3D Scan Localization Using Feature Matching to Correct Drift
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Solution Overview
Problem
Conventional 3D scanners face challenges such as drift in measurement data, uncertainty in captured areas, and insufficient data overlap, which affect localization and tracking accuracy.
Innovation Solution
Utilizing a 3D laser scanner with integrated sensor fusion and simultaneous localization and mapping (SLAM) capabilities, along with a camera, to capture and refine 3D measurement data, overlay it with images/video, and enhance localization and tracking through augmented reality (AR) displays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional 3D scanning is used, then measurement data can be collected, but drift in measurement data occurs affecting localization accuracy
Solution Approach 1:
The system continuously compares scanned features with stored map features and uses the discrepancy information to correct drift in real-time, maintaining accurate localization despite measurement variations
Solution Approach 2:
The patent introduces map features as an intermediary reference system that mediates between the scanner and the environment, providing a stable reference framework for correcting drift and improving localization reliability
2Loss of information
If conventional 3D scanning is used, then environmental data can be captured, but uncertainty in captured areas exists
Solution Approach 1:
The system uses feedback from feature matching between scanned data and map data to identify and fill gaps in captured areas, continuously improving coverage information and reducing uncertainty about scanned regions
3Reliability
If conventional 3D scanning is used, then scan data can be collected, but insufficient data overlap occurs affecting tracking
Solution Approach 1:
The patent transitions from relying solely on spatial overlap of scan points to utilizing feature-space matching, where features are matched across different scans regardless of limited spatial overlap, effectively adding a feature-matching dimension to the tracking process
4Measurement precision
If beam steering mechanism with motors and encoders is used, then light beam can be directed accurately, but device complexity increases
Solution Approach 1:
The system uses optical copying through the beam steering mechanism to project light patterns onto the environment, creating simplified reference structures that reduce the need for complex mechanical positioning while maintaining measurement precision
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 solution provides improved localization and tracking by removing data drift, filling gaps in 3D measurement data, and visually indicating scan-point coverage, thereby enhancing the accuracy and completeness of environmental mapping.
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
Implementation Method 2
The beam steering mechanism includes a first motor that steers the beam of light about a first axis and a second motor that steers the beam of light about a second axis
Data Source
AI summary
An example method collects first data comprising first surface points within an environment by a sensor associated with a processing system. The method further determines an estimated position of the processing system by analyzing the first data using a simultaneous localization and mapping algorithm and identifies a first set of surface features from the first data. The method further collects second data comprising second surface points within the environment by a three-dimensional (3D) coordinate measuring device associated with the processing system and identifies a second set of surface features from the second data. The method further matches the first set of surface features to the second set of surface features and refines the estimated position of the processing system to generate a refined position of the processing system. The method further displays an augmented reality representation of the second data based at least in part on the refined position.