NASA is developing key technologies to send astronauts to Mars as early as the 2030s. The crucial “stop” between Earth and the Red Planet is the Moon, which serves as an essential testing ground for space technologies that will eventually enable human settlements on other planets.
In recent years, lunar exploration has seen a resurgence, with missions such as China’s sample return missions Chang’e-5 in 2020 and Chang’e-6 in 2024, and India’s Chandrayaan-3 successfully landing on the Moon in 2023. The U.S. has accelerated its efforts through NASA’s Artemis program, aiming to return humans to the lunar surface by 2028—over 50 years since their first Moon landing. Moreover, private company Intuitive Machines became the first to successfully land on the Moon, marking a shift from the traditionally government-led missions.
These programs heavily depend on robotics to carry out vital tasks, from resource extraction to infrastructure construction. As robotic systems become increasingly sophisticated, they are expected to lead the way in making lunar exploration both sustainable and scalable for future missions.
How Robotics Makes Space More Affordable
The Apollo 11 mission, which first took human to the Moon, was insanely expensive. According to The Planetary Society, inflation-adjusted cost of the mission would be $3 billion. Five more crewed landings took place on the Moon between late 1969 and late 1972, with ever more ambitious goals and achievements, including the crewed LRV rover on the last three missions.
“Over time, space projects became more affordable, in many ways thanks to the decreasing price of hardware that is used for the space missions, launch budget, etc,” explains Lyubomyr Demkiv, Director of Robotics and Advanced Automation at SoftServe.
Sending robots into space is far more cost-effective and practical than sending astronauts. Robots don't need food, sleep, or bathroom breaks, and they can remain in space for years without the need for a return trip.
Moreover, robots can endure extreme environments that would be too hazardous for humans. They can withstand high radiation levels, intense temperatures, and perform tasks that would be too dangerous or impossible for astronauts.
Technology is evolving. Robotic rovers have been exploring the Moon’s surface to better understand its characteristics and potential. However, the rugged terrain in some areas is too challenging for current rovers to collect crucial data effectively.
SoftServe is working on an alternative solution: free-flying vehicles, or lunar drones, that offer greater mobility for mapping the Moon’s surface. These rocket thruster-propelled drones can fly over regions that traditional rovers struggle with, providing precise data needed for future planetary exploration, in particular for resource prospecting.
“Using the Moon’s low gravity and lack of atmosphere, these drones can traverse large distances," adds Lutz Richter, Space Projects Expert at SoftServe. “Our guidance system for a 70 kg lunar drone enables cost-efficient lunar exploration through precise control-powered flight, seamless landings, and takeoffs. Equipped with vision-based navigation and a SLAM algorithm, it autonomously maps terrain and navigates predefined targets, making lunar missions more affordable.”
The Power Of Simulation
To develop space technologies effectively, engineers must rely on simulation. It allows them to test and optimize robotic systems in realistic virtual environments, avoiding the high costs and risks associated with real-world trials.
“To make it more effective, we always suggest a simulation-first approach, where the system is designed, tested, and validated in simulation before real-life experiments," says Mariusz Janiak, (Co-)simulation and Optimization Expert at SoftServe Poland.
High-fidelity models closely mimic real-world behavior, enabling businesses to explore "what-if" scenarios and optimize performance before building physical prototypes. SoftServe has embraced a simulation-first approach in the development of lunar drones, modeling the entire flight behavior and visual SLAM-based guidance system, including all necessary sensors. Lunar terrain simulations were based on satellite datasets, and using physical AI and visualization tools, engineers generated 3D point clouds and images, later compiled into a comprehensive 3D map of the environment.
Another example of simulation is construction technologies for the Moon as part of a four-company consortium led by Astroport Space Technologies of San Antonio, Texas. NASA has invested $1.3 million in the project, in which SoftServe is responsible for modeling robots that will build a spaceport on the Moon. This involves extensive digital simulations of the construction process, factoring in the unique features and properties of lunar soil.
What Are The Main Challenges In Robotics?
Over the past three years, more than 40 companies have entered the space robotics sector, attracting over $200 million in venture capital. Recognized as an emerging technology by GlobalData, space robotics has one of the fastest-growing innovation rates in the space industry and is transforming sectors like manufacturing, healthcare, and logistics through optimized operations and cost reductions.
A recent PIE study shows that 77% of SMEs in Poland view robotization as a key competitive advantage.
However, this growth comes with challenges. Robotics and industrial automation are inherently multidisciplinary, requiring knowledge in various fields like physics, engineering, programming, and in some cases also chemistry. “We don’t focus on just one area,” says Mariusz Janiak. “One day we might be simulating spacecraft temperature distribution along the mission, the next, optimizing an industrial pressing machine operation.” His team must deliver sophisticated, research-driven solutions, often within tight three-month timelines.
A shortage of qualified experts compounds these challenges. "Typically, those people work at universities, but the industry needs fast, practical solutions," adds Mariusz Janiak. To become robotics expert, a specialist needs a mix of academic expertise—physics, math, and control theory—and business knowledge to translate technical solutions into cost-effective applications.
