5.1 Map Fusion Fundamentals

What Is Map Fusion

Map Fusion is a post-processing mode in LixelStudio v4.0 that combines multiple independent L2 Pro, K2, or K1 scan segments into a single unified point cloud dataset. Each segment is processed individually through SLAM optimization first, then the fusion algorithm aligns and merges them using shared spatial reference: either RTK coordinates, matching control point names, or both.

The reason Map Fusion exists is practical: a single SLAM session has limits. Battery life ends. RAM fills. A 20-floor building cannot be scanned in one unbroken session. Map Fusion is the mechanism that allows you to break a large project into manageable segments during collection and reassemble them into one coherent dataset in post-processing.

Map Fusion is not a stitching tool for overlapping redundant data. It is an alignment tool for sequential scan segments that together cover a complete site. The segments need to share spatial reference at their connection zones; that reference is what allows the algorithm to lock them together accurately.

When to Use It

Five situations make Map Fusion the correct approach rather than attempting a single long scan.

Projects Exceeding Battery Life

The L2 Pro, K2, and K1 each provide up to 90 minutes of scanning time per battery charge. Large facilities, warehouses, campuses, and multi-floor commercial buildings require more time than a single battery supports. Rather than scanning until the battery dies, plan segment breaks at logical transition points and execute Map Fusion to join them in post-processing.

Projects Exceeding RAM Capacity

LixelStudio holds the entire scan trajectory in memory during SLAM optimization. On a 64 GB machine, scans longer than approximately 30 minutes risk failure. On 128 GB, the ceiling is approximately 60 minutes. If your project scope exceeds your hardware, Map Fusion is the solution: process shorter segments that fit in RAM, then fuse the results.

Multi-Floor Buildings

Moving between floors on stairways creates SLAM stress: narrow geometry, repetitive structure, brief feature interruption. Breaking at floor transitions and using Map Fusion produces more reliable results than attempting to carry a single session through multiple stairways.

Long Linear Environments

Tunnels, mine galleries, and corridors exceeding 1,600 ft (500 m) are not suitable for a single Narrow Mode session. The correct approach is to break these into segments of 1,600 ft or less and use Map Fusion with relative control points to join them. Field execution for this scenario is covered in detail in the Field Collection section.

Recurring Scan Projects

Facilities that require periodic rescanning on a scheduled cycle (construction progress monitoring, facility management, asset tracking) use Map Fusion to merge new scan segments with existing baseline data. Only the changed zones need to be recaptured. The new segments are fused with the unchanged baseline through shared control points.

This scenario requires control point infrastructure to be planned into the baseline scan from day one. Control points cannot be added to a completed scan after the fact. If the baseline has no shared control points with the future rescan zones, fusion is not possible. See the Control Point Planning section in 5.2 Pre-Project Planning for permanent control point requirements.

Hard Limits

These are not recommendations. They are system constraints. Exceeding them causes fusion to fail or produce unusable output.

• Maximum 10 segments per fusion job
• Maximum 200 minutes total scan duration across all segments in a job
• Maximum 20 minutes per segment (target 12 to 15 for buffer)
• Minimum 50 ft (15 m) overlap between consecutive segments; plan 65 to 100 ft (20 to 30 m) to give yourself field adjustment room
• Minimum 1 shared control point per segment pair (Narrow Mode requires 2)
• Same device model per fusion job. L2 Pro, K2, and K1 cannot be mixed in a single fusion job

Connection Methods

Map Fusion uses one of three methods to establish alignment between segments. The method you use determines whether the fused output has global coordinates, relative coordinates, or no georeferencing at all. This decision must be made before collection begins; it cannot be applied retroactively.

The Four Valid Connection Patterns

Official documentation defines which configurations the fusion algorithm can resolve. Every segment must be linkable to at least one adjacent segment through one of these patterns.

1. All segments have RTK
2. No RTK: consecutive pairs share identically named control points
3. Segment 1 has RTK; segments 1 and 2 share control points; segments 2 and 3 share control points
4. Segments 1 and 2 have RTK; segments 2 and 3 share control points

A segment with no connection to its neighbors cannot be fused. This is a hard requirement, not a guideline.

What Comes Out

The output of a successful Map Fusion job is a single unified point cloud that spans all input segments. If any segment carried valid RTK, the output has global coordinates. If only control points were used, the output has relative coordinates: internally consistent geometry with no absolute position.

The fused result exports from LixelStudio v4.0 in E57, LAS/LAZ, RCP, or PLY format. The same export selection and quality considerations that apply to single-scan outputs apply here. Regardless of how many segments contributed, the final output is one dataset.

Processing time for Map Fusion is substantially longer than single-scan processing, and hardware requirements are higher. The next sections cover pre-project planning, field collection execution, and the full processing workflow.