Current AI systems in spacecraft demand significant power and computational resources, posing a challenge for autonomous operations, especially in power-constrained environments. Traditional computing architectures are approaching their physical limits, hindering further improvements in power efficiency and performance for space navigation and situational awareness.

Neurobus develops neuromorphic computing solutions designed to enhance the power efficiency, throughput, and performance of AI in spacecraft. Inspired by biological systems, their technology utilizes neuromorphic sensors, algorithms, and hardware to process information in a manner similar to the retina and brain. This approach enables real-time data processing for autonomous systems, addressing the limitations of conventional computer architectures in space applications. Neurobus' solutions facilitate efficient space navigation, in-orbit services, and space situational awareness.

Neuromorphic sensors for efficient data acquisition and processing.

Algorithms inspired by biological neural networks for enhanced pattern recognition.

Low-latency systems for accurate tracking and docking in orbit.

Real-time space navigation using star and landmark tracking.

Space Situational Awareness (SSA) solution for real-time detection, tracking, and identification at low power.

The primary target audience includes aerospace and defense organizations, particularly those involved in space exploration, satellite operations, and autonomous systems development.