环境地图

精确的定位是以环境地图为基础的，而创建环境地图，则必须知道机器人在各个观测点的精确位置。

To build environment map , robot must know its location at every observation point .

通过该软件可以在环境地图已知的情况下，快速规划出一条最优路径。

An optimal path can be planed quickly by the software when the environment map is known .

接着介绍了试验的前期准备，即AUV平台携带的传感器以及SLAM算法中用于构建环境地图的特征的提取。

Next , experimental preparation is introduced , which includes sensors carried in AUV platform and features extraction for map construction in SLAM .

与已有的几何位姿估计方法或航标匹配方法不同，该方法不需要人工航标，也不需要准确的环境地图，只需一幅由传统的CCD相机拍摄的图像。

Unlike those reported geometry pose estimation or landmarks matching methods , this approach requires an image taken by a conventional CCD camera but needs neither artificial landmarks nor an accurate map of an indoor environment .

该算法只考虑窗口环境地图，避免了全局搜索，使得RRT算法可以在未知环境下的移动机器人路径规划中应用。

Only the local environmental map is calculated in the planning , thus the searching all environmental map is avoided , so that the RRT algorithm can be used in path planning not only when the environment is known but also unknown .

4维环境地图通过Krige法进行插值可生成栅格地图、利用高程变异算子可生成单元分解地图以及通过二叉树查找可生成拓扑地图。

Then some map transform methods from 4-D environmental map are discussed separately . They are grid map generating by Krige interpolation , cell decomposition map generating by elevation mutation operator , and topological map generating by binary tree finding .

基于环境地图的移动机器人路径规划研究

Research on Path Planning of Mobile Robot Based on Environmental Map

基于激光测距的环境地图动态创建技术研究

The Dynamic Environment Mapping Technology Based on Laser Measurement Sensor

基于声纳和摄像头的动态环境地图创建方法

Mapping dynamic environments based on sonar and camera

因此，论文针对多机器人覆盖提出了4维环境地图的地图表示方法。

So , the 4-D environmental map for coverage is researched in this thesis .

用声环境地图法改革我国城市声环境质量评价体系初探

A Study of Reform Urban Environmental Noise Evaluation System by using Noise Contour Map Method

探索未知区域并构建环境地图是移动机器人研究领域的经典问题。

Building map after exploring unknown environment is a classic problem in mobile robot research .

环境地图是机器人导航的基础，本文以栅格地图的方式存储和表示环境地图。

In this thesis , grid map is used to stored and represent environment map .

然后，机器人利用自身位姿及对目标的观测来构建环境地图。

Then , the environmental map is built according to robot poses and its observations .

提出在基于单目视觉创建的环境地图中实现移动机器人全局定位。

An environmental map built with monocular vision is used to implement mobile robot global localization .

而在4维环境地图中，可以通过简单的循环二叉树查找来获得这些关键点的坐标值。

In 4-D environmental map , these key points can be got by binary tree finding simply .

针对仿人机器人传感器配置和步行特点，提出了建立环境地图的方案。

A scheme of building the map of circumstance is presented based on sensor equipment and walking trait .

在获得激光传感器扫描数据后，该方法用栅格模型来构造二维环境地图。

With the data scanned by laser sensor , this method uses grid models to build 2-D environment map .

第一部分内容是环境地图构建，包括室内环境地图构建和室外环境地图构建。

The first subject of this dissertation is focused on environment map building for indoor environment and outdoor environment .

机器人的大脑将传感器收集的所有信息组合起来并更新它的环境地图。

The robot 's brain fuses all the information gathered by its sensors and updates the map of its world .

结合上述匹配算法，给出了一种基于激光测距仪的移动机器人环境地图实时创建方法。

A method of map building based on laser scans using the matching method above was presented for mobile robots .

自主创建环境地图近十多年来一直是移动机器人领域的研究热点。

Autonomous mapping has been a highly active research area in the field of mobile robots during the last decade .

该文综述了其在绘制危险环境地图以及建立疾病预警系统方面的应用以及面临的问题。

This article summarizes the implement in the mapping diseases risk environments and establishing the early warning systems and the challenge .

同步定位且能够精确构建环境地图的能力是机器人实现真正自主的必要前提。

The ability of simultaneously localizing a robot and accurately map its surroundings is a key prerequisite of truly autonomous robots .

进一步从制图综合基本问题出发，阐述了移动环境地图自动综合的概念。

Then we elaborated the concept of map generalization in mobile environment from the point of the fundamental problems in map generalization .

对于室外道路环境地图构建，首先提出了一个基于统计密度的障碍检测算法，用于道路环境和越野环境下的障碍检测。

To build outdoor environment map , an approach based stochastic density is proposed for obstacle detection on the road and crosscountry .

对于室内环境地图构建，由于采样点在空间分布上的不均匀性，运用变阈值自适应分隔方法对采样点进行聚类，同时运用加权统计中心来表示拟合线段的中点。

To build indoor environment map , adaptive segmentation and weighted stochastic mean are used because the sample points are not distributing uniformly .

所以本文就围绕着移动机器人研究中的环境地图构建、移动机器人定位、同时定位与地图构建三个问题进行了深入研究，取得了一些有意义的成果。

This dissertation is focused on environment map building , mobile robot localization , simultaneous localization and map building . Exciting results are achieved .

研究的内容包括环境地图的表示，基本的行进方式，以及具体的算法设计流程等。

The main content of the research includes the expression of the environmental map , the way of going , and the detail process design of algorithm .

构建环境地图是伴随着探索过程同时进行的，移动机器人探索一个区域后立即构建该区域的环境地图。

The build environment map is accompanied by exploration at the same time , the mobile robot to explore an area and build map in this region immediately .