Artificial intelligence has long been transforming our daily lives and the daily operations of many businesses. From smart assistants like Siri and Alexa to more complex solutions that optimize business flow in large organizations, the technology has become so pervasive that it has almost become an inseparable companion. But AI’s power to revolutionize doesn’t end there; it extends well beyond individual and company lives into such massive and complex industries as space exploration and science.
With recent breakthroughs and discoveries, AI has been showing immense potential in space exploration, such as global navigation, earth observation, and communications to and fro. Historically, machine learning algorithms have been used in monitoring the spacecraft, autonomous navigation of the spacecraft, controlling systems, and intelligently detecting objects in the route.
Although astronauts are trained physically and psychologically to deal with extreme space situations, living in a confined space with no gravity could sometimes be stressful and could hamper their decision-making processes. This is where artificial intelligence is coming into the picture. Several years after the first moon landing, experts are now looking at emerging technologies to understand the space exploration a little better. And now, in a bid to help astronauts, AI-based assistants are being created to aid astronauts in their missions to Mars and beyond. These assistants are designed to understand and predict the requirements of the crew and comprehend astronautsâ€™ emotions and their mental health.
With rapid technological development and increasing investment in R&D sector, space exploration is experiencing rapid technical development owing to the integration of AI and the space vehicles which are developed for space exploration. The factor leading to the growth of AI in space exploration is the development of AI-based robots that can perform highly complex tasks over a longer period without human inference and for enhances mobility and manipulation benefits. AI offers high flexibility, accuracy and control owing to the development of 3D perception and proximity GNC in AI robots. Moreover, robotics arms in space exploration is witnessing high demand due to the high weightlifting and handling capabilities that are offered to astronauts.
Space has now become a warfighting domain, and Space force is employing AI and Machine Learning to regain space superiority by taking data and turning it into information and turn information into action. The Space Force is said to be seeking technologies related to a range of space operations, including artificial intelligence (AI), weather, business systems, and information technology (IT) for future spacelift missions.
If Russia or China were to launch a missile at a U.S. satellite, operators would only have about 10 minutes to determine the assets most at risk and how to counter the attack. The Pentagon today does not have the capabilities to answer those questions in time, warns retired Lt. Gen. Chris Bogdan, a senior vice president at government services firm Booz Allen Hamilton. But the defense and space industries are working on ways to leverage artificial intelligence to help space troops to analyze the huge amounts of data — such as the location and trajectory of numerous military, intelligence, and civil space assets — to quickly take action. “If you don’t have machine learning and AI helping you sift through all of that, you’re not going to be able to make good decisions in the timeline that we have,” said Bogdan, who previously led the two of the Air Force’s most high-profile aircraft acquisition programs, the KC-46 air refueling tanker and the F-35 fighter jet.
NASA Hatch Artificial Intelligence Technologies
NASA scientists are trying to figure that out by partnering with pioneers in artificial intelligence (AI) — companies such as Intel, IBM and Google — to apply advanced computer algorithms to problems in space science. Machine learning is a type of AI. It describes the most widely used algorithms and other tools that allow computers to learn from data in order to make predictions and categorize objects much faster and more accurately than a human being can. Consequently, machine learning is widely used to help technology companies recognize faces in photos or predict what movies people would enjoy. But some scientists see applications far beyond Earth.
Giada Arney, an astrobiologist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, hopes machine learning can help her and her colleagues find a needle of life in a haystack of data that will be collected by future telescopes and observatories such as NASA’s James Webb Space Telescope.“These technologies are very important, especially for big data sets and especially in the exoplanet field,” Arney says. “Because the data we’re going to get from future observations is going to be sparse and noisy. It’s going to be really hard to understand. So using these kinds of tools has so much potential to help us.”
Katherine Bourzac writes, “machine learning algorithms can more quickly identify and cluster the debris that comets leave in their wake. By speeding up analysis of meteor showers, researchers hope to pinpoint the orbits of distant, but potentially dangerous, comets. This project is one of five being explored as part of an artificial intelligence pilot research program sponsored by NASA.”
The article, written by Steve Chien and Kiri Wagstaff of NASA’s Jet Propulsion Laboratory (JPL), “suggests that autonomy will be a key technology for the future exploration of our solar system, where robotic spacecraft will often be out of communication with their human controllers.” “The goal is for A.I. to be more like a smart assistant collaborating with the scientist and less like programming assembly code,” said Chien, a senior research scientist on autonomous space systems. “It allows scientists to focus on the ‘thinking’ things — analyzing and interpreting data — while robotic explorers search out features of interest.”
“The vast majority of space exploration is conducted by robotic probes. Increasing the autonomy in future missions is essential to both increasing the effectiveness of space exploration as well as exploring more distant, challenging environments, such as sub-ice oceans,” Chien concluded.
To help scientists like Arney build cutting-edge research tools, NASA’s Frontier Development Lab, or FDL, brings together technology and space innovators for eight weeks every summer to brainstorm and develop computer code. The four-year-old program is a partnership between the SETI Institute and NASA’s Ames Research Center, both based in Silicon Valley where startup-hatching incubators that bring talented people together to accelerate the development of breakthrough technologies are abundant.
In NASA’s version, FDL pairs science and computer engineering early-career doctoral students with experts from the space agency, academia, and some of the world’s biggest technology companies. These Goddard scientists hope to one day use advanced machine learning techniques to quickly interpret data revealing the chemistry of exoplanets based on the wavelengths of light emitted or absorbed by molecules in their atmospheres. Since thousands of exoplanets have been discovered so far, making quick decisions about which ones have the most promising chemistry associated with habitability could help winnow down the candidates to only a few that deserve further, and costly, investigation.
The potential of this type of this instrument is not lost on anyone. SETI head, Diamond, imagines a future where these virtual tools are incorporated on spacecraft, a practice that would allow for lighter, less complex and therefore cheaper missions. Domagal-Goldman and Arney envisage future exoplanet missions where AI technologies embedded on spacecraft are smart enough to make real-time science decisions, saving the many hours necessary to communicate with scientists on Earth. “AI methods will help us free up processing power from our own brains by doing a lot of the initial legwork on difficult tasks,” Arney says. “But these methods won’t replace humans any time soon, because we’ll still need to check the results.
Plus, according to NASA, AI allows spacecraft to prioritize the data it collects, balancing other needs like power supply or limited data storage. Autonomous management of systems like these is being prototyped for NASA’s Mars 2020 rover. The Futurism site reports that “Any AI that we use in the future of space exploration will allow us to retrieve data from the places we send probes to, as well as allow us to explore them further, and collect better data. Since humans aren’t yet able to traverse these locales ourselves, unless we’re willing to hand at least some of that responsibility over to AI, it’s unlikely any of these missions could happen.”
Space Force seeking AI technologies
One of the tools and capabilities we feel will become increasingly important for that is AI and machine learning, partly because there is so much data that has to be sifted through to create actionable decisions but also because of the [short] timelines commanders will be put under to fight in space. If you don’t have machine learning and AI helping you sift through all of that, you’re not going to be able to make good decisions in the timeline that we have.
There are three main areas where we see AI and machine learning being important and applicable to space warfighting, said retired Lt. Gen. Chris Bogdan. The first is space domain awareness, or trying to understand what’s going on in space. … That means understanding when things are maneuvering, are they maneuvering on purpose? Is it an adversary?
Booz Allen initially is building algorithms and AI and machine learning models to take care of the space domain awareness problem. That’s the first step in fighting combat. You have to know what the environment is like. … Unless we build the capabilities to defend our assets and until we build the command and control to maneuver and do both offensive and defensive operations in space, those algorithms and machine learning techniques have to take a back seat.
The second area we think AI and machine learning can help is what we call threat characterization and threat assessment. … Let’s say there is an adversary … [who launches] an anti-satellite missile. Today, the ability for the U.S. to detect that missile launch is near perfect. … What we can’t do today — and where machine learning and AI can help us — is understanding what assets are at risk in space because of that launch of that antisat missile. It may take only 10 minutes to get where it needs to go. … Within that 10 minutes, you have to figure out what to do. The first step is figuring out what of your assets is at risk. … That requires lots of computational power [and the] ability to sift through tons of data in a very quick fashion.
With machine learning and AI, as that satellite is maneuvering or the anti-satellite missile is being launched, algorithms and computing power can quickly go through all of the different possibilities and probabilities and provide you [information] in near real time on what things are at risk.
The third piece where AI and machine learning can help is figuring out what the best thing to do is. … The timelines [in space] are so incredibly short. We’re talking minutes. … What you want to do is pick the best of that set of options [to respond] to make sure assets are safe and the mission is degraded as little as possible.
[The Pentagon is] trying very hard to tap into small innovative companies that may not be traditional Department of Defense contractors.
In Sep 2020, Geospark Analytics Inc.,* Herndon, Virginia, was awarded a $95,000,000 firm-fixed-price, indefinite-delivery/indefinite-quantity contract with a five year ordering period for the Phase Three commercialization of their Small Business Innovation Research Phase One technology of Hyperion Artificial Intelligence. The enterprise-level contract provides near real time situational awareness capabilities to the entire U.S. federal government, enabling users to make better decisions faster. This is accomplished by identifying and forecasting emerging events on a global scale to mitigate risk, recognize threats, greatly enhance indications and warnings and provide predictive analytics capabilities.
AI in Space Exploration Market
The Growing Numbers of Space Missions across the Globe Boosting the Demand for the AI Technology. Space Exploration Gives Rise to Humongous Amounts of Data That Cannot Be Analyzed Through Human Intelligence. The Capability of AI Technology to Make Decisions without Specific Commands from the Mission Control.
AI in space exploration Market is valued approximately USD 2 billion in 2018 and is anticipated to grow with a healthy growth rate of more than 7.25% over the forecast period 2019-2026. Machine learning and AI leave their imprints on various fields including construction, automation, image analytics, and space exploration along with many others.
Many applications of AI in space is being researched on various domains which includes relative positioning, communication and many others. Various spacecraft and space vehicles including satellites that are operating in the space may generates large amount of data owing to the complexity of the research missions. With AI in space exploration enables the data transmission over large distance with ease.
Many organization and government agencies are collaborating on machine learning solutions for detection of new planets, space weather using magnetosphere and atmosphere measurement. With rapid technological development and increasing investment in R&D sector, space exploration is experiencing rapid technical development owing to the integration of AI and the space vehicles which are developed for space exploration.
The factor leading to the growth of AI in space exploration is the development of AI-based robots that can perform highly complex tasks over a longer period without human inference and for enhances mobility and manipulation benefits. AI offers high flexibility, accuracy and control owing to the development of 3D perception and proximity GNC in AI robots. Moreover, robotics arms in space exploration is witnessing high demand due to the high weightlifting and handling capabilities that are offered to astronauts.
The regional analysis of AI in space exploration market is considered for the key regions such as Asia Pacific, North America, Europe, Latin America and Rest of the World. North America is expected to dominate the market share of AI in space exploration market owing to the presence of space organizations such as NASA and CSA working effectively towards the development of AI in space exploration. Moreover, U.S. and Canada are investing in the R&D sector and technological innovations to explore deep space. Whereas, Asia-Pacific is also anticipated to exhibit highest growth rate / CAGR over the forecast period 2019-2026 owing to the factors due to various ongoing and upcoming space programs in developing countries such as India and China.
Major market player included in this report are:Orbital ATK, DARPA, NeuralaDescartes Labs, KittyHawk, Iris Automation, Flyby NavPrecision, HawkPilot.ai, MRX Global Holding Corp., Oceaneering International, Maxar Technologies, Northrop Grumman, Astrobotic Technologies, and Motiv Space Systems.