NavVis CLX handheld capture: practical implications for mine and plant teams
Reviewed by Joe Ashwell

First reported on Australian Mining
30 Second Briefing
NavVis has launched the NavVis CLX, an agile handheld reality capture device using dual LiDAR architecture to generate clean, low-noise point clouds for high-volume, day-to-day mine and plant documentation. Positioned to complement the backpack-style NavVis VLX and trolley-based NavVis MLX, the CLX is intended for frequent use by non-specialist staff, putting “professional reality capture in every hand”. For mining engineers and survey teams, this points to wider, lower-cost 3D documentation of underground drives, process plants and brownfield modifications without full survey campaigns.
Technical Brief
- Dual LiDAR architecture is configured to minimise occlusions and blind spots during rapid handheld sweeps.
- Sensor fusion onboard is tuned to output low-noise point clouds suitable for as-built modelling workflows.
- Device form factor is optimised for single-operator use in congested plant rooms and scaffolded areas.
- CLX data is designed to integrate with existing NavVis processing pipelines used for MLX and VLX datasets.
- Handheld configuration targets short mobilisation times, reducing setup compared with tripod or trolley-based scanners.
- System is positioned for repetitive documentation passes, supporting change detection in active construction or retrofit zones.
- Wider deployment to non-specialists implies revised QA workflows for scan coverage, registration accuracy and metadata management.
Our Take
For Australian projects, handheld capture like NavVis CLX typically reduces the need for repeat site access by design and engineering teams, which can materially cut travel and shutdown time compared with tripod-based scanning workflows.
NavVis already appears in our coverage via its MLX and VLX systems, and adding CLX suggests the company is trying to cover both high-throughput trolley or backpack mapping and lighter, task-based documentation, giving mine operators more flexibility in how they digitise workings and plants.
Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.
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