Nature thinks differently
Brains evolved to solve autonomy in the real world, by default. By using highly differentiated algorithms, they far exceed today’s engineered state-of-the-art (SoTA) approaches.
Opteran has patented these biological algorithms to make machine autonomy as robust and efficient as nature.
Solving vision and perception nature’s way
Opteran “sees” at low resolution, high frame rates stabilized to 3DoF rather than high resolution, low frame rates and 6DoF. As a result, they simplify how we understand motion and increase the robustness of sensor noise.
See in visually challenging environments.
Increase robustness with stabilization.
Significantly reduce compute and sensor cost.
Build robust maps dynamically as you move
Opteran creates robust navigation by adding diversity between understanding motion and position, resolving SLAM fragility, and allowing ultra-low memory maps to be built on the edge, at city scale without processing data or training.
Resolve SLAM single point of failure.
Ultra low-memory mapping.
GPS free navigation.
Detect collisions in the real-world at real-time
Opteran avoids collisions by responding dynamically to what it can see, eliminating the delay from managing occupancy maps with costly replanning.
See small static and dynamic objects.
Straight through processing.
Nature evolved to be low SWaP$ by default
Opteran algorithms evolved to enable insects to navigate so are innately edge only, small, lightweight and ultra-low powered. Allowing them to be deployed onto the low-end silicon e.g. CPU, FPGA to ASIC.
Lowest power consumption.
Low cost compute.