CEDARVILLE — Cedarville University students have developed an artificial intelligence algorithm aimed at making future orbital debris removal more feasible. This research addresses growing concerns over space congestion, which was highlighted in June by the confirmed breakup of a Chinese rocket in Low Earth orbit.
The algorithm, designed to predict how rocket debris travels through space, offers a potential solution to a challenge that threatens active satellites and future space missions.
Low Earth orbit, extending approximately 1,200 miles above Earth’s surface, is vital for thousands of communications, navigation and Earth-observation satellites that enable global internet connectivity, weather forecasting and disaster monitoring. However, this strategically important region is becoming increasingly congested with orbital debris.
[DOWNLOAD: Free WHIO-TV News app for alerts as news breaks]
TRENDING STORIES:
- 44-year-old man arrested on arson charges after apartment fire in Fairborn
- 2 arrested after theft suspect runs from police onto I-75, jumps onto hood of woman’s car
- Coroner IDs man shot, killed after argument in Dayton
The June incident, confirmed by the U.S. Space Force, generated additional debris near the International Space Station and SpaceX’s Starlink broadband network.
Starlink, comprising more than 10,000 satellites, delivers high-speed internet to users across more than 160 countries and territories. Space experts warn that increasing amounts of orbital debris could disrupt communications infrastructure and complicate future commercial and government space operations worldwide.
Under the leadership of Dr. George Landon, professor of computer science at Cedarville University, junior Doxa Kudari of Bloomington, Ill., and 2026 graduate Elijah Lewis of Willard, Ohio, spent several months developing a system to determine the orientation of orbital objects over time. This work aimed to create a cleaner and safer environment for current satellites and future missions.
Kudari emphasized the importance of their work, noting the role of advanced technology. “It’s important to keep space clean for the sake of both people and rockets,” Kudari said. “Artificial intelligence is making that future possible as it continues to learn and adapt.”Before algorithm development, Kudari and Lewis compiled extensive datasets of rocket bodies, establishing a repository that previously did not exist. They then used artificial intelligence to generate 3D mesh models, allowing them to gain a deeper understanding of the curvature and structure of these rocket bodies.
The generated 3D mesh models were subsequently integrated into an orbital simulation. This simulation utilized measured orbital and altitude data, alongside predefined parameters for hypothetical scenarios, to calculate the amount of light reflected from a rocket body’s surface.
From these synthetic light curves, the team developed algorithms capable of predicting both the spin and shape of a rocket body using only its light curve.
The Cedarville University team recently presented their findings at the Dayton-Cincinnati Aerospace Sciences Symposium. The presentation offered an opportunity for the students to receive feedback from members of the regional aerospace community.
Lewis expressed gratitude for the experience, stating, “We got a lot of helpful feedback and were met with a lot of support. I was very grateful for the opportunity to be making real-world contributions while completing my degree.”
Moving forward, Dr. Landon plans to continue the research by collaborating with students to expand the mesh model library.
Additionally, he intends to refine the simulator and implement machine-learning techniques to enhance the reliability of the algorithms, which may enable future debris retrieval.
[SIGN UP: WHIO-TV Daily Headlines Newsletter]
