Fan Zheng

Fan Zheng
The Chinese University of Hong Kong | CUHK · Department of Mechanical and Automation Engineering

PhD
VisionNav Robotics

About

9
Publications
1,303
Reads
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76
Citations
Introduction

Publications

Publications (9)
Article
Visual inertial fusion is the problem to estimate vehicle states using visual and inertial measurements, and has recently been an active research topic. Existing visual inertial fusion approaches formulate their estimation algorithms for mobile robots in general 3-D space, and cannot satisfactorily model the nearly planar motion of ground vehicles....
Article
This paper focuses on the motion estimation problem of ground vehicles using odometry and monocular visual sensors. While the keyframe-based batch optimization methods become the mainstream approach in mobile vehicle localization and mapping, the keyframe poses are usually represented by SE(3) in vision-based methods or SE(2) in methods based on ra...
Article
This paper presents a brief review on recent work on machine intelligence for real-world applications of robots. To act in a real world environment, a robot should possess a broad sense of intelligence including speech, perception, reasoning, action, etc. In this paper, we particularly deal with the intelligence involving action or body motion. The...
Conference Paper
For the localization problem of mobile robots in 3D space, vision-based methods are being extensively investigated in recent years, due to the information richness provided by images. To improve the robustness and continuity, usually more sensors are introduced to assist visual localization in practices. In this paper, we propose a geometric model...
Conference Paper
Full-text available
This paper presents a lens-free and portable quantitative phase microscope. This microscope employs a concise off-axis set-up where a dual-pinhole aperture is utilized to generate the reference wave and the object wave. As no lenses or beamsplitters are used in this microscope, the total size of this microscope is only slightly larger than a smart...

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