The Crawler

ONE SYSTEM.
TOTAL
VISIBILITY.

AX-1 — the first autonomous inspection crawler purpose-built for insulated cast iron pipelines in oil & gas and industrial environments.

AX-1

AX-1 Crawler

Autonomous Pipeline Inspection Platform

The AX-1 is a ruggedised 4WD autonomous crawler designed to traverse DN100 cast iron pipelines under live operating conditions. Spring-loaded wheel assemblies provide constant gripping force through aluminium cladding on inclines up to 30° and full vertical risers. The articulated chassis hinge enables navigation through 90° and 45° elbows without requiring pipeline shutdown or insulation removal.

Target Pipe
DN100 Cast Iron (4")
Drive System
4WD Spring-loaded wheels
Max Incline
30° continuous
Vertical Capability
1 m vertical riser
Bend Traversal
90° + 45° elbows
Battery Life
~3.5 hours continuous
Compute
NVIDIA Jetson Orin NX 8GB
Storage
Dual 512 GB industrial microSD (mirrored)
Odometry
Quad encoders + MPU-9250 IMU
Position Accuracy
Sub-centimetre (RFID + dead reckoning)
RFID Resets
At every pipe joint
Communication
Wi-Fi offload post-run
No Pipeline Shutdown Inspects Through Insulation Zero Insulation Removal
SEN

Trimodal Sensor Head

Visual · Thermal · Acoustic — Simultaneous

The sensor head mounts directly to the AX-1 chassis and captures all three modalities simultaneously — visual, thermal, and acoustic — feeding independent AI modules running in parallel on the Jetson Orin NX. Every sensor reading is stamped with Segment ID and precise pipe distance for full spatial traceability.

Visual
4K 360° ring camera array
AI Model — Visual
CNN crack / corrosion detection
Thermal Sensor
LWIR uncooled microbolometer
Thermal Spectrum
8–14 μm
Thermal Sensitivity
≥1°C differential
AI Model — Thermal
Statistical anomaly engine
Acoustic Mode 1
40 kHz AE — crack / leak TDOA
Acoustic Mode 2
Pulse-echo UT thickness gauging
Wall Thickness Resolution
±0.1 mm
AI Model — Acoustic
FFT + LSTM classifier
Fusion Engine
Bayesian multi-modal cross-validation
Inference Speed
>5 FPS per modality
SFT

Cloud Platform

Dashboard · Reports · Digital Twin · CMMS Integration

The platform handles everything from raw sensor data to boardroom-ready inspection reports. Upload completes in under 30 minutes. Every pipe segment builds a living digital twin — tracking material grade, operating conditions, defect history, and remaining-useful-life estimates across all inspection runs.

Cloud Storage
AWS S3 / Azure Blob
Offload Time
<30 min for 3.5 hr session
Reports
Auto PDF — defect table + images + repair priority
Integrations
CMMS / ERP work order triggers
Digital Twin
Per-segment asset database
Predictive
RUL modelling + failure probability forecasting
Middleware
ROS 2 Humble
Licensing
SaaS subscription or on-premise deployment

Open-Source Software Stack

Tool Purpose
ROS 2 HumbleRobot middleware, sensor topic bus
OpenCV 4.xVisual crack and corrosion detection
PyTorch / TensorRTCNN vision model + Jetson inference
Mosquitto MQTTLightweight sensor data broker
Node-REDCloud pipeline and dashboard wiring
Gazebo HarmonicDigital twin physics simulation
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