odometry

简明释义

英[əʊˈdɒmətri]美[oʊˈdɑːmətri]

n. 量距，测程法

英英释义

单词用法

同义词

反义词

例句

1.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。

2.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。

3.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。

4.Visual odometry can get accurate motion information, so it can be used to rectify the stereo images in wide baseline stereo matching system.

视觉里程计可以求取出准确的运动参数，从而可以利用这些参数对宽基线立体匹配中的立体图像对进行有效的校正。

5.Chapter IV introduces the application of visual odometry in wide baseline stereo matching.

第四章主要介绍了视觉里程计在宽基线立体匹配中的应用。

6.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。

7.Odometry Used for speed measurement and distance measurement.

里程计用于测速和测距。

8.The robot uses odometry to calculate its position based on wheel rotations.

机器人使用里程计根据轮子旋转计算其位置。

9.In autonomous vehicles, odometry is crucial for navigation and path planning.

在自动驾驶汽车中，里程计对导航和路径规划至关重要。

10.The accuracy of odometry can be affected by wheel slippage on uneven terrain.

里程计的准确性可能会受到不平坦地形上轮子打滑的影响。

11.Using odometry, the drone was able to maintain a steady course despite wind gusts.

通过使用里程计，无人机能够在风阵中保持稳定航向。

12.Engineers often combine odometry with GPS data for improved positioning accuracy.

工程师们通常将里程计与GPS数据结合，以提高定位精度。

作文

Odometry is a crucial concept in the field of robotics and navigation. It refers to the use of data from motion sensors to estimate a robot's change in position over time. The term itself comes from the Greek words 'odos', meaning path, and 'metron', meaning measure. Essentially, odometry (里程测量) allows machines to understand how far they have traveled and in which direction, which is vital for tasks such as mapping and autonomous navigation. In practical applications, odometry is used in various types of vehicles, from wheeled robots to drones. For instance, in mobile robots, odometry helps in tracking the robot's movement on a flat surface. Sensors such as encoders attached to the wheels measure rotation, allowing the robot’s control system to calculate the distance traveled. This information is then used to update the robot's position on a map, helping it navigate through its environment. However, while odometry (里程测量) is invaluable, it is not without its challenges. One major issue is the accumulation of errors over time, known as drift. As a robot moves, small inaccuracies in measurement can compound, leading to significant deviations from the actual path taken. This is particularly problematic in complex environments where precise navigation is essential. To counteract this, many systems employ additional sensors, such as GPS or visual odometry, which uses images from cameras to help correct the robot's estimated position. The importance of odometry (里程测量) extends beyond just robotics; it also plays a role in various fields such as automotive engineering and aerospace. In self-driving cars, for example, odometry works alongside other technologies like LiDAR and radar to provide a comprehensive understanding of the vehicle's surroundings. By integrating data from multiple sources, these vehicles can create accurate maps of their environment, allowing them to make informed driving decisions. Moreover, researchers are continually exploring ways to improve odometric techniques. Innovations such as machine learning algorithms are being developed to enhance the accuracy of position estimation. By training models on vast datasets, these algorithms can learn to recognize patterns in motion that traditional methods might miss, leading to more reliable navigation solutions. In conclusion, odometry (里程测量) is an essential technology that underpins much of modern robotics and navigation systems. Its ability to provide real-time position estimates enables machines to operate autonomously in dynamic environments. While challenges such as error accumulation exist, ongoing research and advancements in sensor technology promise to enhance the reliability and effectiveness of odometric methods. As we continue to integrate robotics into our daily lives, understanding and improving odometry (里程测量) will be critical to the success of these technologies.