LiDAR: surrounding geometry
Distance measurements describe the surfaces around the scanner. Coverage depends on the sensor’s field of view, range, and visibility of the target.
Multi-Sensor Fusion
Combine geometry, motion, and visual context.
LiDAR, cameras, and motion sensors contribute different information to a scanning workflow. Bringing these inputs together supports mapping and colorized outputs; the available sensors and processing depend on the scanner configuration.
Complementary inputs
Understand what each sensor contributes.
IMU: movement information
Inertial measurements describe motion during capture. They complement geometric observations in the supported mapping workflow.
Cameras: visual context
Images provide surface appearance for colorized outputs and visual review. Lighting, exposure, and visibility affect the quality of the captured imagery.
Positioning: an additional reference
Positioning data adds another input where the hardware and workflow support it. Cobra includes standard RTK; results depend on corrections and field conditions.
How it works
Bring the inputs into a processing workflow.
- 01
Record
Acquire the sensor observations available on the selected scanner.
- 02
Align
Relate observations in time and in the sensors’ coordinate frames.
- 03
Optimize
Refine the map and registration using the supported processing tools.
- 04
Colorize
Associate captured imagery with geometry for the final output.
This is a conceptual sequence. Timing, calibration, and optimization methods vary by product and software version.
In practice
Cobra hardware and MX-Fusion processing.
Cobra combines LiDAR, IMU, multi-view cameras, and standard RTK. Its MX-Fusion workflow includes alignment, registration, outlier removal, and color balancing to produce colorized point clouds.
Practical evaluation
Check how the inputs behave on your site.
- Review the camera conditions. Assess imagery in the expected lighting and around reflective or texture-poor surfaces.
- Plan movement and overlap. Use a route that keeps enough surrounding geometry visible across successive observations.
- Check positioning requirements. Confirm how corrections, reference coordinates, and coordinate transformations will be handled.
- Inspect the processed result. Look at alignment, coverage gaps, duplicated surfaces, and color consistency in representative areas.
Questions about sensor fusion
Does every ModeXion scanner include RTK?
Sensor configurations vary by model. Cobra S and Cobra X include standard RTK; confirm the hardware and positioning workflow for other products.
What is the relationship between sensor fusion and SLAM?
Fusion brings different sensor observations together; SLAM estimates movement while building a map. The two can work together in a mapping system. Explore LiDAR and SLAM →
Can I inspect a processed example?
The Cobra S Mid360 LAS sample lets you examine a supplied colorized point cloud. It is a processed example, rather than the full set of raw sensor inputs. Review the Cobra S sample →