01
Machine Learning
Models for perception, behaviour and decision support, chosen around the constraints of real embedded systems.
Technology / Systems
The systems behind the machines
Technology
We build the perception, control and embedded foundations that allow robots to sense their environment, make decisions and act.
Computer vision & perception
Turning the world into usable information.
Our perception stack is designed around cameras, depth and additional sensors to support object detection, face recognition, mapping and contextual scene understanding.
Object Detection
Face Recognition
SLAM & Mapping
Depth Perception
02
Motion Control
Precision S-curve trajectory generation, social gaze tracking, and active compliant touch interaction.
03
Sensor Fusion
Combining visual, inertial and ranging signals into coherent estimates of robot state and environment.
Engineering principle
Useful intelligence lives at the intersection of software, sensing and hardware.
That principle guides how we choose components, design architectures and validate prototypes.