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Lunar Advancements – Robotics and AI For Autonomous Exploration
AI-Driven Robotics for Autonomous Space Exploration
One day, space exploration might make use of astronauts living permanently on site, as envisioned by the Artemis missions for the Moon, or by Elon Musk for Mars. Still, even with human presence, a lot of the work in space will be done by robots, if nothing else, because they are a lot easier to replace than human astronauts and a lot less vulnerable to toxic air or vacuum, radiation, brutal temperatures, etc.
Ideally, most of the rovers and robots should be able to handle themselves for simple tasks, with humans on Earth or on-site only involved to help them solve specific problems or determine their daily missions.
As AI progresses quickly, including physical AI, a concept now championed by AI leader NVIDIA, this science-fiction vision might already be a reality.
Scientists are taking the first steps in that direction, both in research projects on Earth and with existing rovers on Mars, with two news items related to this topic in the past few days.
The first one was that NASA has deployed AI assistance to guide the Martian rover Perseverance.
The second one is that researchers at the University of Malaga (Spain), the German Research Center for Artificial Intelligence (DFKI), Sorbonne Université (France), as well as the private companies GMV Aerospace and Defence S.A, Magellium, and Space Applications Services are deploying robots in Earth lava tubes that resemble similar structures on the Moon and Mars1.
Perseverance Rover’s AI-Assisted Autonomous Navigation
NASA’s First AI-Planned Rover Drives on Mars
NASA’s Perseverance Mars rover hit a new scientific milestone as it completed the first drives on another world that were planned by artificial intelligence. Announced recently, the move was done on December 8th and 10th, 2025.
The demonstration used generative AI to create waypoints for Perseverance, a complex decision-making task typically performed manually by the mission’s human rover planners.
Source: NASA
This could prove to be a game-changer for Martian exploration. The extreme distance between Earth and Mars (140 million miles / 225 million kilometers) means that light-lag causes a signal lag, which means that every instruction takes 3-22 minutes (depending on orbital positions) to arrive at Mars from Earth, and feedback then takes the same time again.
As NASA scientists are very cautious to avoid getting the multi-billion dollar project stuck in dust or damaged by a rock, this makes any movement a tedious crawl.
“Rover routes have been planned and executed by human drivers, who analyze the terrain and status data to sketch a route using waypoints, which are usually spaced no more than 330 feet (100 meters) apart to avoid any potential hazards.
Then they send the plans via NASA’s Deep Space Network to the rover, which executes them.”
Instead, Perseverance did something new for its 1,707 and 1,709 days on the Martian surface, letting the rover decide where to go using AI.
How It Worked
It used generative AI to analyse the high-resolution orbital imagery from the HiRISE (High Resolution Imaging Science Experiment) camera aboard NASA’s Mars Reconnaissance Orbiter and terrain-slope data from digital elevation models.
Combined with data from previous explorations, this allowed the AI to identify terrain features like bedrock, outcrops, hazardous boulder fields, sand ripples, etc.
“The fundamental elements of generative AI are showing a lot of promise in streamlining the pillars of autonomous navigation for off-planet driving: perception (seeing the rocks and ripples), localization (knowing where we are), and planning and control (deciding and executing the safest path).”
Vandi Verma – A space roboticist at JPL and a member of the Perseverance engineering team.
The AI model used was Claude, provided by Anthropic, which recently made headlines for potentially disrupting the entire SaaS and software industry, causing a mini stock market crash in this sector.
This AI-guided travel helped Perseverance capture images in its two-hour 30-minute autonomous drive along Jezero Crater’s rim.
AI can also be useful in processing the data generated by space probes and reducing the workload of the robot operators.
No doubt this will be extra useful when actual astronauts are near the robot as well, as by then, AI might be more capable.
“We are moving towards a day where generative AI and other smart tools will help our surface rovers handle kilometer-scale drives while minimizing operator workload, and flag interesting surface features for our science team by scouring huge volumes of rover images.”
Vandi Verma – A space roboticist at JPL and a member of the Perseverance engineering team.
In addition, a human presence and logistical support will let NASA operators take more risks, as a robot stuck in dust could be freed manually, instead of causing a catastrophic multi-billion-dollar loss and years of research frozen.
“This demonstration shows how far our capabilities have advanced and broadens how we will explore other worlds.
Autonomous technologies like this can help missions to operate more efficiently, respond to challenging terrain, and increase science return as distance from Earth grows.”
Jared Isaacman – NASA Administrator
Testing AI On Earth’s Lava Tubes
Why Lava Tubes
While AI deployment on Mars is a groundbreaking first, NASA researchers are understandably cautious in risking a unique asset like Perseverance in an AI experiment. For example, no matter how efficient the AI, it would never take the chance of deploying the robot beyond what could be fixed by a human teleoperator in case something goes wrong.
This is why experimenting with terrains analog to what is found in space, but with Earth resources available nearby, is important as well.
The most important possible terrain on the Moon and Mars is lava tubes, which form natural caves that could form natural shelters for the first astronauts to protect them from cosmic radiation. And thanks to these stellar objects’ lower gravity, lava tubes there tend to be larger than they ever could be on Earth.
Lava tubes can naturally have spots that caved in, leading to holes in the ground providing direct access for exploration.
However, no offworld lava tubes have ever been explored, in large part due to the fact that direct control is impaired by the rock blocking any radio signal.
Testing Robots
The European research team used three different robots working together to explore these extreme underground environments autonomously.
Source: ResearchGate
They deployed their test in the volcanic caves/lava tubes of Lanzarote (Canary Islands).
