AI takes control in orbit, speeds ISS flying robot tasks by 60%

Stanford researchers have successfully demonstrated the first machine-learning-based control system operating aboard the International Space Station (ISS), enabling the free-flying Astrobee robot to navigate the station’s complex interior 50 to 60% faster than traditional methods. The AI system uses a trained model to provide an informed initial guess ("warm start") for motion planning, which is then refined through optimization while maintaining strict safety constraints. This approach addresses the challenges posed by the ISS’s dense, cluttered environment and the limited computational resources available on space hardware. Tested initially on a microgravity-simulating platform at NASA Ames and then on the ISS itself, the AI-powered system allowed astronauts to step back from direct control, with commands issued remotely from NASA’s Johnson Space Center. The success of these tests has elevated the technology to NASA’s Technology Readiness Level 5, indicating operational viability in space. Researchers emphasize that such autonomy will be critical for future space missions, especially as robots operate farther from Earth and require minimal