Reliable in Feature-Poor Spaces
Deep INS + SLAM fusion delivers stable tracking in long corridors, multi-floor stairwells, and other low-feature environments where pure SLAM systems drift or fail.
The CHCNAV RS7 is a tool-grade handheld LiDAR SLAM scanner for fast 3D capture where GNSS doesn't work — buildings, corridors, stairwells, tunnels, and underground infrastructure.
A tactical-grade IMU (0.5°/h bias instability) paired with CHCNAV's third-generation NIC-SLAM algorithm keeps tracking stable in long corridors and multi-floor staircases where typical handhelds drift. At 1.2 kg, it's walk-and-scan simple — no tripods, no targets, no aiming.
LAS/LAZ point clouds · OSGB/OBJ mesh · 3D Gaussian Splatting (PLY) · CAD/BIM deliverables
Architectural surveying, BIM and as-built documentation, interior renovation, public safety and forensics, heritage preservation, underground and tunnel mapping, parking structures, industrial facilities, digital twin creation.
Available from Latnet Technologies Ltd. — Authorized CHCNAV dealer in Canada with local support, training, and rentals.
The CHCNAV RS7 is a tool-grade handheld LiDAR SLAM scanner built for fast, reliable 3D capture in buildings, corridors, stairwells, tunnels, and underground infrastructure where GNSS is unavailable.
It fuses a tactical-grade IMU with 0.5°/h bias instability with CHCNAV’s third-generation NIC-SLAM algorithm for stable motion tracking even in feature-poor environments such as long corridors and multi-level staircases.
With up to 1.15 million points per second, an ultra-wide 360° × 189° field of view, dual 12 MP HD cameras, and a unified device-to-cloud workflow via CHCNAV CoCloud, the RS7 makes professional 3D capture genuinely walk-and-scan simple.
RS7 is built for surveyors, BIM specialists, public safety teams, and heritage professionals who need dense, colorized 3D data fast — without tripods, targets, or complex setup. Walk through the space and capture it in minutes.
Most handheld SLAM scanners struggle in three places: feature-poor corridors where the device drifts, fine indoor details that come out blurred, and dim spaces like underground parking where images go dark. RS7 was designed specifically to fix those three problems.
A tactical-grade IMU keeps SLAM stable when geometry runs out. A new-generation LiDAR with 6× the point density of typical handhelds preserves fine detail at walking speed. And Sony binning technology in the dual 12 MP cameras keeps imagery sharp in low light.
RS7 delivers practical field benefits for architects, surveyors, BIM teams, public safety units, and digital twin specialists working in real, complex indoor environments.
Deep INS + SLAM fusion delivers stable tracking in long corridors, multi-floor stairwells, and other low-feature environments where pure SLAM systems drift or fail.
No aiming, no stopping, no manual angle adjustments. The 360° × 189° ultra-wide FOV captures ceilings, floors, and corners in a single walk-through.
1.15 million points per second produces 6× the density of older handhelds at the same walking speed, preserving fine geometry, edges, and texture detail.
Dual 12 MP HD cameras with Sony binning technology produce clearer colorized point clouds in underground parking, basements, and other dim interior spaces.
Upload field data with a single click via CoCloud. Processing runs automatically. No workstation, no software install — just a phone.
Open SDK, 100 Mbps Ethernet, MAVLink, and ROS support let you integrate RS7 into robot dogs, mobile mapping platforms, and custom automation workflows.
RS7 ships with a tactical-grade INS that delivers 20× better gyro bias stability and 150× better accelerometer bias stability than typical consumer-grade IMUs found in entry-level handhelds. In pure-INS testing, trajectory stays within 1 cm over one minute while consumer-grade drifts more than 10 cm.
CHCNAV’s third-generation NIC-SLAM (Navigation-grade INS Core SLAM) algorithm deeply fuses low-frequency, high-precision SLAM poses with high-rate INS attitude data, with mutual correction running continuously. The result: complete, undistorted scans of multi-floor corridors and ultra-high stairwells with no overlap inconsistency.
The new-generation LiDAR captures up to 1.15 million points per second across 64 channels — six times the point density of typical 200,000 pts/s handhelds at the same walking speed. Fine objects, surface textures, and edge details that previously came out blurred are now resolved cleanly.
The ultra-wide 360° × 189° field of view covers everything around and above you in a single pass — a 60% larger vertical FOV than legacy 60° designs. No more blind zones above the device, no need to tilt or aim.
High density also pays off downstream: dense point clouds enable over 95% automated feature extraction accuracy in processing software, dramatically reducing manual cleanup time.
Two 12 MP HD cameras with Sony binning technology deliver noticeably sharper imagery in low-light conditions — underground parking garages, basements, and unlit interior spaces where typical handhelds produce noisy, muddy colorization.
CHCNAV’s proprietary ISP optimization improves HPC HD colorization with a 40% improvement in color saturation and higher-accuracy mesh modeling. The result is reality-grade textures suitable for client deliverables and digital twins.
For the next level of visual fidelity, the CHCNAV HPGS 2.0 engine generates 3D Gaussian Splatting models directly from your RS7 capture — combining photoreal visual quality with precise geometric detail for VR, marketing, and immersive documentation.
RS7 features a fully open hardware platform with base-mounted expansion, a 100 Mbps Ethernet port, and an open SDK. Real-time control and data transmission run over MAVLink and ROS protocols, making the unit ready for unmanned and automated deployments — including robot dogs and indoor mobile platforms.
Two power supply options support different deployment modes: an XT30 interface for stable long-term unmanned operation, and a USB Type-C input for rapid functional testing with a standard power bank.
RS7 is suited to professional indoor and underground 3D capture workflows where speed, portability, and reliable performance in feature-poor spaces matter.
As-built documentation, BIM data capture, facility scans, and renovation planning for residential, commercial, and industrial buildings.
Fast room and floor capture for layout planning, area and volume calculations, and accurate measurements without measuring tape or tripods.
Rapid 3D documentation of crime scenes, accident reconstruction sites, and incident locations for evidence, reporting, and courtroom presentation.
High-fidelity scans of historic interiors, museums, and cultural sites for preservation records, digital archives, and immersive 3D experiences.
Reliable capture in underground parking, basements, utility tunnels, and other GNSS-denied environments where INS-driven SLAM stability is essential.
Plant walkdowns, equipment documentation, and process facility scans for maintenance, retrofits, and digital twin development.
Multi-level parking garage capture for inspection, space analysis, and infrastructure management in challenging low-light environments.
Point clouds, mesh models, and 3D Gaussian Splatting outputs ready for digital twin platforms, VR walkthroughs, and immersive client presentations.
RS7 ships as a fully integrated hardware and software ecosystem. Field, cloud, and office tools are designed to work together so you can move from raw scan to finished deliverable without juggling multiple platforms.
One device. One workflow. From scan to final output — efficiently and seamlessly.
Latnet Technologies is an authorized CHCNAV dealer in Canada, providing local support, training, rentals, and workflow guidance for the RS7 and the wider CHCNAV LiDAR ecosystem.
The CHCNAV RS7 is a high-performance handheld SLAM LiDAR system built for fast and precise 3D data capture in indoor and underground environments.
By combining high-rate LiDAR with advanced INS and SLAM fusion, RS7 delivers accurate and reliable mapping.
Ideal for buildings, industrial facilities, tunnels, and complex infrastructure environments.