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相关概念视频

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

27
Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
27
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

610
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
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相关实验视频

Updated: Jun 14, 2025

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

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一种以对象为中心的等级姿势估计方法,使用语义高清地图用于一般自动驾驶.

Jeong-Won Pyo1, Jun-Hyeon Choi1, Tae-Yong Kuc1

  • 1Department of Electrical and Computer Engineering, College of Information and Communication Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea.

Sensors (Basel, Switzerland)
|August 29, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种用于估计车辆姿势的新方法,这对于自动驾驶至关重要. 它使用带有物体的高清地图来提高GPS信号不可靠的区域的准确性.

关键词:
自动驾驶自动驾驶的自动驾驶.高清地图地图高清地图对象识别对象识别器地方识别 地方识别构成估计估计的估计.

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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

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相关实验视频

Last Updated: Jun 14, 2025

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
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科学领域:

  • 机器人和人工智能 机器人和人工智能
  • 计算机视觉 计算机视觉
  • 自主系统 自主系统

背景情况:

  • 强大的自动驾驶系统需要精确的车辆姿势估计.
  • 目前使用实时动态 (RTK) 传感器的方法在GPS被拒绝的环境中扎,例如室内或信号干扰的区域.
  • 不准确的姿势估计阻碍了可靠的自动驾驶汽车的发展.

研究的目的:

  • 开发一种更普遍,更强大的车辆位置估计方法.
  • 在具有挑战性的环境中克服RTK传感器的局限性.
  • 提高自动驾驶系统的稳定性和可靠性.

主要方法:

  • 利用注册对象的语义高清 (HD) 地图.
  • 从高清地图创建以对象为中心的特征.
  • 使用这些以对象为中心的功能识别车辆位置.
  • 根据已识别的位置估计车辆的姿势.

主要成果:

  • 拟议的方法显著提高了在RTK信号接收不佳的环境中车辆姿势估计精度.
  • 在具有挑战性的场景中提高自动驾驶系统的稳定性和稳定性.
  • 通过模拟和现实世界的实验证明了有效性.

结论:

  • 使用高清地图的对象中心方法为准确的车辆姿势估计提供了可行的解决方案,而RTK则失败了.
  • 这种方法有助于更可靠和更广泛地采用自动驾驶技术.
  • 进一步的研究可以探索与其他传感器模式的集成,以获得更大的稳定性.