Four-Legged Robots Prepare For Autonomous Mars Exploration

One day, space exploration might make use of astronauts living permanently offworld, 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 needed 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.

For even more distant missions, like on Jupiter’s moons, the time lag in communication, up to 1 hour long, makes any direct control even more tricky, making any autonomous decision by the probes extra valuable.

“Rovers are designed for energy efficiency and safety, and to move slowly across hazardous terrain. As a result, exploration is typically limited to only a small portion of the landing site, with rovers typically traveling up to a few hundreds of meters per day, which makes it difficult to collect geologically diverse data.”

Another step will be giving space exploration robots more ability to move freely. After all, wheels and tracks might be more reliable, but it’s not like roads are waiting for them on the Moon and Mars.

As a result, most robotic exploration missions so far have focused on relatively flat, easily navigable regions. But these areas might also not be the most useful for future space colonization.

For example, lava tubes might make perfect pre-built shelters for future astronauts, but we never explored one properly, although AI-driven exploration of lava tubes is being planned. And most resources are likely to be found in deep craters (water) or mountainous regions (metals and other mineral deposits).

“On the Moon, many key resources are located in terrain that is difficult to access, including volatile- and titanium-rich pyroclastic deposits, REE-bearing KREEP basalts, and water ice within permanently shadowed regions near the South Pole. On Mars, water-ice exposures and metal-rich regolith have also been identified in high-latitude and highland regions, often within unstable slopes or fractured geological settings.”

So more advanced robots are needed, with quadrupedal “robodogs” a likely option, as this design is becoming increasingly popular on Earth as well.

This possibility is being tested by Swiss researchers at the ETH Zurich, the University of Zurich, the Neuchâtel Space Exploration Institute, the University of Basel, and the University of Bern.

They used a quadrupedal robot, they tested if it could handle semi-autonomous exploration and sample collection in a reconstructed space environment, and published their findings in Frontiers In Space Technologies¹, under the title “Semi-autonomous exploration of martian and lunar analogues with a legged robot using a Raman-equipped robotic arm and microscopic image”.

Recreating Mars On Earth

The researchers used the Marslabor facility at the University of Basel, which simulates planetary surface conditions using analogue rocks, regolith (planetary dust), and analogue lighting conditions to recreate an environment identical to Mars’ except for the gravity.

Marslabor encompasses an 80 m2 room featuring a 40 m2 test bed composed of Martian analogue materials. This included rocks with a strong potential for biosignature preservation, like gypsum or carbonate rock, which would be of major interest in a real Martian exploration looking to investigate past biological activity on the Red Planet.

Source: Frontiers In Space Technologies

In addition, rock types indicative of past flowing water, like siliciclastic carbonate rock and sulphur-bearing basalt, were also included.

A segment of the room was also recreating lunar conditions, with rock types that could be a useful source of oxides, titanium, aluminum, and silicon.

Four-Legged Explorers

Polyvalent Robot With Sensors

The robot used in this study was an ANYmal robot built by the Swiss company ANYbotics, specialized in industrial inspections in hazardous areas. To enable mapping and localization, ANYmal is equipped with a VLP-16 Puck LITE LiDAR by Velodyne, six RealSense D435 active stereo sensors by Intel for elevation mapping, and two FLIR Blackfly wide-angle cameras to provide RGB image streams.

Source: Frontiers In Space Technologies

The robot was equipped with a microscopic imager (MICRO) and a MIRA RTX Raman spectrometer produced by the Swiss company Metrohm. These sensors were installed on a robotic arm developed in-house by the ETH (Eidgenössische Technische Hochschule – Swiss Federal Institute of Technology).

It was remotely controlled by an operator using a graphical user interface (GUI) that shows a digital elevation map and camera images where commands and tasks are transmitted.

Source: Frontiers In Space Technologies

The MICRO imager’s goal is to capture close-up images of the rock samples’ texture, grain, and color, a crucial dataset to identify the type of rock and its composition. It incorporates a USB microscope, a ring of 48 RGB LEDs, a time-of-flight (ToF) sensor, and control electronics. A foam ring prevented stray light from entering when MICRO is in contact with a target.

The Raman spectrometer featured an infra-red excitation laser with a wavelength of 785 nm and a maximum power of 100 mW, with a range spanning from 400 to 2,300 cm with a resolution of 8–10 cm. The data complement the MICRO observation by revealing the chemical composition of the studied rocks.

Source: Frontiers In Space Technologies

Investigation with & Without Humans

Two operational concepts for robotic scientific surveying: one with classical human control, and the other with multi-target, semi-autonomous sampling with minimal human intervention.

In the human-assisted method, the operator identified a target in the camera image and selected a navigation waypoint in the graphical GUI. Then, the operator could immediately review the incoming data and decide whether additional measurements were needed. The operator also chose how many Raman measurements were deployed and determined their specific locations on the rock.

In the semi-autonomous method, predefined commands were given in advance to the robot, including locomotion, waypoint navigation, instrument deployment, and data return. Once the instructions were uploaded, the robot executed all tasks autonomously, from movement to robotic arm deployment and science measurements.

After completing the measurement sequence at each target, the robot autonomously continued its execution cycle, moving to the next target and saving data after each measurement. Only once measurements were completed for all targets would the robot transmit the collected data to the base station.

Source: Frontiers In Space Technologies

The results of the analysis confirmed the usefulness of combining different instruments, with the combination of Raman and MICRO analysis increasing the chance of properly identifying a given rock.

The semi-autonomous method identified correctly at least 1/3rd of targets per cycle, achieving 100% target identification in one out of four analogue missions. Multi-target missions took between 12 and 23 minutes, while a human-guided mission required 41 minutes to complete comparable analyses.

So while results were less perfect, much more successful analysis could be conducted per minute, leading to more efficiency overall. So this experience confirmed that more autonomous robots could rapidly survey large areas of planetary surfaces.

In addition, once identified, an interesting sample can then be manually analyzed by the scientists in further investigation.

“Instead of relying solely on large and complex instrument suites, future missions could deploy agile robots that rapidly scan the environment and flag promising targets for detailed investigation.”

Improving Robotic Exploration

The researchers also noted that the tools deployed were all developed with direct human control in mind. This means that the semi-autonomous robot sometimes suffered from off-target arm placement, leading to blurred MICRO images or too noisy Raman data.

An improved system could instead redo the test with slight automated arm adjustments in case of blurred images or poor spectrometry data. Further automation programs could help as well.

“To move to an even higher level of autonomy, the robots could detect targets of interest autonomously based on shape, colour, and texture. In scenarios where the data transmission is very slow (e.g., in the outer solar system), the robot could then autonomously take measurements of these targets. ”

This system also did not make use of recent advances in AI, which could give the robots much greater autonomy in the future, as we discussed in “Space 2.0: The Rise of Autonomous Robots and AI“. So, even more advanced protocols of detection and then scanning could bring more efficient and autonomous measurement. From there, training a specialized AI model on real data from robots on Mars or the Moon could make future generations of probes even more efficient.

Investing In Space Robotics

Intuitive Machines

Sending autonomous probes to interstellar objects is going to require a strong expertise in building large space probes and making them arrive in the right place intact. For now, this has been mostly the domain of public institutions like NASA, the ESA, and associated universities.

This is changing as we are getting closer to the point where private companies could start sending automated or manned missions to mine asteroids, especially near-Earth objects. This sort of project will likely be the next step or done in parallel to the return of manned missions to the Moon, planned for the upcoming years.

Founded in 2013 in Houston, Texas, Intuitive Machines is, for now, a very “Moon-focused” company, as indicated by its stock ticker LUNR, and has already been selected for 4 NASA lunar missions, and employs 400+ people.

Source: Intuitive Machines

It was the first commercial company to successfully land and transmit scientific data from the Moon. It also performed the 1st firing of the LOx/LCH4 (liquid oxygen, liquid methane) engine in space. The company is working on many projects that will form the base of a lunar infrastructure for exploration and settlement.

The first one is the “data transmission service”, with the technology being tested, and ultimately looking to end with a lunar data transmission constellation around the Moon’s orbit.

Source: Intuitive Machines

The second part is the “Infrastructure as a Service”. It should include telecommunication services, GPS localization services, and a Lunar Surface Vehicles (LTV) capable of autonomous operations.

Source: Intuitive Machines

The last segment is the delivery of material to the lunar surface. So far, the company has delivered scientific payloads with the Nova-C lander, a 4.3-meter-tall lander (14-feet) able to deliver 130kg of payload to the Moon.

The next step will be with the Nova-D lander, able to deliver 1,500-2,500 kg of material to the Moon. This payload capacity and size will be the one required for delivery of the Lunar Terrain Vehicle (LTV), as well as the 40kW Fission Surface Power nuclear reactor expected to power the Moon base.

Source: Intuitive Machines

The company has landed many valuable contracts with NASA, for example, the Near Space Network contract, with a maximum potential value of $4.82B. The LTV contract final decision by NASA between the 3 potential suppliers is expected for the end of 2025, and would be worth up to $4.6B as well.

Besides NASA, the company is trying to diversify its client base, having been selected in April 2025 for a grant of up to $10M by the Texas Space Commission.

This will support the development of an Earth reentry vehicle and orbital fabrication lab designed to enable microgravity biomanufacturing. This reentry vehicle will also provide a backup option and reduce risks for the Company’s future lunar sample return missions.

Another project is the development of low-power nuclear stealth satellites for an Air Force research laboratory JETSON contract.

As the company reaches a positive free cash flow point in Q1 2025, and with the lunar telecommunication contract, it is now becoming a lot safer for investors, moving away from a cash-burning startup to an established services provider to the growing space economy.

And it could form the building block of further deep space exploration and utilization of space resources, especially as it becomes a trusted partner of NASA on par with SpaceX (soon to IPO after its merger with xAI) or Rocket Lab (RKLB ).

(You can read more about Intuitive Machines in our investment report dedicated to the company.)

Latest Intuitive Machines (LUNR) Stock News and Developments

Study Referenced

^{1. Gabriela Ligeza, Philip Arm, et al. Semi-autonomous exploration of martian and lunar analogues with a legged robot using a Raman-equipped robotic arm and microscopic imager. Frontier Space Technologies, 31 March 2026. Volume 7 – 2026 | https://doi.org/10.3389/frspt.2026.1741757}