VIS-Guided Measuring Device Positioning for Gap-Free Point Cloud Registration
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Solution Overview
Problem
Existing methods for surveying large or complex measurement surroundings with mobile measuring devices often require multiple deployments and post-processing to identify and rectify missing data, which can be time-consuming and impractical, especially when data must be kept on-site and cannot be easily optimized for efficient gap-free coverage.
Innovation Solution
A method utilizing a visual inertial system (VIS) to automatically capture and track object features during deployment changes, enabling real-time assessment of suitable positions for deploying a mobile measuring device, allowing for immediate identification of registration possibilities between point clouds, and guiding the user to optimal scanning paths using visual and inertial data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple deployments are performed to survey large or complex measurement surroundings, then complete data coverage is achieved, but time expenditure and complexity increase
Solution Approach 1:
The system continuously provides real-time feedback during deployment changes by comparing measurement surroundings and assessing registration possibilities. This allows operators to immediately know whether a deployment position will contribute useful data, enabling dynamic adjustment of the surveying plan to avoid unnecessary deployments while ensuring complete coverage.
Solution Approach 2:
The system performs preliminary assessment of suitable deployment positions by analyzing measurement surroundings and evaluating point cloud registration possibilities before the actual surveying deployment. This advance planning allows operators to select optimal positions that maximize data coverage efficiency from the outset.
2Reliability
If multiple deployments are performed to ensure gap-free surveying, then complete coverage is achieved, but the number of deployments increases
Solution Approach 1:
Real-time feedback on registration possibilities and coverage gaps enables operators to make informed decisions about deployment positioning. The system continuously monitors whether sufficient corresponding object features are visible to enable point cloud registration, allowing dynamic optimization of the deployment sequence to achieve gap-free coverage with minimal deployments.
Solution Approach 2:
The system dynamically adjusts the surveying plan based on real-time conditions and measurement results. By continuously evaluating the suitability of deployment positions and the potential for successful point cloud registration, the system adapts the surveying strategy to achieve complete coverage with the fewest necessary deployments.
3Measurement precision
If post-processing is used to identify missing data, then data quality is improved, but time and cost increase
Solution Approach 1:
The system provides real-time feedback during the surveying process about data coverage completeness and potential gaps, eliminating the need for time-consuming post-processing analysis. Operators can immediately identify and address any coverage issues while on-site, significantly reducing both time and costs associated with post-processing.
Solution Approach 2:
The system performs self-assessment of data coverage quality during the surveying process itself, automatically analyzing measurement surroundings and evaluating whether complete coverage has been achieved. This eliminates the need for separate post-processing quality control steps.
4Productivity
If optimal scanning paths are planned in advance, then surveying efficiency is improved, but planning complexity increases
Solution Approach 1:
The system performs preliminary assessment of suitable deployment positions and potential scanning paths by analyzing measurement surroundings and evaluating point cloud registration possibilities. This advance preparation provides operators with guidance on optimal deployment sequences without requiring complex manual path planning.
Solution Approach 2:
The system automatically generates and updates surveying path recommendations based on real-time analysis of measurement surroundings and coverage status. This self-service path planning eliminates the need for complex manual planning while maintaining high surveying efficiency.
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
Enables efficient, gap-free surveying with reduced deployments and time expenditure by providing real-time feedback on suitable scanning positions, optimizing the scanning path, and ensuring complete data capture without the need for costly rework.
Implementation Method 1
first and second measurement surroundings containing first and second object features are automatically optically captured at the first deployment and tracked using a visual inertial system (VIS)
Implementation Method 2
scanning devices such as laser scanners, which are embodied to record a very large number of object points in order thus to three-dimensionally map, e.g., building or workpiece surfaces in the form of point clouds
Data Source
Figure 1~2
Figure 3~4
Figure 5~6
AI summary
The present invention relates to a method for ascertaining a suitable deployment of a mobile measuring device (1) within measurement surroundings (3), wherein first and second measurement surroundings (5, 9) containing first and second object features (14, 15) are automatically optically captured (12) at the first deployment (4) and tracked using a visual inertial system (VIS) (6) and within the scope of changing the deployment. The first and second measurement surroundings (5, 9) are compared, wherein the comparison is based on searching for corresponding first and second object features (24) visible in a certain number and quality in the first and second measurement surroundings (5, 9), wherein this certain number and quality of corresponding features (24) is a criterion that a registration of the first and second point cloud is possible.