Related Concept Videos
Confocal Fluorescence Microscopy
Imaging Biological Samples with Optical Microscopy
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
Light Acquisition
You might also read
Related Articles
Articles linked to this work by shared authors, journal, and citation graph.
Construction Method of a Digital-Twin Simulation System for SCARA Robots Based on Modular Communication.
Two-Level Model for Detecting Substation Defects from Infrared Images.
Related Experiment Video
Updated: Jan 13, 2026

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT
Published on: August 4, 2018
Multi-View Omnidirectional Vision and Structured Light for High-Precision Mapping and Reconstruction.
Qihui Guo1, Maksim A Grigorev1, Zihan Zhang1
1Department of Electric Drive, Mechatronics and Electromechanics, South Ural State University, Chelyabinsk 454080, Russia.
We created a virtual simulation for omnidirectional vision systems, improving obstacle reconstruction and distance estimation. This platform offers a cost-effective and safe alternative to physical testbeds for robotics research.
Area of Science:
- Robotics and Computer Vision
Background:
- Omnidirectional vision is crucial for autonomous navigation and mapping.
- Physical testbeds for omnidirectional vision are expensive, risky, and inefficient.
Purpose of the Study:
- To develop a flexible virtual simulation platform for multi-view omnidirectional vision.
- To propose and validate a novel reconstruction and ranging method using fused omnidirectional images and structured-light projection.
Main Methods:
- Development of a cross-platform virtual simulation environment for omnidirectional vision.
- Implementation of a fusion method combining multi-view omnidirectional images with structured-light projection.
- Validation through experiments in both simulated and real-world environments.
Main Results:
- Achieved high-precision obstacle contour reconstruction and distance estimation.
- Demonstrated distance errors within 8 mm in real-world experiments.
- Showcased robust performance across various camera configurations.
Conclusions:
- The virtual simulation platform provides a practical and efficient solution for omnidirectional vision research.
- The proposed fusion method enables accurate 3D perception without complex hardware or calibration.
- The platform facilitates cost-effective development and testing of autonomous systems.

