Handheld RGB-D Vision Sensing for Confined-Space 3D Scanning
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Solution Overview
Problem
Existing 3D scanning technologies are inadequate for confined spaces due to the lack of positioning infrastructure, requiring external computing devices and failing to provide compact, low-cost, high-accuracy 2D and 3D vision sensing with short-range capabilities.
Innovation Solution
A vision sensing device with a camera, laser pattern generator, inertial measurement unit, and processor that generates an RGB-D point cloud by combining visual, inertial, and depth data using a VLIO-SLAM algorithm, enabling infrastructure-free scanning in confined spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sensors are used for 3D scanning, then scanning capability is provided, but the system cannot detect objects in close range and requires external positioning infrastructure
Solution Approach 1:
The patent merges multiple sensing modalities (laser radar for depth, camera for visual data, IMU for motion) into a single integrated handheld device. This combination enables the system to achieve high scanning accuracy in confined spaces without external positioning infrastructure, as the fused sensor data provides both metric-scale measurement and self-contained localization capability.
Solution Approach 2:
The patent introduces structured light patterns as an intermediary between the laser radar and the object surface. By projecting and detecting these patterns, the system enables accurate depth measurement and localization in confined spaces without requiring external positioning aids, effectively mediating the measurement process in environments lacking traditional infrastructure.
2Measurement precision
If existing visual sensor systems are used, then 2D and 3D vision sensing is provided, but an additional external computing device is required and the system is too large
Solution Approach 1:
The patent integrates the laser radar, camera, and IMU into a single compact handheld device, eliminating the need for separate external computing devices. The processor within the device fuses data from all sensors to achieve accurate 2D and 3D vision sensing, thereby reducing overall system complexity and size while maintaining high measurement precision.
Solution Approach 2:
The handheld device is designed with multi-functionality, where a single unit performs scanning, visual capture, depth measurement, and data processing simultaneously. This universal design consolidates multiple functions that previously required separate devices, reducing system size and complexity while preserving vision sensing accuracy.
3Measurement precision
If conventional sensors are used, then scanning is provided, but the system is not accurate within confined spaces and requires external positioning infrastructure
Solution Approach 1:
The patent implements self-service localization by using the IMU to track device motion and the laser radar to detect features on the object surface independently. The system fuses this self-generated data to achieve accurate localization without requiring external positioning infrastructure, enabling autonomous operation in confined spaces.
Solution Approach 2:
The patent employs feedback mechanisms where the IMU continuously provides motion information that is fed back to the processor for real-time pose estimation. This feedback loop enables the system to maintain accurate localization in confined spaces by continuously adjusting its position understanding based on actual device motion, without external infrastructure.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The device achieves high-accuracy scanning and reconstruction in confined spaces without external positioning aids, utilizing a compact design and integrated processing for efficient data capture and alignment.
Implementation Method 1
a laser pattern generator arranged within the housing; capture depth data with the laser pattern generator as the user moves the housing
Implementation Method 2
a camera arranged within the housing and having a field of view; capture visual data from the field of view with the camera as the user moves the housing
Data Source
AI summary
Provided is a vision sensing device including a housing, a camera, a laser pattern generator, an inertial measurement unit, and at least one processor configured to project a laser pattern within the field of view of the camera, capture inertial data from the inertial measurement unit as a user moves the housing, capture visual data from the field of view with the camera as the user moves the housing, capture depth data with the laser pattern generator as the user moves the housing, and generate an RGB-D point cloud based on the visual data, the inertial data, and the depth data.