Robots have become extremely helpful for us to accomplish difficult tasks and dangerous missions. Though they are non-human aids, we tend to personify them by giving them human-like features and equip them with artificial intelligence.
Usually, we teach the robots these artificially intelligent systems by encoding complicated computer codes, which allows the computer to mimic human intelligence.
However, computers can also achieve this through Machine Learning, where machines are trained to learn for themselves. We feed the machine’s algorithm with a massive load of data, and it processes them by developing artificial neural networks.
It leads us to Deep Learning, where the computer uses multiple layers of artificial neural networks as training for complex tasks like image recognition. DL can happen either through supervised or unsupervised (reinforced) learning.
Space Application and Related Researches on Artificial Intelligence
More improvements are needed for AI’s adaptability and reliability and ML’s complicated structures before we can consider it useful. However, some famous applications of AI include:
- Satellite Operations: This mainly refers to the operational side of large satellite constellations.
- Approximations of Real-World Complex Representations: These are manifested especially in analyzing vast amounts of data and telemetry information from Earth observation and spacecraft.
- Space Mission Data Analysis: This involves ML systems analyzing a large amount of data coming from every space mission.
Moreover, ESA’s Basic Activities developed many research pieces that utilized artificial intelligence for space applications and spacecraft operations, which includes:
- identification of necessary requirements and technology to improve automation for future spacecraft constellations
- Complex Constellation Management that observes new automated procedures to lessen the active workload for ground operators
Technologies that incorporate machine learning in space applications generally involve producing and analyzing the data, including spacecraft and telemetry data.
ESA’s Advanced Concept Team (ACT) and Extensive Applications
ESA’s ACT is actively present in a variety of DL applications like fully automated systems. An example of tits supported activities is investigating a science mobile app that improves space probes’ autonomous capabilities.
Concerning this, ACT particularly:
- studies evolutionary computation, where better evolutions are kept, and worse are rejected, like in calculating planets’ trajectories
- investigates areas of guidance, navigation, and control using ML, like that in hive learning
ESA also uses AI and ML in space missions, some of which is evident in:
- rovers autonomously finding their way across unfamiliar fields and navigating around obstacles
- Machine learning algorithms utilized in quick identification and clustering of comets’ debris
Additionally, ESA has also acquired ample experience in using AI to plow through large amounts of data to come up with meaningful information, which is similar to some applications in our world, like predicting retailers’ financial conduct.
Other space agencies also coordinated with NASA, while some made their technological applications like:
- German Aerospace Center (DLR)’s CIMON and CIMON-2
- NASA and Google’s Discovery of Two New Exoplanets
- NASA and ESA’s Artificial Intelligence Data Analysis (AIDA)
- Japanese Space Agency’s (JAXA’s) Int-Ball
Truly, AI-equipped robots continue to impress and go over boundaries of human imagination, which eventually led them to extend their special applications outside this world.
How do you plan to take advantage of the power of artificial intelligence in your thesis? Message me in the comments below.
Mr. Jaycee De Guzman holds a degree in Computer Science. The machine language is his favorite among the several languages he can fluently speak and write with. As a self-taught computer scientist, he is into computer science, computer engineering, artificial intelligence, game development, space technology, and medical technology. He is also an entrepreneur with businesses in several niches such as, but not limited to, digital marketing, finance, agriculture, and technology.