Space is a messy place. An estimated 34,000 pieces of junk over 10 cm in diameter are at the moment orbiting Earth at around 10 times the speed of a bullet. If one among them hits a spacecraft, the harm could possibly be disastrous.
In September, the International Space Station needed to dodge an unknown piece of debris. With the amount of space trash quickly rising, the probabilities of a collision are rising.
The European Space Agency (ESA) desires to scrub up some of the mess — with the help of AI. In 2025, it plans to launch the world’s first debris-removing space mission: Clearspace-1.
The technology is being developed by Swiss startup ClearSpace, a spin-off from the Ecole Polytechnique Fédérale de Lausanne (EPFL). Their removal target is the now-obsolete Vespa Upper Part, a 100 kg payload adaptor orbiting 660 km above the Earth.
ClearSpace-1 will use an AI-powered camera to seek out the particles. Its robotic arms will then seize the object and drag it back to the atmosphere before burning it up.
“A central focus is to develop deep learning algorithms to reliably estimate the 6D pose (three rotations and three translations) of the target from video-sequences even though images taken in space are difficult,” said Mathieu Salzmann, an EPFL scientist heading the mission. “They can be over- or under-exposed with many mirror-like surfaces.”
Vespa hasn’t been seen for seven years, so EPFL will use a database of artificial images to simulate its current look as training materials for the algorithms.
Once the mission begins, the researchers will seize real-life pictures from beyond the Earth’s ambiance to finetune the AI system. The algorithms additionally must be transferred to a devoted hardware platform onboard the captured satellite.
“Since motion in space is well behaved, the pose estimation algorithms can fill the gaps between recognitions spaced one second apart, alleviating the computational pressure,” stated Professor David Atienza, head of ESL.
“However, to ensure that they can autonomously cope with all the uncertainties in the mission, the algorithms are so complex that their implementation requires squeezing out all the performance from the platform resources.”
If the capture is successful, it might pave the way for further debris-removal missions that may make space a safer place.
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