3D Scanner Registration via 2D Motion Data
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Solution Overview
Problem
Existing 3D laser scanners require manual registration steps that are time-consuming and often incomplete, leading to inefficiencies and additional costs, as well as challenges in accessing sites for re-scanning due to insufficient overlap and omitted sections in initial scans.
Innovation Solution
A method involving a 3D scanner and a 2D scanner mounted on a movable platform, where the 2D scanner collects data to determine translation and rotation values for automatic registration of 3D scans, allowing for accurate alignment and registration of scans taken from different positions without the need for manual target matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual registration procedures are used to align 3D scans from different positions, then registration accuracy can be achieved, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs automatic self-registration by using the 2D scanner to capture images during movement between 3D scan positions. The processor automatically identifies common features across multiple 2D images and calculates registration transformations without human intervention, making the system self-sufficient in the registration task.
Solution Approach 2:
The 2D scanner continuously captures images during the physical movement between scan positions, preparing registration data in advance. This preliminary capture of 2D images and automatic feature matching occurs before the actual 3D scan registration is needed, enabling faster final registration.
2Reliability
If manual registration is performed, then some level of alignment is achieved, but the registration is often incomplete and requires returning to the site for additional scans
Solution Approach 1:
The system uses 2D images captured during movement as feedback to verify and refine the registration between 3D scan positions. The processor continuously compares features across overlapping 2D images to validate that the calculated transformations correctly align the scan data, ensuring complete and accurate registration.
Solution Approach 2:
The 2D scanner acts as an intermediary device that bridges multiple 3D scan positions. By capturing images during transitions and providing additional geometric constraints, the 2D scanner enables more reliable registration and reduces the need for return visits to ensure complete coverage.
3Measurement precision
If a 3D scanner is used to capture comprehensive spatial data, then accurate 3D coordinates are obtained, but manual target matching and control network establishment are required
Solution Approach 1:
The system merges the 3D scanner with a 2D scanner into an integrated measurement system. The 2D scanner provides additional imaging capability that works together with the 3D scanning to automatically establish correspondences between positions, eliminating the need for separate manual target matching and control network procedures.
Solution Approach 2:
The system replaces manual mechanical procedures (physical target placement, manual coordinate measurement with total station) with automated optical-mechanical systems. The 2D scanner and processor automatically perform feature detection and transformation calculation, substituting human-operated mechanical registration methods with automated computational geometry.
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
This approach enables automatic and accurate registration of 3D scans, reducing the time and cost associated with manual processing and ensuring comprehensive data collection during initial scans, while allowing for on-site corrections and improved data quality.
Implementation Method 1
A TOF laser scanner is a scanner in which the distance to a target point is determined based on the speed of light in air between the scanner and a target point
Data Source
AI summary
A method for measuring and registering three-dimensional (3D) coordinates by measuring 3D coordinates with a 3D scanner in a first registration position, measuring two-dimensional (2D) coordinates with a 2D scanner while moving from the first registration position to a second registration position, measuring 3D coordinates with the 3D scanner at the second registration position, and determining a correspondence among targets in the first and second registration positions while moving between the second registration position and a third registration position.