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Camera Modules for Drone and UAV Navigation

Reliable vision for drone navigation, enabling accurate positioning, obstacle avoidance, and real-time decision making with system-ready camera modules designed for fast integration.

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Camera Modules for Drone and UAV Navigation
UAV Navigation

Find the Right Camera Module for Autonomous Drone Navigation

Reliable navigation starts with consistent visual data. FSM:GO camera modules are system-ready imaging solutions for drone manufacturers and UAV system integrators who need predictable performance in real-world conditions, including GPS-denied environments.

Each module combines a validated sensor, matched optics, and optimized drivers to deliver stable image quality for positioning, obstacle avoidance, and real-time decision making.

To support accurate positioning, FSM:GO modules can be delivered with geometric calibration – correcting lens distortion and ensuring consistent camera geometry. This improves feature tracking and visual positioning accuracy while reducing system-level calibration effort.

For high-speed navigation, global shutter options like FSM:GO IMX900 eliminate motion distortion and support accurate feature tracking. Combined with strong low-light sensitivity, these modules maintain reliability across changing light conditions and dynamic flight scenarios.

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Shutter type matters

Why global shutter is required for reliable drone navigation

Reliable UAV navigation depends on fast, consistent image data across changing environments and flight conditions. FSM:GO camera modules provide optimized image pipelines, validated optics, and geometric calibration support to improve visual positioning, obstacle avoidance, and autonomous navigation performance.

Rolling Shutter - what SLAM receives
Problem
Each row captured at a different moment in time
Fast movement = feature positions shift between rows
SLAM algorithm receives geometrically inconsistent data
Position estimate wanders and jumps - waypoint precision suffers
Rolling shutter row desync causes measurable feature displacement. At cruise speed this reduces visual odometry precision. At fast or agile speeds the position estimate becomes too imprecise for tight clearances.
Global Shutter - what SLAM receives
Recommended
All rows captured simultaneously at t=0
Feature positions geometrically accurate across the full frame
SLAM algorithm works with consistent data every frame
Pose estimate matches true position - navigation stays on track
Drone position computed from geometrically consistent data. Reliable across hover, cruise, fast, and agile flight profiles.
Interactive simulation

GPS-Denied Navigation - Where Does Rolling Shutter Think You Are?

Rolling shutter can distort frame geometry during motion and vibration. In visual SLAM, those distorted feature measurements can increase drift, reduce trajectory stability, and in severe cases cause position jumps or re-localization errors.

RS position error 0.0 m
GS position error ~0 m
RS nav status -
GS nav status On track
Low vibration, clear sight lines. Rolling shutter adds small position noise - the estimate stays close to the true path, but waypoint precision is measurably reduced. Global shutter holds the reference track.
Technical detail - how sensor type affects precision
Interactive simulation

SLAM Visual Odometry - What the Algorithm Sees

This simulation shows what SLAM algorithms receive from each sensor type during drone flight. Rolling shutter readout skews scene geometry - vertical structures lean and feature positions shift, so the computed pose wanders around the true path. Global shutter delivers frame-consistent data, keeping the pose estimate on track.

Flight speed
Vibration
Rolling shutter - what SLAM sees Skew distortion
Vertical skew0px
Feature displacement0px
Frame quality-
Global shutter - what SLAM sees Stable frame
Vertical skew0px
Feature displacement0px
Frame qualityAccurate
Pose deviation - estimated path around true path Live chart
RS pose error0.00 m
GS pose error~0 m
Elapsed0.0 s
Nav precision-
System consequence: Select a flight speed and vibration level to see how sensor type affects SLAM positioning precision.
Low-light sensitivity

Navigation doesn't stop when the lights go out

Standard camera modules lose feature tracking reliability in low-light environments - underground, indoors, at dusk, or in tunnel inspection. High camera sensitivity extends the operational envelope without adding external lighting hardware.
01
Indoor & confined space flight

Warehouses, tunnels, building interiors. The FSM:GO IMX900's high sensitivity keeps feature detection working where ambient light is scarce.

02
Dusk / dawn operations

Light levels fall quickly at low sun angles. High sensitivity maintains reliable feature tracking through the full flight window without changing exposure parameters.

03
No added illumination

More usable scene detail at the same exposure settings - extends low-light operation without onboard lighting hardware, saving weight and power.

04
Multi-sensor fusion compatibility

Camera data fuses with depth sensors, IMU, and LiDAR for robust navigation pipelines that maintain localisation across lighting transitions.

Interactive simulation

Camera Sensitivity - Feature Detection in Low Light

Toggle between standard and enhanced camera sensitivity to see how feature point detection changes in a sub-1 lux scene - same exposure, no added illumination. In near-dark conditions, more usable features mean steadier visual odometry, stronger tracking, and more reliable navigation when light is limited.

Indoor corridor - sub-1 lux ambient - feature point detection
Scene lighting Near-dark (<1 lux)
Feature points -
Feature tracking -
GPS-denied operations

When the satellite link drops, visual navigation keeps flying

GPS denial can be environmental, regulatory, or adversarial. In each case the system must switch to optical localisation immediately. The quality of that transition depends entirely on the camera.

01 - Environmental

Urban & indoor operations

Building interiors, underground infrastructure, dense urban canyons, and parking structures all block or attenuate GPS signals. Visual navigation becomes the primary positioning system for the entire flight envelope.

02 - Regulatory

BVLOS in restricted airspace

Beyond-visual-line-of-sight operations in controlled environments increasingly require autonomous positioning independent of external infrastructure. Visual odometry combined with onboard mapping provides the required reliability without ground-based beacons.

03 - Adversarial

Jamming & spoofing resilience

Systems designed for regulated and sensitive environments require navigation that cannot be disrupted by RF interference. Optical visual positioning with a high-integrity camera module provides a layer of resilience that satellite-dependent systems cannot match.

In all three scenarios

In all three scenarios the system transitions to visual odometry. If that camera has rolling shutter, position estimates degrade under the exact flight conditions - speed, vibration, manoeuvring - where GPS-denied operations are most demanding. Global shutter removes that dependency on calm flight to maintain navigation accuracy.

The module

FSM:GO IMX900 - Navigation Camera Module

Recommended for UAV Navigation

Product image representative only

Sensor
Sony IMX900M/C - 3 MP Global Shutter
Pixel size
2.25 µm
Sensor format
1/3.1"
Standard lens
76° HFoV - Narrow
Interface
PixelMate™ (MIPI CSI-2)
NIR sensitivity
Improved
Shutter type
Global shutter
FSM:GO IMX900
System-ready global shutter module for GPS-denied autonomous flight

The FSM:GO IMX900 is built for drone manufacturers and UAV system integrators who require pixel-perfect navigation performance in real-world conditions. Global shutter eliminates motion distortion during rapid manoeuvres and high vibration – delivering geometrically consistent frames every shot.

Strong low-light sensitivity extends reliable operation into dusk, indoor, and tunnel environments. Based on FRAMOS’ FSM:GO platform, it integrates seamlessly with embedded AI compute platforms like NVIDIA Jetson or NXP i.MX, with open-source drivers available on GitHub.

Validated Platform Support
NVIDIA Jetson Orin / AGX / NX
NXP i.MX 8M / i.MX 93
Qualcomm RB5 / QCS
Raspberry Pi 5 / CM4
Distortion-free motion capture
No rolling-shutter artefacts during rapid manoeuvres or high vibration
Factory geometric calibration
Per-module calibration included - improves SLAM accuracy, reduces integration effort
Strong low-light sensitivity
Reliable feature tracking at dusk, indoors, and in tunnel environments
Open-source drivers & SDK
Optimised image pipelines and GitHub-hosted drivers for fast camera bring-up
Compact & lightweight
Designed for space-constrained UAV platforms without compromising performance
EU-built, regulated market ready
European manufacturing for deployment readiness in industrial and regulated environments
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Integration path

From evaluation kit to production deployment

FSM:GO IMX900 is available from Mouser Electronics for immediate evaluation – no account required, ships in standard electronics lead time. From there, FRAMOS engineering support covers everything from driver bring-up to geometric calibration to volume production.

1

Choose and order a camera module for evaluation

In stock, no account required. Ships in standard electronics lead time. Comes with lens fitted, connector ready.

2

Flash the open-source driver

GitHub-hosted drivers for Jetson, NXP, Qualcomm, and Raspberry Pi. Tested against reference configurations. No custom kernel patches required.

3

Validate in your navigation stack

Connect to your SLAM framework (ORB-SLAM3, OpenVINS, or custom). Use the included calibration parameters or request custom calibration from FRAMOS.

4

Request geometric calibration (optional)

FRAMOS offers per-module and stereo calibration services. Calibration data delivered in standard OpenCV and ROS-compatible formats.

5

Scale to production volumes

Request a Quote for volume pricing, custom lens configurations, mechanical integration support, and SLA documentation for regulated deployments.

Payload & FPV modules to complete your UAV system

The same FSM:GO platform extends across the full UAV mission - pair navigation with 4K payload imaging and ultra-wide FPV from a single validated ecosystem.

UAV Payload

FSM:UAV-PAY - Payload Camera Module

High-resolution 4K imaging for inspection, mapping, and precision agriculture. Built on the IMX678 with STARVIS 2 low-light performance.

View module
UAV FPV

FSM:UAV-FPV - First-Person View Camera Module

Ultra-wide 185° field of view for real-time pilot awareness, tight-space flight, and obstacle-rich environments.

View module

Ready to integrate?

Talk to our UAV vision engineers. Discuss your platform, flight profile, and integration requirements - we'll help you validate the module for your navigation stack.

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