Dense Point Cloud Alignment Across Multiple Scan Orbits

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Solution Overview

Problem

Existing methods for aligning dense point clouds (DPCs) from different orbits around a physical object are prone to errors, require manual intervention, and result in misalignment or loss of detail, making them tedious, expensive, and potentially dangerous.

Innovation Solution

A method and device for aligning DPCs that selects a first and second reference DPC, individually aligning others with each, using an iterative closest point (ICP) algorithm and noise removal, to generate a composite DPC with high resolution and accuracy without manual interaction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If a single DPC is generated directly from all images captured during all orbits, then the process is simplified, but some images may be skipped leading to lost details and reduced measurement precision

Engineering Contradiction:

ImproveProcess simplicityVSAvoidDetail completeness

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent segments the image processing into multiple orbits, generating one DPC per orbit separately. This allows each orbit's images to be processed independently with proper feature matching, ensuring no details are lost while maintaining process organization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent adds the orbit dimension to the processing workflow, treating each orbit as a separate processing unit. This dimensional approach allows systematic handling of images from different orbital paths, ensuring comprehensive coverage without skipping images.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Measurement precision

If one DPC is generated from images of each orbit, then detail completeness is improved, but the DPCs from different orbits may not be fully aligned resulting in misalignment

Engineering Contradiction:

ImproveDetail completenessVSAvoidAlignment accuracy

Core Design Contradiction:

Measurement precisionVSManufacturing precision

Solution Approach 1:

The patent performs preliminary alignment by selecting a reference DPC (from a specified orbit) and aligning all other orbit DPCs to this reference before feature extraction. This preliminary alignment ensures consistent spatial relationships across all orbits.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The reference DPC acts as an intermediary that mediates the alignment between all other orbit DPCs. By using this common reference frame, the patent ensures all DPCs are coordinated in a consistent spatial relationship.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Manufacturing precision

If point cloud alignment algorithm is applied to transform DPCs to correct positions, then alignment is achieved, but the algorithm is error-prone resulting in false positive matches and misalignment requiring manual adjustment

Engineering Contradiction:

ImproveAlignment accuracyVSAvoidAlgorithm accuracy

Core Design Contradiction:

Manufacturing precisionVSReliability

Solution Approach 1:

The patent performs preliminary noise removal from all DPCs before alignment operations. This preprocessing step eliminates erroneous data points that could cause false matches, improving the reliability of subsequent alignment algorithms.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent uses alignment metrics to evaluate the quality of alignment between DPCs. This feedback mechanism allows automatic assessment of alignment success, reducing the need for manual adjustment while ensuring high accuracy.

Inventive Principle:

Principle #23Feedback

4Manufacturing precision

If alignment is based on identifying a region of interest (ROI) in the physical object, then alignment can be performed, but manual identification of ROI is time consuming and error-prone

Engineering Contradiction:

ImproveAlignment capabilityVSAvoidManual processing time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent enables the system to automatically identify and use features from different orbits as alignment references without manual ROI specification. The algorithm autonomously selects appropriate features for alignment, eliminating manual intervention while maintaining accuracy.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12567160B2Alignment of dense point clouds of a physical object

Publication Date: 2026.03.03 TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)

AI summary

There is provided mechanisms for aligning different DPCs of a physical object. A method is performed by an image processing device. The method comprises obtaining DPCs captured from different orbits around the physical object. The method comprises aligning the DPCs with each other. The method comprises selecting, in a first stage, a first DPC of the DPCs as a first reference DPC and individually aligning all remaining DPCs with the first reference DPC, resulting in a first alignment of the DPCs. The first alignment of the DPCs yields a first value of an alignment metric per each of the DPCs except the first DPC. The method comprises selecting, in a second stage, a second DPC of the DPCs as a second reference DPC and individually aligning all remaining DPCs, except the first DPC, with the second reference DPC, resulting in a second alignment of the DPCs. The second alignment of the DPCs yields a second value of the alignment metric per each of the DPCs except the first DPC and the second DPC. The method comprises selecting, for each of the DPCs except the first DPC and the second DPC, that of the first alignment of the DPCs and the second alignment of the DPCs yielding best value of the alignment metric.