Cosmic Game Changer. How AI Driving Space Industry To New Horizons
The field of space travel, exploration, and observation is home to some of the most complex and dangerous scientific and technical operations ever carried out. However, artificial intelligence (AI) has proven to be incredibly useful in tackling the challenges that arise in this field.
AI is currently being utilized in the space industry to help scientists analyze data more quickly and accurately, as well as to automate operations on spacecraft. The continuous development of AI technology is enabling rovers and landers to explore other planets and moons in ways that were never before possible. All of these advancements are contributing to new discoveries and making AI an invaluable tool for learning more about the world beyond our own.
For decades, scientists have used AI to study the cosmos, creating algorithms that help map new planets, stars, and black holes with greater speed and accuracy than humans. In recent times, AI has been used to carry out autonomous missions with robots that can withstand conditions still too dangerous for humans. Renowned scientists, like Neil deGrasse Tyson, emphasize the transformative impact of AI on the space industry.
“Now, we’re entering a new era where artificial intelligence could not only expand our understanding of the universe, but help us find new life within it”, deGrasse Tyson says.
It's fascinating how AI has become an integral part of modern-day space exploration. From guiding rockets in space to examining distant planetary surfaces, determining the universe's dimensions, and plotting celestial trajectories, AI has been utilized in various innovative and captivating ways.
Researchers now use AI and machine learning (ML) models to automate spacecraft functions, process vast data sets, and even save lives. These functions have become extremely crucial in the quest for knowledge in space exploration. In this article, we will delve into some of the most exciting applications of AI in space.
Robotics
AI is playing an increasingly vital role in space exploration by autonomously navigating around obstacles. Rovers like Mars Exploration Rover and Curiosity have been doing fully-autonomous navigation on Mars for over a decade. The rover's sensors detect hazards, and AI analyzes the data to determine the best path. AEGIS, a computer vision-based detection system, helps the Perseverance rover finds interesting rocks to sample, paving the way for completely autonomous space exploration rovers.
Healthcare for Manned Space Exploration
AI is crucial for healthcare in manned space exploration due to the unique challenges posed by space missions. AI helps address complex diagnoses, treatment needs, and monitors astronaut health and psychological well-being. Trained on extensive medical data, these models predict patient risks and outcomes with high accuracy. Such capabilities are vital for space healthcare, given the increased variables and challenges. AI's advanced analytics ensures astronaut well-being and optimizes healthcare resources in space.
Mining
In space mining, AI plays a critical role. AI-driven geospatial solutions process vast satellite, drone, and sensor data, enhancing human analyst capabilities, as emphasized by Mark Munsell of the National Geospatial-Intelligence Agency.
AI algorithms are pivotal in asteroid mining, identifying lucrative asteroids. Asterank, using AI, evaluated over 6,000 asteroids and found that mining the top 10 could yield US$1.5 trillion, with 16 Psyche alone estimated to contain US$700 quintillion in gold. AI integration in space mining leads to optimized extraction, efficient resource identification, and cost-effectiveness, paving the way for expansive resource exploration beyond Earth.
Machine Learning in Astrobiology Research
Astrobiology utilizes AI to explore life in the universe. Machine learning algorithms sift through extensive data on habitable zones, planetary conditions, and biological markers, helping scientists focus on promising locations for life. This approach expedites our cosmic understanding and targets potential life-sustaining environments.
AI applications in extraterrestrial life research include:
- SETI Institute's AI algorithm that detects methane in exoplanet atmospheres, a potential biosignature.
- University of California, Berkeley's machine learning algorithm that finds patterns in Kepler telescope data, indicating Earth-like exoplanet atmospheres.
- Jet Propulsion Laboratory's (JPL) AI algorithm aiding the Mars Perseverance rover in selecting exploration targets.
Satellite Operations
As the space industry grows, AI/ML technologies are essential in managing complex satellite networks, offering efficient routing and reducing ground station dependence. They improve satellite health management by providing accurate fault predictions, potentially extending satellite lifespans.
AI/ML is also enhancing space mission safety and success, particularly in areas like AOCS and space weather monitoring, by ensuring precise attitude determination and enabling thorough data collection and rapid information sharing.
As the space industry evolves, AI/ML's role in addressing operational, exploratory, and security challenges is increasingly crucial.
The possibilities are endless. AI has potential applications in a wide range of areas including the search for extraterrestrial life, satellite production, Earth exploration and imaging, star and galaxy mapping, rocket landings, and astrogeology to name a few. The scope for AI usage in space industry is incredibly broad.
For example, NASA employs AI for a wide range of applications, including scientific analysis, spacecraft operations, and deep space network management. It has developed cognitive radio technology to improve communication efficiency by using 'white noise' areas for data transmission, enhancing the limited telecommunication bands. AI is also used to calibrate solar images, aiding in solar research. For deep-space missions, NASA is exploring more autonomous spacecraft and landers to make real-time decisions and reduce communication delays.
In collaboration with Google, NASA trained AI algorithms to analyze data from the Kepler exoplanet mission, leading to the discovery of two previously overlooked exoplanets. This success extended to the TESS mission, where AI has been instrumental in identifying potential exoplanets.
A notable application is how AI and computational language can help us in visualizing and understanding the early universe's existence. Stephen Wolfram, the creator of the well-known Wolfram Alpha software, demonstrated how this can be achieved.
“It all starts from the idea that space—like matter—is made of discrete elements. And that the structure of space and everything in it is just defined by the network of relations between these elements—that we might call atoms of space. It’s very elegant—but deeply abstract.
But here’s a humanized representation:
A version of the very beginning of the universe. And what we’re seeing here is the emergence of space and everything in it by the successive application of very simple computational rules. And, remember, those dots are not atoms in any existing space. They’re atoms of space—that are getting put together to make space. And, yes, if we kept going long enough, we could build our whole universe this way.”
The rapid development of AI has the potential to cause significant disruptions in the aerospace industry, which may lead to job losses, including design and engineering roles. This could fundamentally change the economic structure of the space industry and its reliance on job-centric and cost-plus approaches.
Despite the potential for disruption, AI's advanced capabilities may make previously impossible missions and projects feasible. The future of aerospace is expected to be transformative, with numerous new investment opportunities arising.
