AR/VRVR TrainingIndustrial Simulation

ScannerVRLiDAR Training Simulator

Meta Quest VR application simulating professional LiDAR scanning workflows with target placement, dual-scan verification, real-time raycasting, and point-cloud generation in progressive warehouse environments.

ScannerVR — LiDAR Training Simulator: device mockup
Category
AR/VR
Built with
Unity 6, C# Scripting, XR Interaction Toolkit +8 more

ScannerVR is a production-ready VR training simulator for Meta Quest that authentically recreates industrial LiDAR scanning operations from target placement through point-cloud validation. Users physically grab retroreflective paper targets from supply tables and snap them to warehouse walls using XR Interaction Toolkit grab physics with visual outline feedback. The tripod-mounted virtual scanner performs industry-standard 360° rotational scans, executing thousands of Unity Job System batched raycasts to validate line-of-sight to minimum three targets per position. The complete professional workflow requires dual scans—First Scan establishes baseline geometry from initial position, Second Scan from relocated tripod confirms overlapping registration and geometric stability—before generating dense point clouds visualized as cyan particle systems. Three progressive difficulty levels introduce escalating obstructions (crates, pallets, barrels, forklifts, machinery) forcing strategic scanner positioning and target layout decisions. Comprehensive training analytics capture time-on-task, target consumption, scan coverage percentage, and export structured JSON session data to persistent storage. Production features include 48 configurable scan resolutions via dual sliders, spatial audio feedback throughout (scan initialization beeps, target placement clicks, success/error chimes), head-tracked pause menus, async scene transitions with progress visualization, URP baked lighting maintaining 72fps standalone performance, and complete onboarding covering locomotion, controller interactions, and scanning objectives.

Demo

See it in action

Highlights

What makes it work

  1. Authentic LiDAR workflow: physical target placement → dual-scan verification → point cloud generation

  2. Physics-driven target handling with wall-snapping and collision feedback

  3. Real-time 360° raycast scanning requiring 3 line-of-sight targets

  4. Progressive difficulty (3 levels) with industrial obstructions (crates, forklifts, barrels)

  5. 48 scan configurations via dual resolution/quality sliders

  6. Training analytics with JSON session export (time, coverage, targets used)

  7. Complete onboarding: locomotion tutorial → interaction tutorial → objectives

  8. Production audio: scanner beeps, placement sounds, success/error feedback

  9. Spatial pause menu, async scene loading, progress visualization

  10. URP optimized for 72fps Quest standalone performance

The challenge

The hard parts of building ScannerVR

7 problems we had to solve, from physics, 3D math, learning design and more.

  1. 01 / 07Physics

    Authentic LiDAR physics

    Replicating authentic LiDAR physics required implementing thousands of concurrent raycasts using Unity Job System while maintaining real-time feedback under Quest hardware constraints.

  2. 02 / 073D math

    Registration without false positives

    The dual-scan verification workflow demanded robust target registration algorithms that validated geometric consistency across scanner relocations without false positives.

  3. 03 / 07Learning design

    Guidance vs. discovery

    Balancing training guidance with discovery-based learning required carefully paced onboarding that taught locomotion, grabbing, scanning, and strategic decision-making without overwhelming VR newcomers.

  4. 04 / 07Performance

    Industrial detail, smooth frames

    Industrial environment fidelity vs. performance tradeoffs involved extensive LOD implementation, occlusion culling, and URP material optimization.

  5. 05 / 07UX design

    Readable UI inside VR

    Spatial UI legibility inside VR demanded multiple iterations on scale, contrast, and head-tracking behavior.

  6. 06 / 07Audio

    Audio in step with every scan

    Audio design synchronization across asynchronous scan operations, UI interactions, and spatialized environmental effects required precise event-driven architecture.

  7. 07 / 07Data

    Research-grade session data

    Session data integrity for research export needed bulletproof JSON serialization handling partial failures and edge cases gracefully.

  8. 7 of 7 solved

    Got a problem like these? We’d like to hear about it.

Screens

Inside ScannerVR

1 / 10

Built with

  • Unity 6
  • C# Scripting
  • XR Interaction Toolkit
  • Unity Job System (raycast batching)
  • Meta Quest 2/3/3S Optimization
  • URP (Universal Render Pipeline)
  • Particle System (laser effects)
  • TextMesh Pro (spatial UI)
  • Addressables (async loading)
  • Spatial Audio
  • Controller Haptics

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