This technology is a neuromorphic processing system with architecture optimized for computationally-intensive autonomous navigation applications.
Autonomous vehicles require computationally-demanding processing that needs to be performed in a reliable and swift fashion. A local system performing the processing would satisfy both of these criteria; however, currently available processors are not well-suited for the computationally intensive nature of autonomous navigation. This has resulted in heavy reliance on cloud infrastructure for processing, which presents performance issues such as bandwidth and communication bottlenecks, as well as security issues such as susceptibility to man-in-the-middle type attacks.
Neuromorphic computing systems have shown promise in efficiently computing highly unstructured streaming data, such as the visual and audio data a self-driving car needs to process. This technology is a neuromorphic processing system that is optimized for computationally-intensive autonomous robotics applications and describes a custom-designed architecture that is optimized to process data collected by an autonomous guidance system. Using a cognitive processing approach, this system allows for local, reliable, real-time processing for autonomic guidance.
Eren Kursun, Ph.D.
Patent Pending
IR CU17298
Licensing Contact: Richard Nguyen