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3D scanning system Trek
measurementlasermobile

3D scanning system
3D scanning system
3D scanning system
3D scanning system
3D scanning system
3D scanning system
3D scanning system
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Characteristics

Number of axes
3D
Applications
measurement
Configuration
mobile
Other characteristics
automated, robotic
Length

350 mm
(14 in)

Measuring distance

350 m
(1148'03" )

Description

In the past, the only way to use laser scanners for reality capture on a construction site was to assign a worker to the task. But today, you can send in the Boston Dynamics Spot Mobile Robot instead. Just walk Spot through the project once to record your scanning mission, and Spot can repeat it as needed for ongoing progress monitoring and quality checks. Spot works with any FARO FocusS Laser Scanner and relies on FARO Trek 3D Laser Scanning Integration to enable autonomous scanning. Business Value of FARO Trek Keep Teams Productive Autonomous scanning allows you to free up workers to perform other, more valuable tasks. Keep Owners, Developers and Tenants Informed Accurate as-builts keep stakeholders updated on progress and provide quality assurance throughout the project. Easily Compare Progressive Scans A quick scan comparison lets you identify areas of progress at a glance. Improve Construction Quality Discrepancies between design models and as-built conditions are easy to identify and make corrections. Ensure Proper Pay Proof of progress ensures accurate payment for work completed. Ensure Accuracy and Consistency Capture data at the same location every time. Trek Performance Autonomous Mobile Scanning Solution Enabled by Trek, the Boston Dynamics Spot Mobile Robot autonomously navigates busy and dynamic job sites, capturing highly accurate point clouds. The workflow leverages Spot’s Autowalk tablet software to record a mission path around the jobsite, designate scan locations and replay the mission as needed. Trek avoids new obstacles without direct human control and enables a repeatable, automated workflow for capturing spatially linked datasets over time.

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