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NASA’s Commercial Lunar Payload Services (CLPS) are bringing us closer than we’ve been in decades to regular lunar exploration and scientific discovery. As a scientist, I admire what these companies have achieved and support their continued efforts.
Yet, beyond landing safely, it’s crucial to remember that these missions exist to deliver critical scientific payloads that will enable groundbreaking research. CLPS has notably ushered in a new era by embracing higher risks in exchange for lower costs. But before we rush into discussions about expanding the CLPS model for commercial lander companies, we should consider something equally important: applying the same iterative, multiple-attempt mindset to low-cost scientific instruments and missions themselves. After all, scientific discovery is one of the key reasons to go to the moon in the first place.
All NASA science instruments and missions, regardless of their cost and risk profile, are selected based on their scientific merit. In other words, the science questions themselves aren’t inherently low- or high-cost, the cost primarily factors into the way the mission is implemented. Low-cost missions or instrument opportunities are offered through NASA’s PRISM (Payloads and Research Investigations on the Surface of the Moon), PRISM SALSA (Payloads and Research Investigations on the Surface of the Moon: Stand Alone Landing Site Agnostic) and the SIMPLEx (Small Innovative Missions for Planetary Exploration) programs.
Investigations proposed to these calls must address critical scientific questions identified by the planetary science community itself, outlined in guiding documents like the Planetary Decadal Survey or community-defined science exploration objectives. The evaluation of instruments and missions proposed to higher-cost, more risk-averse programs, like New Frontiers or Discovery (typically Class A) is no different from a low-cost mission. Whether it’s a small Class D mission or a large flagship Class A mission, if the science questions a mission addresses are deemed valuable enough to fund, the importance of getting answers to those questions shouldn’t diminish just because the mission was implemented on a low-cost platform. And especially not if the mission or instrument encounters setbacks or achieves partial success.
A CLPS model for science
Pursuing scientific exploration through multiple smaller, lower-cost missions can actually be more cost-effective than relying solely on one large Flagship or Discovery-class mission. But we need missions of every class. There’s a time and place for risk-taking and there are times when more caution is necessary; it’s a balance that requires careful consideration.
In most cases, if a mission opportunity is offered as low-cost, then it would by definition benefit from adopting the same iterative mindset as the CLPS lunar landing missions, which reduce risk through increased redundancy, resilience and the ability to learn and improve from experience. This could be implemented through an iterative model that incorporates optional reflights directly into initial proposals, establishing dedicated funding or opportunities specifically for follow-up attempts, requiring spare hardware upfront, or collaborating with partners for cost-effective secondary flight opportunities. Encouragingly, NASA appears to be taking small but meaningful steps in this direction.
For example, the recent PRISM-SALSA solicitation asked proposers to estimate the cost of rebuilding their payloads in the event NASA opts to fly a second (or more) copy on a future mission, an explicit acknowledgment of the value in planning for repeat flights. While this cost is currently outside the solicitation’s cap, making this type of planning a more central and supported element of future solicitations would be an excellent way to build resilience and continuity into the low-cost science pipeline.
The reality of conducting ambitious science missions at reduced costs with deliberately higher risk typically means we can’t just reach for existing instruments. They’re often too expensive, too big, or incompatible with the constraints of smaller spacecraft. Instead, mission teams have to innovate by creating new, simpler instruments that can achieve similar scientific results within tighter constraints.
The challenge is that developing lower-cost instruments typically involves more uncertainty. Unlike established, flight-proven instruments, new technologies require real-world experience in flight to become reliable. Science teams therefore need multiple opportunities to fly and test their instruments. In science and in engineering, flight provides valuable experience and data, allowing teams to incrementally refine their designs, reduce uncertainties, and eventually achieve reliable, robust science returns at substantially lower costs.
Moreover, a significant fraction of a mission’s total cost is concentrated in the initial design and development phase. When those foundational efforts are already complete, a reattempted mission, especially one with clear lessons learned and improved oversight, can be implemented far more efficiently. This not only helps salvage previous investments but also creates long-term cost savings across NASA’s science portfolio. If we want low-cost exploration missions to deliver meaningful and consistent scientific results, we need to explicitly adopt this iterative, multiple-attempt mindset not just for commercial lunar landers, but also for the science instruments these missions carry. Otherwise, we’re asking teams to develop and implement innovative, low-cost instrumentation perfectly on their very first try, a strategy that is unrealistic and ultimately limits our ability to advance scientific discovery.
Multiple shots on goal
Recently, NASA and other international space agencies have taken some small steps toward a lower-cost science model, having funded several new and innovative types of missions, both science-driven and technology-focused. Examples like MarCO, LICIACube, ArgoMoon, Equuleus, OMOTENASHI, Lunar Flashlight, LunaH-Map, BioSentinel, NEA Scout, Lunar IceCube, Lunar Trailblazer, all the scientific payloads launched on Astrobotic Peregrine-1 and Intuitive Machines IM-1 mission and IM-2 missions that were not able to demonstrate full success, all perfectly illustrate exactly why a shift in approach is important to consider right now. Despite varying degrees of success, and even in the case of failure, these missions have spurred significant advancements in spacecraft miniaturization, propulsion, communications, scientific instrumentation and deep-space navigation.
Equally vital, they’ve trained a new generation of engineers, scientists and students who are developing essential tools and technologies for future missions, at a fraction of the cost of a much larger mission. Yet under the current system, these talented teams only got one chance. If things don’t go perfectly, their accumulated knowledge and technology becomes sidelined, fragmented or completely lost. Perhaps more importantly, when LunaH-Map, Lunar Flashlight, Lunar IceCube, or Lunar Trailblazer’s prime missions to locate and quantify lunar water ice were lost and when the VIPER rover launch slipped, it didn’t make the underlying science any less vital, in fact DARPA’s new Lunar Assay via Small-Satellite Orbiter (LASSO) solicitation literally exists because someone still has to get that water map.
It’s hard to understand why NASA is not giving the science teams that have already flown another chance, particularly given how inexpensive these missions are compared to traditional ones. And especially given the opening statement by Chairman Brian Babin (R-Texas) at the Congressional Hearing on Leveraging Commercial Innovation for Lunar Exploration:
“NASA reduces its risk exposures by selecting CLPS payloads that are scientifically valuable yet smaller and more cost-effective — then it distributes them across multiple missions,” he said at the April 1 hearing. “NASA understands and accepts the possibility that a CLPS mission may fail, an approach informally referred to as taking ‘shots on goal.’”
For science investigations, we’re instead applying a “one-shot on goal” mindset. These are the very science missions that will produce the data we need for future missions to be successful, to build a long-lasting exploration program, and to fully capitalize on the very innovations the CLPS program is intended to deliver.
On the flip side, NASA has specifically selected commercial lunar companies and given them multiple attempts, clearly demonstrating the value of learning and iterating:
- Intuitive Machines: Intuitive Machines’ Nova-C lunar lander, Odysseus, achieved a landmark soft landing in 2024, the first by the U.S. in over five decades. Even though Odysseus landed on its side, the mission was largely successful, providing critical data. NASA selected them again for a follow-up mission in March 2025, which achieved partial success, and they have another NASA-funded mission planned for 2026.
- Astrobotic Technology: Although the Peregrine Mission One never reached the moon and ended with a controlled reentry after ten days, NASA recognized the valuable lessons learned and selected them again for another mission planned for late 2025.
- Firefly Aerospace: NASA chose Firefly’s Blue Ghost lander, which successfully landed on Mare Crisium in March 2025 and operated for an impressive 14 days. NASA has selected Firefly for at least two more missions scheduled for 2026 and 2028.
These examples demonstrate how NASA’s deliberate strategy of allowing multiple attempts enables commercial companies to refine technologies, learn from setbacks and boost their odds of ultimate success. Unfortunately, scientific missions rarely receive this same targeted support, which stifles innovation and wastes hard-earned experience.
The incremental cost of additional attempts pales in comparison to the enormous long-term benefits. Imagine a small lunar cubesat designed to characterize polar ice deposits. The entire mission could be developed and flown for a fraction of the cost of a larger-scale mission. Even if this cubesat encounters difficulties and achieves only partial success, it would still provide a clear path forward by revealing critical lessons. Under a CLPS-inspired iterative model, a follow-up flight could already be budgeted, planned, or at least available as an option. This approach allows the team to directly implement improvements, significantly increasing their odds of achieving their mission objectives and fully realizing the original scientific goals, rather than simply waiting years for another lunar ice-probe mission opportunity to emerge. At such low costs, you could even iterate multiple times and still spend only about 25 to 35 percent of what a single, larger mission would cost.
Building redundancies
Just as NASA selects multiple CLPS providers to independently tackle similar landing objectives, maximizing overall mission success, it could similarly fund multiple teams pursuing complementary or overlapping science goals. This diversified approach fosters collaboration, accelerates learning and ensures scientific objectives remain robust despite setbacks.
There are several practical ways to implement a more iterative, multi-attempt model for science investigations. For instance, NASA could explicitly incorporate optional reflights into initial Announcements of Opportunity (AOs), allowing teams to plan and budget for multiple launches from the start. Another viable strategy could be establishing dedicated reflight AOs available exclusively to teams who’ve demonstrated a viable path toward success despite initial challenges. Alternatively, NASA might require missions to construct flight spare instruments or even spacecraft (recall these might be cubesats) that could later be used for follow-up flights, leveraging existing investments with minimal extra cost. Additionally, NASA could establish a dedicated “Rapid Response” funding pool for quick-turnaround follow-up missions, or implement phased funding based on incremental mission milestones, or partner with industry or academic institutions to enable “ride-along” opportunities for reflight payloads, significantly reducing cost and logistical challenges.
Without adopting this flexible, iterative approach, we’ll continue a frustrating cycle of inefficiency: talented teams and promising technologies will keep fading away after single-mission setbacks, resulting in lost opportunities and scattered expertise. Sure, setbacks are nothing new in engineering or space exploration, but with these smaller missions, it’s especially disheartening to see teams who put in enormous effort achieve remarkable breakthroughs, only to watch their progress vanish in an instant. Thoughtfully applying the iterative, CLPS-inspired model to low-cost science isn’t just smart, it’s essential if we’re serious about building a dynamic, productive and genuinely sustainable future for lunar exploration.
Craig Hardgrove is a planetary scientist and professor specializing in planetary geology and physics. He has extensive experience working on NASA interplanetary spacecraft missions and currently serves as an instrument scientist for NASA’s Lunar-VISE mission and a Participating Scientist on the Mars Science Laboratory Curiosity rover. Hardgrove was the Principal Investigator for the NASA LunaH-Map mission, which launched on SLS Artemis-1.
This article first appeared in the May 2025 issue of SpaceNews Magazine.
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