In Space Odyssey 2001, HAL 9000, the Heuristically Programmed Algorithmic Computer, consigned the crew commander to his death by refusing to open the pod bay doors. Leaping forward to June, 2020, NASA announced a visionary step: that intelligent computer systems will be installed on space probes to direct the search for life on distant planets and moons. The AI program will start with the 2022/23 ESA ExoMars mission before moving beyond to moons such as Jupiter’s Europa and of Saturn’s Enceladus and Titan.
“First Filter will be the AI system”
“When first gathered, the data produced by the Mars Organic Molecule Analyzer (MOMA) toaster-sized life-searching instrument will not shout out “I’ve found life here”, but will give us probabilities which will need to be analyzed,” says Eric Lyness, software lead in the Planetary Environments Lab at NASA Goddard Space Flight Center. “These results will largely tell us about the geochemistry that the instruments find. We’re aiming for the system to give scientists directions, for example our system might say “I’ve got 91% confidence that this sample corresponds to a real world sample and I’m 87% sure it is phospholipids, similar to a sample tested on July 24th, 2018 and here is what that data looked like”. We’ll still need humans to interpret the findings, but the first filter will be the AI system.”
Scientists from the NASA Goddard Space Flight Center announced the first results from new intelligent systems, to be installed in space probes, capable of identifying geochemical signatures of life from rock samples. Allowing these intelligent systems to choose both what to analyse and what to tell us back on Earth will overcome severe limits on how information is transmitted over huge distances in the search for life from distant planets. The systems will debut on the 2022/23 ExoMars mission (landing map at top of page), before fuller, autonomous implementation on more distant destinations in the Solar System.
Visionary step in space exploration
“This is a visionary step in space exploration.” said lead researcher Victoria Da Poian during the online June Goldsmidt Conference. “It means that over time we’ll have moved from the idea that humans are involved with nearly everything in space, to the idea that computers are equipped with intelligent systems, and they are trained to make some decisions and are able to transmit in priority the most interesting or time-critical information”.
“It costs a lot of time and money to send the data back to Earth which means scientists can’t run as many experiments or analyze as many samples as they would like. By using AI to do an initial analysis of the data after it is collected but before it is sent back to Earth, NASA can optimize what we receive, which greatly increases the scientific value of space missions.” adds Lyness.
Future systems for the outer solar system will be autonomous
Da Poian and Lyness have trained artificial intelligence systems to analyse hundreds of rock samples and thousands of experimental spectra from the Mars Organic Molecule Analyzer (MOMA), an instrument that will land on Mars within the ExoMars Rosalind Franklin Rover in 2023. MOMA is a state-of-the-art mass spectrometer-based instrument, capable of analyzing and identifying organic molecules in rocks samples. It will search for past or present life on the Martian surface and subsurface through analysis of rock samples. The system to be sent to Mars will still transmit most data back to Earth, but later systems for the outer solar system will be given autonomy to decide what information to return to Earth.
“Smart Algorithms” of the Future
“What we get from these unmanned missions is data, lots of it; and sending data over hundreds of millions of kilometers can be very challenging in different environments and extremely expensive; in other words, bandwidth is limited. We need to prioritize the volume of data we send back to Earth, but we also need to ensure that in doing that we don’t throw out vital information. This has led us to begin to develop smart algorithms which can for now help the scientists with their analysis of the sample and their decision-making process regarding subsequent operations, and as a longer-term objective, algorithms that will analyse the data itself, will adjust and tune the instruments to run next operations without the ground-in-the-loop, and will transmit home only the most interesting data.”
The team used the raw data from initial laboratory tests with an Earth-based MOMA instrument to train computers to recognize familiar patterns. When new raw data is received, the software tells the scientists what previously encountered samples match this new data.
Real-Time Onsite Decisions
“The mission will face severe time limits,” says Lyness. “When we will be operating on Mars, samples will only remain in the rover for at most a few weeks before the rover dumps the sample and moves to a new place to drill. So, if we need to retest a sample, we need to do it quickly, sometimes within 24 hours. In the future, as we move to explore the moons of Jupiter such as Europa, and of Saturn such as Enceladus and Titan, we will need real-time decisions to be made onsite. With these moons it can take 5 to 7 hours for a signal from Earth to reach the instruments, so this will not be like controlling a drone, with an instant response. We need to give the instruments the autonomy to make rapid decisions to reach our science goals on our behalf”.
“Data from a rover on Mars can cost as much as 100,000 times as much as data on your cell phone, so we need to make those bits as scientifically valuable as possible.” emphasized Lyness.