This article has been written by Sheba Attoor pursuing a Startup Generalist & Virtual Assistant Training Program from Skill Arbitrage.
This article has been edited and published by Shashwat Kaushik.
Table of Contents
Introduction
Man is the only creature on Planet Earth to be endowed with a brain that has various abilities, viz., learning from experience, applying knowledge acquired from experience, the ability to handle complex situations, the ability to solve problems when important information is missing, determining what is important, reacting quickly and correctly to new situations, understanding visual images, processing and manipulating symbols, and using heuristics.
If these human abilities that we call intelligence can be recreated in a machine, we call it artificial intelligence (AI), as it is man-made. The machine (computer or robot) should be able to think like a human, and act like a human, i.e., think rationally and act rationally.
Since 1956, when the word artificial intelligence (AI) was first coined by John McCarthy, we have seen a lot of progress in this field. The level of enthusiasm and work in this field has reached sky-highs, and it is now going on to the exploration of outer space.
Understanding AI
In our daily lives, if we look around, we find AI applications in our daily lives, from house-cleaning robots to self-driving cars. We now use AI in the fields of aviation, education, industry, marketing, finance, weather forecast, military, and space exploration. AI, gives recommendations when using Netflix, Amazon, etc. AI algorithms analyse our preferences and behaviour to suggest products. Face recognition is used in mobile phones, Google Maps, health care, etc.
Growth of AI
We see the development going from ‘Narrow Artificial Intelligence (ANI)’, used by Siri in Apple computers, Cortana in Microsoft, and Alexa in Amazon, to ‘General Artificial Intelligence (AGI),’ which has more fields of operation, like problem-solving ability and then to ‘Super Artificial Intelligence (ASI),’ which has the entire human intelligence. Then we have the most fundamental type of AI, active machine AI like the ‘Deep Blue’ and Netflix recommendation engine, which can respond to immediate tasks and requests, but cannot store memory or learn from past experiences. The next type is ‘Limited Memory AI’. This type can store past data and use that data to make predictions. Chatbots and self-driving cars fall under this category. The next stage of development is the ‘Theory of Mind AI’. This type can perceive and pick up on the emotions of others. Lastly, there is the ‘Self Aware AI’. As the name suggests, this AI possesses self awareness. This is the ultimate goal in AI development. This type of robot will be able to sense the feelings of others as well as have a sense of self. An almost close example of this type is ‘Sophia’. A robot was developed by Hanson Robotics. There is a lot of debate about the ethics of building such a robot.
Benefits of using AI in daily life
AI makes our work easier, faster, and more accurate, as it can do it continuously without the need for breaks, sleep, or restroom time. It works objectively, as there is no emotion involved.
AI-powered robots are used for rescue operations during natural disasters like earthquakes, floods and nuclear power stations.
IBM’s reactive AI machine ‘Deep Blue’ was able to communicate in real time and could beat Russian grandmaster Garry Kasparov in a 1997 chess match.
For space exploration:
- Lower cost- By automating, labour costs for human employees can be reduced. Also, robots require less maintenance compared to conventional machines. So over the long run, the cost of upkeep is very low. Robots need not eat, sleep, or go to the washroom. They can survive in space for a long time and can be left there without a return trip.
- Less human oversight- Since AI-powered robots can work independently, gather data, make decisions, and also act according to their needs, supervision is not needed.
- More efficient: Better than humans when it comes to exploring uncharted regions of the universe. Using robots reduces risk factors and life-supporting systems.
More efficient than humans when it comes to analysing vast volumes of data and making decisions. Robots rarely make mistakes and have great precision. They are fast and don’t tire or get bored with repetition.
Need for AI in space exploration
AI spacecraft should have the ability to carry out decisions based on data collected, the ability to interpret the given goal as a list of actions or steps to be taken, and to continuously change action based on what is happening within their system and surroundings.
AI can be used to control spacecraft, analyse data, and make quick decisions.
Ability to explore deeper in space, which is otherwise restricted by long communication times with human controllers. Robotic spacecraft would often be out of communication with human controllers and yet produce better results.
The immense use of AI in space missions is due to the development of high-level automated systems like AI-powered soft landing, inertial navigation and simultaneous localization and mapping (SLAM), hazard detection and avoidance, and trajectory planning.
Multilayered artificial neural networks (deep learning) enable AI-powered robots to learn by themselves. On planets like Mars, where extreme conditions prevail, AI can be used as supplementary tools to perform tasks that humans wouldn’t be able to perform.
AI-powered space crafts
CIMON (crew interactive mobile companion) is the first robot with AI to fly in space. CIMON acts like a hands-free database, computer, and camera. Astronauts can fully control CIMON by using voice commands. CIMON can see, speak, hear, understand, and even fly!
NASA’s Mars 2020 rover, Perseverance, uses an AI system called Terrain-Relative Navigation to analyse images of the Martian surface and adjust its landing position accordingly.
ISRO’s Chandrayaan-3 uses AI for a soft landing on the lunar surface, hazard detection, and avoidance cameras to avoid the harsh lunar terrain.
Inertial navigation, SLAM and trajectory planning. The rover Pragyan observed and studied the chemical and mineralogical composition of the lunar soil. The AI algorithms were developed by ISRO in collaboration with IIT, Madras.
ESA (European Space Agency) uses the Advanced Concepts Team (ACT) to explore uncharted regions of space. This involves a collection of small robots that share their information in a network. If one robot learns from experience, it is shared with the other robots. This is called hive learning.
Some AI uses in space exploration
ESA’s Hera planetary defence mission works similarly to self-driven cars. It prevents the collision of artificial satellites with asteroids and space debris.
In the ESA’s European Earth Observation Mission, the CubeSat
carried an artificial intelligence 𝟇-sat 1, which automatically discarded clouded images and sent only useful data down to Earth.
AI can be used to improve the images of the sun and collect more data, which can be used by scientists for solar research.
NASA, along with Google, used AI to analyse vast amounts of data from the Kepler exoplanet mission. This led to the discovery of two new exoplanets previously missed by human scientists.
The Japanese Space Agency’s (JAXA) Epsilon rocket was the first to use AI by performing checks and monitoring its performance autonomously. Thus, Epsilon made launching a payload into space simpler than ever before.
JAXA also developed an intelligent robot called ‘int-ball’ that takes pictures of experiments done on the ISS, saving astronauts valuable time. Artificial Intelligence is also aiding astronauts on board the International Space Station (ISS)
French space agency CNES worked with French company Clemessy to optimise the filling of rocket tanks using AI neural networks.
The UK space agency funded a project that uses AI to detect buried archaeological remains in satellite imagery.
India’s ISRO plans to launch a fleet of fifty new AI-powered satellites that interact and gather geo-intelligence to provide surveillance of the country’s borders.
Benefits of using AI in space exploration
Here are some of the potential benefits of using AI in space exploration:
- Reduced costs: AI-powered robots can be less expensive to develop and operate than human astronauts. This could make it possible to send more frequent and longer-duration missions to space.
- Increased safety: AI-powered robots can be used to explore dangerous or inaccessible areas without putting human lives at risk. This could make it possible to explore new worlds that are currently too dangerous for humans to visit.
- New discoveries: AI can be used to analyse data collected by space probes and satellites more quickly and efficiently than humans can. This could lead to new discoveries about the universe.
- Improved communication: AI can be used to improve communication between astronauts and ground control. This could make it possible for astronauts to stay in touch with their families and friends while they’re on long-duration missions.
AI is a powerful tool that has the potential to revolutionise space exploration. As AI continues to develop, it’s likely to play an increasingly important role in our quest to understand the universe.
How NASA uses AI in space exploration
NASA, the National Aeronautics and Space Administration, is renowned for its groundbreaking endeavours in space exploration. Artificial intelligence (AI) has emerged as a transformative tool, revolutionising various aspects of NASA’s missions. Here’s how NASA harnesses the power of AI to push the boundaries of space exploration:
- Autonomous navigation and guidance:
NASA employs AI-powered autonomous navigation systems to guide spacecraft through complex trajectories. These systems leverage machine learning algorithms to process real-time data from sensors, cameras, and onboard instruments. By analysing this data, AI can detect obstacles, adjust flight paths, and optimise fuel consumption, enabling spacecraft to navigate autonomously in space. - Image processing and analysis:
AI plays a vital role in analysing vast amounts of imagery and data collected by space telescopes and probes. Machine learning algorithms are trained to identify patterns, classify objects, and extract meaningful insights from images. This capability allows scientists to detect exoplanets, study celestial bodies, and gain a deeper understanding of the universe. - Natural language processing:
NASA utilises natural language processing (NLP) to enhance communication between humans and AI systems. NLP enables spacecraft to comprehend and respond to complex voice commands, aiding astronauts in controlling and monitoring various systems. Additionally, NLP helps translate scientific data into human-readable formats, facilitating seamless collaboration between scientists and engineers. - Predictive analytics:
Predictive analytics plays a crucial role in mission planning and risk assessment. AI algorithms analyse historical data and identify patterns to forecast future events and potential hazards. This enables NASA to make informed decisions, optimise resource allocation, and minimise risks during space missions. - Scientific discovery and exploration:
AI empowers scientists to explore vast datasets and uncover hidden patterns and relationships within them. Machine learning algorithms can analyse large volumes of scientific data, identify anomalies, and generate hypotheses that guide further research. This has led to significant advancements in astrophysics, planetary science, and other fields of space exploration. - Robotics and automation:
AI-powered robotics and automation play a vital role in space exploration. Rovers equipped with AI can traverse harsh terrains, collect samples, and perform scientific experiments autonomously. Additionally, AI algorithms enable autonomous docking and servicing of satellites and spacecraft, reducing the need for human intervention. - Spacecraft health monitoring:
AI is used to monitor the health and performance of spacecraft systems. Machine learning algorithms continuously analyse telemetry data to detect anomalies, predict failures, and identify potential maintenance needs. This proactive approach helps prevent malfunctions and ensures the safety and reliability of space missions.
NASA’s integration of AI into space exploration has revolutionised the way we understand and navigate the cosmos. As AI capabilities continue to advance, NASA will undoubtedly leverage this technology to unlock even greater possibilities and push the boundaries of human knowledge and exploration in space.
Role of AI and machine learning in NASA’s missions
Artificial intelligence (AI) and machine learning (ML) are playing an increasingly important role in NASA’s missions. These technologies are helping NASA to automate tasks, improve decision-making, and gain new insights into the universe.
Self-driving rovers on Mars
One of the most visible examples of AI and ML in use at NASA is the self-driving rovers on Mars. These rovers are equipped with a variety of sensors that collect data about their surroundings. This data is then processed by AI and ML algorithms to help the rovers navigate their way around Mars, avoid obstacles, and identify interesting scientific targets.
The self-driving rovers have been a major success for NASA. They have allowed scientists to explore Mars in much greater detail than was previously possible. The rovers have also made a number of important discoveries, including evidence of past water on Mars and the presence of organic molecules in the Martian atmosphere.
A robotic astronaut – the robonaut
Another example of AI and ML in use at NASA is the Robonaut, a robotic astronaut that is being developed to help astronauts with tasks such as repairs and maintenance. The Robonaut is equipped with a variety of sensors and actuators that allow it to move around and interact with its environment. The Robonaut is also equipped with AI and ML algorithms that allow it to learn and adapt to new situations.
The Robonaut is still under development, but it has already shown great promise. In 2011, the Robonaut became the first robot to work outside the International Space Station. The Robonaut is expected to play a major role in future NASA missions, as it will allow astronauts to work more safely and efficiently in space.
AI and ML are revolutionising NASA’s missions. These technologies are helping NASA to automate tasks, improve decision-making, and gain new insights into the universe. As AI and ML continue to develop, they will play an even greater role in NASA’s future missions.
Chandrayaan-3
The Indian Space Research Organisation (ISRO) is embarking on an ambitious endeavour—its second Moon mission, named Chandrayaan-3. At the forefront of this mission is the cutting-edge AI-powered rover, aptly named “Pragyan.” This remarkable rover promises to revolutionise lunar exploration, enabling scientists to unravel the mysteries of the moon’s surface and subsurface like never before.
Pragyan is equipped with an array of advanced sensors and instruments, meticulously designed to gather valuable data and provide unprecedented insights into the lunar environment. Its AI capabilities empower it to make autonomous decisions, adapt to changing conditions, and prioritise scientific investigations. This level of autonomy allows Pragyan to explore regions that were previously inaccessible to traditional rovers, pushing the boundaries of lunar exploration.
One of Pragyan’s key features is its ability to analyse samples on-site using its onboard laboratory. This eliminates the need to transport samples back to Earth for analysis, significantly reducing the time required to obtain results. The rover’s AI algorithms enable it to identify and select the most promising samples, ensuring that the limited resources available are utilised efficiently.
Furthermore, Pragyan is equipped with a high-resolution camera system that captures stunning images and videos of the lunar landscape. These visuals not only aid in scientific research but also provide captivating content for public outreach and education. The rover’s AI capabilities allow it to identify and focus on features of particular interest, ensuring that the most scientifically valuable data is captured.
In addition to its scientific capabilities, Pragyan is also designed to withstand the harsh conditions of the lunar environment. Its robust design and advanced power systems enable it to operate in extreme temperatures and radiation levels. The rover’s AI algorithms continuously monitor its health and performance, allowing it to adapt to changing conditions and optimise its operations accordingly.
The AI-powered rover Pragyan represents a significant milestone in space exploration. Its advanced capabilities empower it to conduct groundbreaking research, enabling scientists to gain a deeper understanding of the Moon’s geology, mineralogy, and potential resources. Pragyan’s successful deployment on Chandrayaan-3 will open up new avenues for lunar exploration and pave the way for future missions to the Moon and beyond.
Future of AI in space exploration
The predictable future with AI in space exploration is expeditions to other planets, leading to permanent and self-sufficient settlements on the Moon and Mars.
Robots are likely to be employed to establish mining and fueling outposts in the asteroid belt.
The Vera C. Rubin Observatory has already used AI to spot a potentially dangerous asteroid.
AI can help astronomers make unexpected and incredible discoveries and perhaps life on other planets.
Conclusion
Leading countries in AI research and technology are the USA, China, UK, Israel, Canada, France, India, Japan, Germany and Singapore.
In a world that is continuously progressing at a fast rate, Artificial Intelligence is a natural step forward. Although AI with self-modifying and self-replicating abilities (neural networks) is of great use, it may have dangerous and unexpected results.
Robots used in the military may make dangerous decisions that could destroy our planet itself.
There is a lot of debate on the ethics of ‘Self Aware AI’. Movies like The Matrix give an ominous prophecy of future misfortune.
As said by Stephan Hawking “It will either be the best thing that’s ever happened to us, or it will be the worst thing. If we’re not careful, it may very well be the last thing.”
References
- How AI drove the historic landing of Chandrayaan 3 – Bohitesh Misra
- https://www.esa.int
- https://indiaai.gov.in/
