Redefining sensing for robotics and self-driving vehicles
Delivering trustworthy Perception to machines
Our Perception sensors capture rich and highly accurate spatial data, enabling machines to see and understand the world around them, enhancing safety and productivity.
Defence
Transport
Mining
Agriculture
Perception Delivers
Vehicle Autonomy
Real-time location determination
On and off-road operation
Autonomous navigation
Contested Operation
GPS denied or contested environments
Passive sensing — does not emit signals
Path Analysis
Identifies trajectories and velocities of objects
Establish clear paths in the desired route ahead
Increased Safety
See in all weather and lighting conditions: rain, fog, dust, smoke, night and day
All terrain collision avoidance
Simplifying Autonomy
Driven by PandionTM optical sensing, Perception solves a critical part of the automation stack for robotics, advanced driver-assist, and self-driving vehicles — efficiently generating the low-latency spatial data that every autonomous system needs.
Perception is powering the shift to full autonomy with:
Higher Fidelity 3D Spatial Perception
Visionary Machines Perception is powered by our Pandion™ spatial awareness technology, that views and constructs in real-time a high fidelity 3D image of the surrounding environment
Safer Autonomy
The rich 3D data captured empowers vehicle autonomy, terrain analysis and more accurate and robust obstacle detection .
Perception sensing that doesn't need roads.
On and Off-Road
Perception does not rely on maps or road markings, it interprets unknown or rapidly changing environments in real-time, solving the need for assured navigation on and off road in complex and dynamic environments.
Operation in All-weather Conditions, Day and Night
Perception can see accurately in fog, dust, smoke, rain and complete darkness.
Real-time Mapping
Real-time localisation and mapping, live point cloud data is processed into a map in real-time.
Contact Us
To learn more about our advanced optical Perception sensing for auontomy