ROBOTICS & AI
INTELLIGENCE AT THE EDGE. ACTION IN THE PHYSICAL WORLD.
Perception, decision support and control, engineered together with the sensors, motors and enclosures that turn intent into physical action.
01EMBEDDED & ROBOTIC SYSTEMS
Discipline
Robotic system design
Discipline
Firmware
Discipline
Microcontrollers
Discipline
Real-time operating systems
Discipline
Sensor integration
Discipline
Real-time processing
Discipline
Navigation
Discipline
Control
Discipline
Simulation
Discipline
Testing
Discipline
Optimization
Discipline
System safety
02AI & MACHINE LEARNING
Perception to action on platforms including NVIDIA Jetson Nano and Jetson Orin-class hardware.
Capability
Computer Vision
Capability
Detection
Capability
Tracking
Capability
Classification
Capability
Predictive Maintenance
Capability
Anomaly Detection
Capability
Adaptive Systems
Capability
Reinforcement Learning
Capability
Data Collection
Capability
Model Training
Capability
Model Optimization
Capability
Edge Inference
03INDUSTRIES
Where embedded intelligence meets physical systems.
Autonomous vehiclesAgricultureManufacturingAerospaceDefenceInspectionAssemblyAssistive robotics
FIELD AUTONOMY
AUTONOMY THAT SURVIVES CONTACT WITH TERRAIN.
Perception, localisation and control are validated on real platforms in real conditions, not only in simulation.
FIELD TRIALS
SIM-TO-REAL
SAFETY CASES
EDGE COMPUTE
04EDGE COMPUTE
Inference next to the sensor.
Running perception on the platform keeps latency bounded and reduces dependence on links that may be degraded or contested.
Latency
Bounded, local
Power
Budgeted per platform
Thermal
Conduction-cooled
Models
Quantised for edge
05PLATFORMS
Hardware, perception and control in one program.
Ground platforms
Traction, suspension and navigation for uneven terrain.
Manipulation
Actuation and control for inspection and assembly tasks.
Perception stacks
Camera, depth and inertial fusion running on-platform.
PLATFORMS & EDGE COMPUTE
Hardware we build on,
