Deadline Date: September 09, 2026
The Technology Innovation Institute invites proposals for an innovative model that can process raw neuromorphic vision sensor (NVS) data from input to resident space objects (RSOs) detection, tracking, and visualization.
The challenge focuses on developing high-performance AI/ML algorithms and pipelines to process raw neuromorphic vision sensor (NVS) data for resident space object (RSO) detection, tracking, and visualization, achieving real-time RSO detection and tracking in noisy, low-light NVS data feeds, delivering real-time AI inference for efficient object detection and tracking, supporting broad compatibility with TII-provided NVS datasets across different neuromorphic sensor resolutions, and providing visualization tools for interpreting and presenting detection results.
Proposed solutions should enable detection of objects in noisy, low-light NVS data feeds, classification of space objects against background noise and artifacts, detection of RSOs across varying magnitude levels from dim to bright objects, compatibility with TII-provided datasets across different camera resolutions, and a real-time pipeline from raw NVS streams to RSO detection, tracking, and visualization.
The challenge aims to redefine how space is monitored by encouraging participants to develop innovative AI solutions capable of processing neuromorphic vision sensor data with greater speed and precision. The proposed solutions should strengthen real-time, autonomous Space Situational Awareness capabilities while improving satellite resilience and national space security.
The winning solution will receive funding of up to US$50,000. There will be one winner, and participants may also have the opportunity to collaborate with TII after the competition if mutually agreeable. The challenge is open to startups, researchers, students, and enterprises.
Participants are required to submit a five-page written proposal along with a technical package in the form of a Docker image. Submissions will be evaluated on technical innovation, detection accuracy using test data, real-time performance, documentation, visualization and reporting, and team competency and solution articulation.
For more information, visit TII.
