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Will we use AI to work and settle on the moon in the future?
Will we use AI to work and settle on the moon in the future?
Many stories about AI have taken place in the universe, perhaps because of the universal, life and AI propositions that can bring us the desire to explore and the vastness of the sense of insignificance in the face of eternity. Even without the emotional resonance, the moon and AI have certain practical levels of connection.
On the day when the moon is the most round, we might as well see how AI draws human contact with the moon. Maybe someday in the future, we can really work with AI and settle down on the moon.
After all, the charm of the future comes from uncertainty.
Depth learning processing lunar images and data
The most direct link between artificial intelligence and the moon should be NASA's advanced development laboratory FDL series proposed by NASA's NASA.
By building a deep learning system, NASA can analyze the lunar 3D images acquired over a large number of angles and in a long time. Outline a more complete and accurate lunar surface topography database, and more accurately predict the trajectory of the earth, the moon, and the sun between the three.
The main reason for this is that the moon's speed of revolution causes the moon to have large areas of the moon hidden in the shadow, which poses great difficulties for the study of the moon and the moon. By using neural networks and other techniques to learn and reason about the existing data, it is possible to explore the moon and the moon poles in the shadow.
Another necessity is that NASA has a large number of satellites that simultaneously photograph lunar images, as well as lunar surface probes that send precise data. But these data are scattered and huge, and it is difficult to complete the integration analysis task manually. Therefore, the use of depth learning technology to deal with data has become the most appropriate choice.
The application of artificial intelligence in lunar data is not only forward-looking research value, but already has very specific application scenarios. For example, to help calculate lunar landing point, the best operation trajectory of lunar rover to speculate the maximum acceptance of solar power lines, so as to enhance its service life, high precision lunar environment data reasoning, help scientists analysis of lunar geology information etc..
In the future, once the moon has been re opened, it will be more important to draw a lunar map of high precision with artificial intelligence.
The NASA AI data processing methods of the moon, mainly relying on projects such as Intel giant AI cooperation. This model may also be well developed in China in the future.
Artificial intelligence in lunar exploration
It says about the moon landing, but we all know that human re landing has not been put on schedule, because there are a lot of security risks and cost problems in manned space flight. The constraints of these conditions have prevented most countries from imitating the human landing on the moon under extreme political and economic circumstances. It can be said to be a pity.
Artificial intelligence is playing a more and more important role in manned space exploration and star landing exploration.
For example, the most important aspect of space shuttle launch and space station building is risk control. So far, rocket launchers and space station maintenance have always been highly dangerous jobs. Any minor flaw can lead to a very serious accident.
One of the important sources of risk lies in the fact that space vehicles and other equipments are extremely complex and can not be monitored and eliminated in real time. Because of the breakdown of time and steps between the investigation and the launching, the accident problems can not be completely eliminated.
Space experts have been building AI technology to build rockets and space shuttle overall accident detection systems. Through the artificial knowledge network Tupu Model, the perception and controllable spacecraft safety matrix can be established, so that the equipment safety can be monitored for the first time.
This is known as the active safety monitoring system for spacecraft, and the future hero behind this system will come from the data perception and overall learning ability of artificial intelligence.
In addition, using artificial intelligence to construct astronaut's auxiliary system is also one of the important subjects.
In the universe, the astronaut's senses are heavily restricted by the environment, and cannot be perceived as accurately as the earth does. At present, this area is relatively mature intelligent cockpit management system. It can learn from past tasks and accident experiences through machine learning and provide more optimized options for astronauts when they need help.
Of course, like "Iron Man" and "battle armor", "nanny artificial intelligence" does not yet exist, but the intelligent system to monitor the spacecraft, space suit and docking system has become increasingly possible.
Another important scenario is the planning and scheduling system for astronauts when they land on other planets. For extraterrestrial landings, the greatest danger comes from projected landings, inconsistencies in reality, or other unknown factors. What may be used here is the ability of neural networks to sense and judge the fuzzy environment. Through the fuzzy perception of data and large database connectivity, help astronauts real-time adjustment landing program, is landing extraterrestrial intelligence may
On the day when the moon is the most round, we might as well see how AI draws human contact with the moon. Maybe someday in the future, we can really work with AI and settle down on the moon.
After all, the charm of the future comes from uncertainty.
Depth learning processing lunar images and data
The most direct link between artificial intelligence and the moon should be NASA's advanced development laboratory FDL series proposed by NASA's NASA.
In this project, NASA hopes to develop the technology of artificial intelligence to deal with various problems involved in space exploration. Particularly important, is the use of artificial intelligence to the analysis of the current NASA large amount of data collected after so many satellites and planetary rover, astronomical telescope, always on the record and collect data, these data processing workload is far from human can bear.
By building a deep learning system, NASA can analyze the lunar 3D images acquired over a large number of angles and in a long time. Outline a more complete and accurate lunar surface topography database, and more accurately predict the trajectory of the earth, the moon, and the sun between the three.
The main reason for this is that the moon's speed of revolution causes the moon to have large areas of the moon hidden in the shadow, which poses great difficulties for the study of the moon and the moon. By using neural networks and other techniques to learn and reason about the existing data, it is possible to explore the moon and the moon poles in the shadow.
Another necessity is that NASA has a large number of satellites that simultaneously photograph lunar images, as well as lunar surface probes that send precise data. But these data are scattered and huge, and it is difficult to complete the integration analysis task manually. Therefore, the use of depth learning technology to deal with data has become the most appropriate choice.
The application of artificial intelligence in lunar data is not only forward-looking research value, but already has very specific application scenarios. For example, to help calculate lunar landing point, the best operation trajectory of lunar rover to speculate the maximum acceptance of solar power lines, so as to enhance its service life, high precision lunar environment data reasoning, help scientists analysis of lunar geology information etc..
In the future, once the moon has been re opened, it will be more important to draw a lunar map of high precision with artificial intelligence.
The NASA AI data processing methods of the moon, mainly relying on projects such as Intel giant AI cooperation. This model may also be well developed in China in the future.
Artificial intelligence in lunar exploration
It says about the moon landing, but we all know that human re landing has not been put on schedule, because there are a lot of security risks and cost problems in manned space flight. The constraints of these conditions have prevented most countries from imitating the human landing on the moon under extreme political and economic circumstances. It can be said to be a pity.
Artificial intelligence is playing a more and more important role in manned space exploration and star landing exploration.
For example, the most important aspect of space shuttle launch and space station building is risk control. So far, rocket launchers and space station maintenance have always been highly dangerous jobs. Any minor flaw can lead to a very serious accident.
One of the important sources of risk lies in the fact that space vehicles and other equipments are extremely complex and can not be monitored and eliminated in real time. Because of the breakdown of time and steps between the investigation and the launching, the accident problems can not be completely eliminated.
Space experts have been building AI technology to build rockets and space shuttle overall accident detection systems. Through the artificial knowledge network Tupu Model, the perception and controllable spacecraft safety matrix can be established, so that the equipment safety can be monitored for the first time.
This is known as the active safety monitoring system for spacecraft, and the future hero behind this system will come from the data perception and overall learning ability of artificial intelligence.
In addition, using artificial intelligence to construct astronaut's auxiliary system is also one of the important subjects.
In the universe, the astronaut's senses are heavily restricted by the environment, and cannot be perceived as accurately as the earth does. At present, this area is relatively mature intelligent cockpit management system. It can learn from past tasks and accident experiences through machine learning and provide more optimized options for astronauts when they need help.
Of course, like "Iron Man" and "battle armor", "nanny artificial intelligence" does not yet exist, but the intelligent system to monitor the spacecraft, space suit and docking system has become increasingly possible.
Another important scenario is the planning and scheduling system for astronauts when they land on other planets. For extraterrestrial landings, the greatest danger comes from projected landings, inconsistencies in reality, or other unknown factors. What may be used here is the ability of neural networks to sense and judge the fuzzy environment. Through the fuzzy perception of data and large database connectivity, help astronauts real-time adjustment landing program, is landing extraterrestrial intelligence may