USC MAVERIC Satellite to Launch on SpaceX Mission to Test Autonomous Space Technologies

A student-built nanosatellite from the University of Southern California is scheduled to launch in July aboard a SpaceX Falcon 9 rideshare mission to evaluate next-generation autonomous spacecraft capabilities. The 3U CubeSat, known as MAVERIC, will test advanced 2D and 3D imaging systems designed to support future on-orbit satellite servicing, including inspection and repair operations. This mission represents a significant step in integrating artificial intelligence and low-cost sensing into the space technology sector, potentially reducing the cost and complexity of future orbital maneuvers.

Developed by the USC Space Engineering Research Center with contributions from over 60 students and faculty, the MAVERIC satellite is a shoebox-sized 3U CubeSat designed to advance the field of autonomous space operations. The mission, funded by a gift from Positron Capital Management, focuses on imaging methods critical for on-orbit servicing—an emerging sector where spacecraft approach others for maintenance, refueling, or repair. David Barnhart, director of the USC Space Engineering Research Center, emphasized that the mission aims to provide human operators with better situational awareness and the ability to intervene in autonomous close-proximity operations, thereby building trust in intelligent systems.

A key technical objective of the mission is the demonstration of 3D imaging using dual cameras to provide dynamic visualization for operators during complex orbital maneuvers. This imaging hardware will also support an industry partnership with Planetary Systems AI, which is conducting its first on-orbit demonstration of AI-powered decision-support software. According to Planetary Systems AI CEO Cindy Chin, the mission allows the company to train machine learning models using real-time data collected in orbit, significantly reducing the need to transmit massive raw datasets back to Earth for processing.

Beyond imaging, MAVERIC will test low-cost magnetic field sensing to determine if inexpensive CubeSats can provide high-quality space weather data comparable to more expensive platforms. The spacecraft also features a novel navigation approach that utilizes Earth’s magnetic field for orientation instead of traditional reaction wheels. Researchers plan to use AI-based reinforcement learning to analyze flight data and upload improved navigation algorithms to the satellite while it is in orbit, potentially leading to more efficient and lower-cost spacecraft designs for the broader space industry.