables a tracking performance test of an image tracking device (40) even in a very narrow interior space and, in particular, can calculate quantitative target tracking accuracy by accurately identifying the position of a target in an image using azimuth and a high-angle direction.
Abstract translation: 本发明的长距离目标机动室内模拟器包括快速转向镜模块（40），其将近距离生成的目标的红外波长转换成适合于方位角的长距离红外波长的光源， 相对长距离目标具有的角度方向以及将红外波长的到达红外光源的光学模块（20）成为具有窄光学宽度的平行光束，然后创建放大三倍的平行光束。 因此，长距离目标机动室内模拟器即使在非常狭窄的内部空间中也能够进行图像跟踪装置（40）的跟踪性能测试，并且特别地，可以通过精确地识别目标的位置来计算定量目标跟踪精度 图像使用方位角和高角度方向。
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公开(公告)号：KR101280348B1
公开(公告)日：2013-07-01
申请号：KR1020120005611
申请日：2012-01-18
Applicant: 국방과학연구소
Abstract: PURPOSE: A multiple target tracking method is provided to improve tracking performance by accurately classifying target and clutter using geometric information extracted from a target image. CONSTITUTION: A multiple target tracking method includes a target state prediction step predicting a kinetic state vector of a target and a state vector of a geometric image characteristic, an NN measurement value selection step selecting an NN measurement value through a sum of the kinetic state vector and state vector of geometric image characteristic provided in the target state prediction step and a state vector estimation update step updating state vector estimation using the NN measurement value selected by the NN measurement selection step. [Reference numerals] (AA) Start; (BB) End; (S301) Target state prediction step predicting a kinetic state vector/a state vector of a geometric image characteristic; (S302) NN measurement value selection step selecting an NN measurement value through (the kinetic state vector + state vector of geometric image characteristic); (S303) State vector estimation update step updating state vector estimation using the NN measurement value
Abstract translation: 目的：提供多目标跟踪方法，通过使用从目标图像提取的几何信息，精确地对目标和杂波进行分类，提高跟踪性能。 构成：多目标跟踪方法包括预测目标的动态状态向量和几何图像特征的状态向量的目标状态预测步骤，NN测量值选择步骤，通过动态状态矢量的和选择NN测量值 以及在目标状态预测步骤中提供的几何图像特性的状态矢量和使用由NN测量选择步骤选择的NN测量值来更新状态矢量估计的状态矢量估计更新步骤。 （附图标记）（AA）开始; （BB）结束; （S301）预测几何图像特征的动态状态向量/状态向量的目标状态预测步骤; （S302）NN测量值选择步骤通过（动态状态向量+几何图像特征的状态向量）来选择NN测量值; （S303）状态向量估计更新步骤使用NN测量值来更新状态向量估计
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公开(公告)号：KR1020130058480A
公开(公告)日：2013-06-04
申请号：KR1020110124502
申请日：2011-11-25
Applicant: 국방과학연구소
IPC: H04N5/262
CPC classification number: H04N5/265 , H04N7/0135
Abstract: PURPOSE: An image fusion device and a method are provided to perform registration and fusion of images based on a transformation matrix, which is produced using test images offline. CONSTITUTION: An image fusion method, by an image fusion device, comprises the steps of: acquiring a first and a second image which are object images for fusion(S110); generating a third image by transforming the first image based on a transformation matrix(S120); and generating a fusion image by fusing the second and third image(S130). The transformation matrix is characterized by including coefficients considering image errors between a fourth image and a fifth image, which are test images, based on corresponding points, after at least one or more corresponding points are found in the fourth image and the fifth image. [Reference numerals] (AA) Start; (BB) End; (S110) Acquire a first and seconds image corresponding to fusion images; (S120) Generate a third image by transforming the first image based on a transformation matrix; (S130) Generate a fusion image by fusing the second and third image
Abstract translation: 目的：提供一种图像融合装置和方法，用于基于使用测试图像离线产生的变换矩阵来执行图像的注册和融合。 构成：通过图像融合装置的图像融合方法包括以下步骤：获取作为融合的对象图像的第一和第二图像（S110）; 通过基于变换矩阵变换第一图像来生成第三图像（S120）; 以及通过融合所述第二和第三图像来生成融合图像（S130）。 转换矩阵的特征在于，在第四图像和第五图像中找到至少一个或多个对应点之后，基于考虑图像，考虑第四图像和第五图像之间的图像误差的系数，其为测试图像。 （附图标记）（AA）开始; （BB）结束; （S110）获取与融合图像相对应的第一和第二图像; （S120）通过基于变换矩阵变换第一图像来生成第三图像; （S130）通过融合第二和第三图像生成融合图像
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公开(公告)号：KR101262697B1
公开(公告)日：2013-05-15
申请号：KR1020120147708
申请日：2012-12-17
Applicant: 국방과학연구소
IPC: B25J9/16 , G05B19/418 , B25J13/06
CPC classification number: Y02P90/02
Abstract: PURPOSE: A system for producing a formation of a robot and a method thereof are provided to autonomously produce various formations based on dispersed intelligence and ad-hoc networking, and to improve an operation effect of the robot. CONSTITUTION: A system(10) for producing a formation of a robot comprises a control system(100), a seed robot, and a follower robot. The seed robot selects one or more robots responding to a call signal as the follower robot, and produces an arbitrary formation through interlocking with the follower robot. The follower robot is transferred to a formation position point coordinate included to the call signal transmitted from the seed robot. The formation starting command includes information about the arbitrary formation and parameter setup information related to the formation. [Reference numerals] (100) Control system; (200) Communication network; (300) Ad-hoc network; (310,320,330,340,350) Robot
Abstract translation: 目的：提供一种用于生成机器人的形成的系统及其方法，用于基于分散的智能和自组织网络自主地生成各种结构，并且改善机器人的操作效果。 构成：用于产生机器人形成的系统（10）包括控制系统（100），种子机器人和从动机器人。 种子机器人选择响应于呼叫信号的一个或多个机器人作为从动机器人，并且通过与从动机器人互锁产生任意形成。 跟随机器人被转移到从种子机器人发送的呼叫信号所包含的形成位置点坐标。 地层起动指令包括有关地层的任意地层和参数设置信息。 （附图标记）（100）控制系统; （200）通讯网络; （300）Ad-hoc网络; （310,320,330,340,350）机器人
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公开(公告)号：KR101217611B1
公开(公告)日：2013-01-02
申请号：KR1020110009565
申请日：2011-01-31
Applicant: 국방과학연구소
IPC: H04N5/208
Abstract: 본발명은부 영상기반의영상등록방법에관한것으로서, 구체적으로는상관도(Cross Correlation) 계산을통한영상등록방법에있어서, 전체영상을일정한크기로분할하여다수의부 영상을추출하는부 영상추출단계와, 상기추출된각각의부 영상의경계부분에대하여경계완화(Edge Tapering) 기능을적용시키는단계와, 상기각각의부 영상의균질도(Uniformity) 및엔트로피(Entropy)를계산하여일정크기이상의균질도와일정기준이하의엔트로피를가지는부 영상을등록될부 영상으로결정하는단계와, 상기등록될부 영상의이동량을계산하고계산된이동량의평균을구하는단계와, 상기부 영상을등록하는단계를포함한다. 본발명에따른부 영상기반의영상등록방법을이용하면, 연산량을감소시키고, 영상등록의정확도를향상시킬수 있으며, 나아가미세한움직임을갖는침입인원에대하여정확도가높은영상을제공할수 있다.
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