Our Mission
To demonstrate how spacecraft can leverage environmental randomness to execute evolutionary, learning-based algorithms in orbit while improving performance and reducing energy consumption.
What We Do
- Develop and validate small satellite technology
- Design and build evolutionary computing payloads
- Execute genetic algorithms that leverage radiation-induced variability within memory hardware
- Measure how radiation-driven mutation impacts adaptive performance in orbit
- Train engineers through hands-on mission development
Why it Matters
Most spacecraft rely on fixed, prewritten software designed to minimize environmental uncertainty, often requiring continuous error detection and correction to maintain reliability. DoomSat applies a different approach: using the space radiation environment as a computational resource.
By leveraging radiation-induced variability as a natural source of mutation, Genetic Algorithms reduce reliance on energy-intensive correction processes while continuing to improve performance over time.
This approach enables more energy-efficient onboard computing so spacecraft can adapt, optimize, and operate by incorporating the environment itself into the system, which has implications for long-duration and deep space missions where power is limited and autonomous adaptation is critical.
- Demonstrate evolutionary computation in orbit
- Measure adaptation driven by radiation-induced memory variation
- Validate autonomous onboard performance improvement without continuous ground intervention
- Establish a repeatable benchmark for adaptive computing in space
- Advance spacecraft computing architectures for future missions