Abstract:
본 발명은 복수의 로봇을 이용한 가시선 정보 기반의 표적 위치 결정 방법 및 이를 위한 복수의 로봇 배치 방법에 관한 것이다. 본 발명의 일 실시 예에 따른 통제서버가 표적 위치를 결정하기 위해 복수의 로봇을 배치하는 방법은, 가상 표적을 설정하는 단계; 기 설정된 배치에 따라 상기 복수의 로봇이 배치되도록 상기 복수의 로봇으로 제어신호를 송신하고, 상기 기 설정된 배치에 위치한 상기 복수의 로봇으로부터 각각 상기 가상 표적으로의 가시선 정보를 수신받으며, 상기 가시선 정보를 이용해 상기 가상 표적이 특정 반경 내에 포함될 제1확률을 계산하는 단계; 상기 복수의 로봇이 상기 기 설정된 배치와 다르게 배치되도록 상기 복수의 로봇으로 제어신호를 송신하고, 재배치된 배치에 위치한 상기 복수의 로봇으로부터 각각 상기 가상 표적으로의 가시선 정보를 수신받으며, 상기 가시선 정보를 이용해 상기 가상 표적이 특정 반경 내에 포함될 제2확률을 계산하는 단계; 및 상기 기 설정된 배치 및 상기 재배치된 배치에 대하여, 상기 제1확률과 제2확률을 비교하여 더 높은 확률을 가지는 때에 해당하는 배치를 결정하고, 상기 결정된 배치에 근거하여 상기 복수의 로봇이 배치되도록 상기 복수의 로봇으로 제어신호를 송신하는 단계;를 포함한다.
Abstract:
Disclosed is an operating method of a distributed multimedia system for a weapon system based on a service unit. According to the embodiments of the present invention, an operator sets a desirable service and a degree of service availability and each node is controlled by referring to information about the operation state and availability of each local node based on the set service and degree of service availability, thereby easily applying a redundant operation suitable for various features in system operation. Also, service management suitable for situations can be achieved and the availability of the nodes can be improved by reflecting the state monitoring information of the entire system in the redundant operation of the local node for each service.
Abstract:
The present invention relates to a terrain analysis method based on a grid map using a quad tree capable of effectively supporting the autonomous driving of an unmanned ground vehicle. The method is helpful in solving a problem that a response time increases as the number of conventional grids increases when a terrain analysis is performed in order to generate a grid map reflecting the situation of a target area in a global path planning which optimizes driving routes of a large area target. And the method comprises the steps of: recursively splitting digital terrain information of the NxN grid including terrain attribute information into 1/4; selecting the minimum sized grids including the terrain attribute information; performing a terrain information analysis on the selected minimum sized grids; and calculating costs for the analysis. [Reference numerals] (AA) Start; (BB,DD) No; (CC,EE) Yes; (FF) End; (S10) Recursively splitting the digital terrain information of the NxN grid including terrain attribute information into 1/4 using quadtree; (S11) Sequentially check each split grid; (S12) Is terrain attribute information included in each split grid?; (S13) Select a grid in which the terrain attribute information is included; (S14) Disregard; (S15) Is the size of the split grid minimum?; (S16) Finally select a grid in which the terrain attribute information is included; (S17) Perform the terrain information analysis for the finally selected grid and calculate cost
Abstract:
PURPOSE: An automatic moving device and an obstacle determining method of the device are provided to make more accurate decision if an obstacle is a human. CONSTITUTION: An obstacle determining method of an automatic moving device is as follows. An obstacle is detected from a front area. It is determined whether an obstacle is a moving obstacle or a fixed obstacle. It is determined what object the obstacle is. The contour of the obstacle is detected. The detected contour is changed into a defined shape of a figure. The changed data is compared with a shape of an object predefined as a figure. It is determined whether the changed data corresponds to a specific kind of an obstacle if being matched with the predefined shape of object.
Abstract:
PURPOSE: A local path planning method of an unnamed vehicle is provided to calculate the velocity of the vehicle and to reflect the topography of lattice corresponding regions. CONSTITUTION: A geographic information acquisition module collects the geographic information of a specific region. An obstacle information extraction module extracts the information of the obstacle in the specific region. A velocity calculation module calculates the velocity of an unmanned vehicle in each direction. The velocity calculation module generates a seed map based on a lattice system in each direction. A route extraction module calculates a route based on an optimum route setting algorithm.