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From Vikram’s landing to Pragyan’s predictive maintenance, how AI is powering Chandrayaan 3

When ISRO revealed that they would proceed with today’s launch schedule for the Vikram Lander Module of Chandrayaan 3, they showed an exciting thing.

ISRO’s scientists will not control the Vikram Lander Module. Instead, it will be entirely governed by AI and ML algorithms explicitly designed for this mission to the lunar south pole.

As it turns out, ISRO is not using AI and ML just for the landing. Instead, like most other space agencies worldwide, ISRO uses AI for many things. Without AI algorithms, any space mission in this day and age would not only take a lot more effort but also be a lot more expensive and more prone to end in a disaster.

Letting Pragyan Rover do its thing
Thanks to AI, rovers like the Mars Exploration Rover and Curiosity have been exploring Mars for over a decade. Similarly, the Pragyan Rover will use an AI algorithm to execute the moves needed to locate relevant samples and then analyze them.

Besides that, the rover’s sensors can detect obstructions such as rocks, craters, and other topological elements. Using AI, it analyses the data from those sensors to draw the best path forward. This ensures the rover can safely pass by without any risk.

Getting Vikram closer to its current orbit
AI has completely changed how satellites and spacecraft such as the Vikram Lander Module traverse space.

Based on inputs from the Vikram Module’s sensors and camera arrays, the onboard AI system determines when to boost itself and apply its air brakes. It also decides when and which direction to turn and by how much.

Analysing Data
The Pragyan Rover and the Vikram Lander will be collecting tons and tons of raw, unprocessed data. Imagine what would have happened if a team of humans had to sit and sift through it and make the data sense.

Analyzing data from space missions is getting a serious upgrade, thanks to machine learning. Those intelligent algorithms can jump in and spot patterns in data collected from satellites and probes. This is handy when looking for anything unusual that might point to exciting discoveries or potential problems.

It can also dig into data trends and give us more astonishing insights than regular old data analysis methods. It can even predict and forecast outcomes, taking space exploration to a new level.

Helping with maintenance
It’s pretty impressive how AI isn’t just limited to handling satellite operations and nailing rocket landings. It’s also got a knack for using all that data to pinpoint spots where things might need maintenance.

These clever machine-learning models can predict when things might go haywire or performance could take a hit. And they’re not just stopping at predictions. They’re giving us solid plans to tackle those potential problems head-on, which cuts down on the chances of things going wrong. This isn’t just about saving money on maintenance – it’s also about keeping the mission and other assets safe and sound.

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