Things to keep in mind while scanning - Get excellent data to work - - PowerPoint PPT Presentation

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Things to keep in mind while scanning - Get excellent data to work - - PowerPoint PPT Presentation

Dec 31, 2023 134 likes •616 views

Things to keep in mind while scanning - Get excellent data to work with Richard Steffen Martin Graner CTO R&D Engineer Table of contents 1. Project planning 2. Scanning 3. Registration 2 Things to keep in mind - 2020 Table of

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Things to keep in mind while scanning

  • Get excellent data to work with

Richard Steffen CTO Martin Graner R&D Engineer

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Things to keep in mind - 2020

Table of contents

  • 1. Project planning
  • 2. Scanning
  • 3. Registration

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Things to keep in mind - 2020

Table of contents

  • 1. Project planning
  • a. Requirements
  • b. Time x money
  • c. Planning

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Things to keep in mind - 2020

What does the customer want / need:

  • Accuracy and point density
  • Point cloud for presentation
  • Processing for BIM / CAD

Project planning - Requirements

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Things to keep in mind - 2020

On accuracy:

  • Global vs local accuracy
  • Verification

Project planning - Requirements

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Things to keep in mind - 2020

One scan Project planning - Requirements Two scans

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Things to keep in mind - 2020

  • Scanning with / without colour
  • Resolution
  • Estimated Scan positions
  • Data accuracy - mandatory things to achieve it

Project planning - Time x money

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TODO: Übersichtstabelle mit Scanning zeiten je auflösung… https://docs.google.com/spreadsheets/d/1mJyidKomhSUzHRKro8PFIrJw-IO 1Gq7W9At6vDOW3q4/edit#gid=1535648332 Project planning - Time x money

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TODO: Übersichtstabelle mit Scanning zeiten je auflösung… https://docs.google.com/spreadsheets/d/1mJyidKomhSUzHRKro8PFIrJw-IO 1Gq7W9At6vDOW3q4/edit#gid=1535648332 Project planning - Time x money

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TODO: Übersichtstabelle mit Scanning zeiten je auflösung… https://docs.google.com/spreadsheets/d/1mJyidKomhSUzHRKro8PFIrJw-IO 1Gq7W9At6vDOW3q4/edit#gid=1535648332 Project planning - Time x money

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TODO: Übersichtstabelle mit Scanning zeiten je auflösung… https://docs.google.com/spreadsheets/d/1mJyidKomhSUzHRKro8PFIrJw-IO 1Gq7W9At6vDOW3q4/edit#gid=1535648332 Project planning - Time x money

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Project planning - Time x money

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Beam Divergence Spot Size Distance ----------------------------------------------- >

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Things to keep in mind - 2020

Project planning - Time x money

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Things to keep in mind - 2020

Project planning - Time x money

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Single Point Accuracy Distance ----------------------------------------------- > ςα ςd ςα = const (Faro 19 arcsec = 0.005°) ςd = const + ppm (Faro 1mm + 10 ppm)

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Project planning - Time x money

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Things to keep in mind - 2020

Why beam divergence and single point accuracy is important?

  • Beam divergence

○ Reflected waveform has multiple peaks in time diagramm ○ Usually mean will be computed (ghost points on edges)

  • Single point Accuracy

○ Should be considered in the adjustment ○ Should be considered in distance measurements

Project planning - Planning

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Things to keep in mind - 2020

  • Use existing Layout plan! (Scan position planning & field book)
  • Loop closures, feature placements
  • Geodetics
  • Use high standard spheres and checkerboard targets
  • Do a site inspection prior to scanning
  • On-site registration

Project planning - Planning

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Project planning - Planning

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Things to keep in mind - 2020

Table of contents

  • 1. Project planning
  • 2. Scanning
  • a. C2C vs feature based
  • b. Georeferencing
  • c. How to scan

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Things to keep in mind - 2020

Scanning - C2C vs feature based

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C2C Feature based Matching via:

  • Point to Point (ICP)
  • Point to Plane (ICP*)
  • Planes (patches)
  • Spheres
  • Checkerboard targets
  • Natural features

Limits:

  • No planes/normals in three axis

existing (e.g. long hallways)

  • Not enough features (<3)
  • Bad feature constellation

Gets time consuming when:

  • No approximation values (Creating

the connection graph) Manual Topview pre-alignment

  • Bad Automatic feature extraction
  • Getting wrong approximation

values Constellation search:

  • Scan to scan connections
  • Global Scan connections
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Things to keep in mind - 2020

  • Is it necessary?
  • Direct vs indirect
  • While registering vs after registration

Scanning - Georeferencing

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Things to keep in mind - 2020

  • Scan position connections
  • Loop closure
  • Feature distribution
  • How to scan through a door
  • Automatic sphere detection

Scanning - How to scan

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Things to keep in mind - 2020

Scanning - How to scan

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Scan: Scan connection

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Scanning - How to scan

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Scan: Scan connection

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Scanning - How to scan

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Loop closure Scan:

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Scanning - How to scan

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Loop closure Scan:

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Scanning - How to scan

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Feature distribution Feature: Scan:

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Scanning - How to scan

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The good Feature: Scan:

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Scanning - How to scan

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The bad Feature: Scan:

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Scanning - How to scan

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The ugly Feature: Scan:

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Scanning - How to scan

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The super bad luck

60° 60° 60°

Feature: Scan:

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Scanning - How to scan

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The super bad luck Feature: Scan:

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Scanning - How to scan

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The super bad luck Feature: Scan:

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Scanning - How to scan

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The super bad luck Feature: Scan:

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Scanning - How to scan

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Door scanning Configuration 1

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Scanning - How to scan

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Door scanning Configuration 2

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Scanning - How to scan

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Source: https://www.laserscanning-europe.com/en/news/use-laser-scanner-reference-spheres-optimal-distance-to-the-scanner

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Real life sphere detection in Faro Scene

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Things to keep in mind - 2020

Table of contents

  • 1. Project planning
  • 2. Scanning
  • 3. Registration
  • a. Feature based
  • b. Cloud to Cloud (C2C)

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The big challenge

  • Determine the connection graph

○ Which Scans are overlapped (adjacency matrix) ○ Which local features correspond to each other (constellation search)

  • Simplify automatic search algorithms

○ Complexity O (n2 / 2) ○ Clustering 20->100 Scans per cluster

Registration

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Things to keep in mind - 2020

  • Wording issues: “Bundle adjustment” - It’s Photogrammetry, not

scanning because of the 3D->2D Projection (bundle of rays)

  • Least squares adjustment -> Squared sum of the residuals (errors) will

be minimized Registration

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Feature based model

  • Each Scan depends on H (X, Y, Z, ⍵, φ, ϰ) - rigid motion
  • Model for point based features: Xw = Hw Xlocal

○ Xw Unknown 3D Position ○ Xlocal Measured local 3D Position

  • Georefernce Observation

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Xw = Xgeod

  • Inclinometer Observation

⍵ = ⍵inc , ϰ = ϰinc Registration - Feature based

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Global Adjustment - Feature Based

  • All “raw” observations with their accuracy introduced in one big

adjustment (usually sparse system)

  • All errors are distributed into the whole network
  • For all observation types a posteriori accuracy can be estimated
  • Full error analyze possible
  • Georeferencing included, reduce drift effect

Registration

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Things to keep in mind - 2020

“Two step” alignment - Used very often for Cloud2Cloud

  • 1. Step: Alignment of relative orientation between two scans

○ The model: X2 = ΔH12 X1 (Helmert transformation between 2 scans) ○ Cloud 2 Cloud use IPC to detemine ΔH12

  • 2. Step: Net adjustment of all relative orientations in a cluster or for

complete overlapping graph

○ The model: Hw2 = ΔH12 Hw1 (Relative orientation)

  • 3. Step: Cluster alignment (big residual stress on cluster bounds)
  • 4. Step: Georeferencing (big residual stress)

Registration - Cloud to Cloud

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Recommendations for the registration 1. Use Cloud2Cloud for small projects (20-50 scan) and no georeferencing 2. Use Feature based Registration for proof of result 3. Introduce high accuracy control points (GPS/Total station) for Georeferencing and drift compensation Registration - Cloud to Cloud

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