.png){kind=icon}
返回
Effective Feature-Based Downward-Facing Monocular Visual Odometry
.png){kind=icon}
PRE
AI
DOI：10.1109/TCST.2023.3294843.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
To achieve accurate pose estimation for robots in industrial applications and services, this brief proposes an effective feature-based downward-facing monocular visual odometry technology that uses an affordable sensor system and a systematic optimization approach. To extract more effective features simply and efficiently from images of the ground, even for small mobile systems, the proposed visual odometry system is designed in a lightweight and cost-effective manner; we used an easily available LED, a single-channel time-of-flight (ToF) sensor, and a monocular camera. From the extracted features, the potentially irrelevant ones are removed in advance, using a masking algorithm and measured velocity. This enhances feature efficiency and reduces the computational burden. Finally, the optimal pose estimate is explicitly obtained by solving a nonconvex optimization problem, to make the best use of the features. The experiments' results show that our proposed method improves feature tracking ability and pose estimation accuracy.
Keyword:
Downward-facing camera
masking
monocular visual odometry
nonconvex optimization
robot
期刊
IF:
3.9
论文数:
4.9K
被引数:
1.7W
机构
暂无机构信息
引用论文
.png){kind=icon}
Visual Servoing Trajectory Tracking of Nonholonomic Mobile Robots Without Direct Position Measurement无需直接位置测量的非完整移动机器人视觉伺服轨迹跟踪
PREAI
分享收藏分享收藏
分享收藏
查看更多内容