Simultaneous Localization And Mapping (SLAM) has its roots in the robotics industry as a solution for the problem of “How do I get a robot to understand its location within an environment while it’s learning what that environment is?” While the methods involved can vary as greatly as human imagination, machine learning and computer vision can allow, it typically involves the analysis of data from inertial measurement units (IMUs) along with high-density laser measurement data (known as point clouds) and images in order to better refine the path that the instrument took during its operation, thus vastly improving the likelihood that the calculated path it took is the true path. This determination forms the spine of the resulting model with the onboard instruments and other analytical refinements forming the resulting model.

With the introduction of measurement control networks, refinement scans (scanning areas in ‘loops’ or closed, crossing geometric patterns) along with high precision lasers and high definition camera manufacturers, these models are only becoming faster and more accurate with each new generation of platform.

Depending on the type of work being carried out, these instruments are opening new avenues and possibilities for collaboration, awareness, preservation, analysis, digital planning and simulation, asset/site management, legal/situational documentation, and automation.

The growing industry of SLAM platforms is presenting itself as a direct solution to the issue of collecting data quickly, comprehensively, with sufficient accuracy and with minimal disruption to production or environment. Likewise, these and traditional 3D scanning collection methods are being made even more impactful through the application of computer learning and automated extraction methods, turning these instruments into invaluable analytical tools and the bedrock for a future that will demand a plethora of data, fast. However, there are as many different spatial tools as there are there are needs for spatial information! Which ones are right for the work you wish to pursue? This event aims to help answer that question.

As this scan-off is being hosted as a means to aid commercial and industrial data collection awareness and selection, only commercially available units are able to participate.

Due to this year’s event being in a public, populated area only commercially available hand-held or human-mounted SLAM units are encouraged to participate. Aerial and vehicle platforms will not be allowed to participate as these drones pose a potential danger and disruption to the public. Robot platforms may be considered provided they are escorted, equipped with high-visibility markings, are terrestrially bound and do not pose a potential danger or disruption to public activities and thoroughfares.

Dates of Event: November 3 to 5, 2023
Allotted time for collection: 1 hour
Approx (linear) distance to scan: 100 metres
Deadline to Apply: September 30, 2023
Time slots by availability on first come, first serve basis.
Deadline to Submit Data Deliverables: November 6 @ 13:00 MST
Participant Data Deliverables:

• Platform Data Sheet (pdf)
• Post-Processing Software data sheet (pdf, txt or html)
• Platform Operation Manual (pdf)
• Software Operation Manual (pdf, link sufficient)
• Price List – “Turn-key; ready to collect, process and present tomorrow” (pdf, Canadian Dollars)
• Post-Processing Report with positional confidence (pdf)
• Control point locations – Point, Northing, Easting, Elevation, description (csv)
• Georeferenced point cloud (las, laz or e57)
• Times required to:
  1 ) Scan the scene
  2) Post-process the scene into the extractable model

  Description of deliverables are in the participant package.