Hyperspec Perception Stack
Our Perception Stack is a collection of self-teaching machine learning models that are powered by accelerated edge computing. Hyperspec enables the vehicle to construct and contextualize the scene in real-time and self-localize without a reference map.
Patent-pending AI models that find features between aerial and terrestrial perspectives to determine the error in the vehicle’s positioning allowing localization without an HD map.
Replace map latency with a fast, edge computing stack and create boarder-less, ubiquitous autonomy without disengagements.
AI Training Tools
The Hyperspec Annotation Tools are highly scalable and versatile with uses from mapping to ground truthing.