odometry

Fusion Model of GPS and Odometry in Mobile Robot Navigation

GPS与测距法的融合模型在机器人导航中的实现

The effects of GPS signal errors on mobile robot positioning accuracy were studied and a fusion model by blending GPS and odometry data was presented .

分析了GPS信号的误差对移动机器人定位精度的影响，提出了GPS信号与测距法的融合模型。

This paper describes a new way to fuse vision information and odometry data .

摘要提出了一种新的将视觉信息和里程计数据相融合的方法。

Research on Mobile Robot Localization Based on Stereo Visual Odometry

基于立体视觉里程计的移动机器人定位研究

An approach based on disparity space to a binocular visual odometry system is presented .

提出了一种基于视差空间的双目视觉里程计算法。

Measurement and Calibration of Systematic Errors of Odometry

测程法系统误差的测量与校核

Realization of the Monocular Vision Odometry Based on Extracting Keypoints by SIFT in the Navigation System

基于SIFT特征提取的单目视觉里程计在导航系统中的实现

An approach based on least median squares ( LMedS ) to a stereo-based visual odometry system is presented .

最后，研究了基于立体视觉里程计的移动机器人定位算法及其实现，提出了基于最小平方中值定理的立体视觉里程计算法。

By analyzing a series of related image sequences , visual odometry can ascertain the position and posture of robots and estimate their displacement .

视觉里程计是一个通过分析相关图像序列，来确定机器人位姿和估算机器人移动距离的过程。

One is vision-based pose tracking , which uses the environment information from vision sensor to correct the robot 's estimated pose obtained by odometry .

一种是基于视觉的位姿跟踪方法，其特点是利用视觉传感器得到的环境信息来对基于里程计所获得的机器人预估位姿进行校正。

In comparison with the traditional method , visual odometry enhances the robot navigation accuracy and is better able to adpt to changing conditons .

与传统的移动传感器测距方式相比，视觉里程计增强了机器人的导航精度，对环境的适应能力更强。

Based on Monte Carlo localization , the system makes use of high-noised sensor data of artificial and natural landmarks , along with odometry data without feedback .

该系统基于MonteCarlo定位方法，分别利用了人工地标和自然地标的高噪声的传感器信息，结合无反馈的里程计信息来完成自身定位。

The navigation subsystem of the mobile robot fuses the position estimation obtained by a vision system with the position estimated by odometry using a Kalman filter .

移动机器人的导航子系统利用卡尔曼滤波器，融合由视觉系统与由里程计获得的位置估计值。

In the fields of robotics and computer vision , visual odometry is one of the research focuses and this technology has been successfully applied to autonomous mobile robots .

在机器人学和计算机视觉领域中，视觉里程计是研究的热点之一，并且该技术已成功运用于自主移动机器人中。

Finally we design a Monte Carlo localization method based on the information of omni-vision system and odometry , and present the localization results of two localization methods and analyze the experiment results and get the conclusions .

最后设计了一种基于全向视觉信息和里程计信息的MonteCarlo定位方法，给出两种方法的定位结果，并分析实验结果，给出结论。

The fundamental principles of stereo binocular vision system are the basis of study for binocular stereo vision . Thirdly , the system framework of binocular stereovision odometry is introduced , and a deep study of the key techniques it includes is taken .

双目立体视觉系统的基本原理是之后进行双目立体视觉里程计研究的基础。再次，介绍了双目立体视觉里程计的系统框架，基于此框架，对其涉及的各项关键技术进行了深入的研究。