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November 1, 2021

Oculli’s AI-Based Radar Software Improves Resolution of Autonomous Systems

Concept: American software startup Oculli has launched AI-based high-resolution radar systems for autonomous systems. The company aims to improve the spatial resolution of radar sensors by up to 100 fold.

Nature Disruption: Oculii’s Virtual Aperture Imaging software leverages AI to learn from the environment and adapt. It uses software intelligence to enhance sensitivity and resolution. The sensor keeps improving as the software gathers more data. The software scales with Moore’s law to provide a longer range and high resolution. Virtual Aperture Imaging software can run on any radar hardware platform to improve performance, offering a scalable perception solution for advanced driver assistance systems and autonomous systems. Precise angular formation enables smarter positioning and safer navigation. Oculii’s high-resolution cloud data can be integrated with other sensors such as LiDAR and cameras which helps to improve the performance of sensors in all weather conditions.

Outlook: Traditional commercial radars require more hardware antennas as the resolution depends on the number of antennas. An increase in hardware leads to high costs and growth in size. Oculii’s Virtual Aperture Imaging software helps automakers to reduce the cost by eliminating the need for hardware antennas. It has raised $55M in series B funding led by Conductive Ventures, Catapult Ventures and with participation from Susquehanna Investment Group, Taiwania Capital, PHI-Zoyi Capital, HELLA Ventures, VectoIQ, R7 Partners, Mesh Ventures, ACVC Partners, Signature Bank, and Schox Ventures. The Startup intends to use the proceeds to improve its technology to provide high resolution, longer range, and cheap sensors that will accelerate the autonomous future. General Motors has also invested in Oculii to use its software for enhancing capabilities in its hands-free advanced driver assistance system known as Super Cruise.

This article was originally published in

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