Manifold Tech
MindCloud Studio

MindCloud Studio

MindCloud Studio is a professional 3D point cloud processing software independently developed by Manifold Tech Ltd., compatible with all of the company's scanner devices. Specifically designed for handling .lx point clouds and .olx files generated by Manifold Tech's products, it accurately analyzes the data, fully unlocks its value, and lays a solid foundation for subsequent data processing.

Recently Updated

  1. Multi-flight Stitching Supports joint optimization and automatic stitching of multiple consecutive scanning projects. The software intelligently identifies scan sequences and performs unified optimization, significantly improving mapping efficiency, stitching accuracy, and global consistency for large-scale environments.
  2. Enhanced Measurement Tools Expanded point cloud measurement capabilities with polyline length, polygon area measurement, and result export. The enhanced tools improve efficiency for engineering surveys, BIM verification, quantity calculation, and geometric analysis.
  3. Image Fusion Introduced Image Fusion to spatially integrate high-resolution photographs and panoramic images with point clouds, enabling synchronized visualization of 2D imagery and 3D geometry for improved scene interpretation.
  4. RTK Coordinate System Optimization Optimized the RTK coordinate transformation workflow by improving coordinate reference system matching, resolving abnormal coordinate offsets, and enhancing transformation accuracy and positioning stability across different coordinate systems.
  5. Loop Closure Optimization Enhanced the SLAM Loop Closure algorithm to improve repeated-scene recognition, reduce accumulated drift, wall layering, and ghosting artifacts, resulting in greater mapping accuracy and overall reconstruction consistency.
  6. Relocalization Map Optimization Improved the relocalization map generation pipeline by enhancing navigation map completeness, localization accuracy, and long-term stability, providing more reliable positioning for autonomous robotic applications.
  7. Point Cloud Quality Enhancement Optimized the point cloud reconstruction pipeline to reduce noise and point cloud thickness while improving edge continuity and normal estimation, delivering higher geometric accuracy, better detail preservation, and superior modeling quality.

Key Features

Documentation Manual

Video Tutorial