A New Way to Prepare Samples of Mars for Return to the Earth
Mars 2020’s strategy to cache samples is evolving as the mission matures
Mars 2020, NASA’s next and yet-to-be-named Mars rover, will be the first mission to collect and prepare samples of the martian surface for return to Earth. This process is known as caching, and it is the crucial first step of a fully-born sample return campaign that could define the next two decades of robotic Mars exploration. Recently, the Mars 2020 engineering team proposed a new caching strategy that differs from previous concepts in some interesting ways.
JPL calls this adaptive caching, but I like to think of it more as the cache depot strategy. This means that after coring samples and placing them into hermetically-sealed tubes (the same process for any sort of caching), the rover will then deposit groups of samples on the ground throughout its drive. A future rover would retrieve some or all of these samples, place them in a rocket, and launch them into Mars orbit.
Casey Dreier / JPL-Caltech
The adaptive caching cycle proposed for the Mars 2020 rover
After landing, the rover would drill and store soil samples in sealed tubes. At the team’s discretion, groups of these sample tubes would be placed at strategic ‘cache depots’ for a future retrieval mission. This can repeat as needed until the Mars 2020 is out of sampling tubes.
Now, this wasn’t always the idea. For years, caching concepts focused on a single repository for the samples, essentially a high-tech bucket that would hold 30 or so tubes in a honeycomb pattern. This would then be dropped off at a single location for future retrieval.
Here’s an example of this “cache bucket” concept from the European Space Agency:
A concept design for a Mars sample cache container
This would hold all of the samples in one container, which would be loaded into a rocket and launched into Mars orbit to await a return to Earth.
It sounds straightforward, right? Drill some rock samples, seal them in a sample tube, and stick the tubes in a caching bucket, and set it on the ground for a future mission to grab and launch into space. Honeybee Robotics has a video depicting this basic concept for a Curiosity-like rover:
But it wasn’t until teams of engineers and scientists started to think about the scientific goals and the risk factors of a single caching storage system that people began to realize this may not be the best way to go.
Think of the following scenario: a hypothetical Mars 2020 rover is on the surface. It has 31 empty sample tubes that it can fill, but “mission success” is defined as collecting 20 different samples (this comes right from the actual science definition team’s report for the mission, by the way).
With the old-style cache bucket, you hit an interesting problem once you reach your minimum success goal of 20 samples. By definition: the mission is now a “success.” You have a treasure trove of samples that you could set on the ground for future collection, but you could also fill it with 11 more samples of indeterminate importance. You don’t know what or how important these samples could be, since you’d have to continue looking for interesting rocks to drill. But every meter you rove carries with it risk: risk of breaking down, risk of getting stuck in sand, risk of a computer malfunction, you name it. Despite JPL making it look easy to operate a rover on Mars, it’s not.
So there would be an enormous amount of pressure to drop the cache container once minimum success is reached. Do you cash out your winnings or let it ride? Even if you kept going, the levels of risk that the team would accept for roving to interesting places would be very low. This risk-aversion would increase with every sample collected beyond the minimum success point.
With the adaptive cache (or cache depot) strategy, you don’t have the same problem. You just tell the rover to drop the 20 samples on the surface, effectively creating a cache depot at that spot on Mars (the rover can carry a certain number of sample tubes with it while it drives). The rover then continues on to other interesting places where it can drill additional samples, safe in the knowledge that it has already deposited a successful mission’s worth for future retrieval.
There are additional practical benefits for the cache depot strategy. Since Mars 2020 would no longer be limited by the size of a cache bucket designed to return every sample to Earth, the rover could bring along more sample tubes to use throughout the mission. And since the samples are deposited frequently, which frees the rover to go on in search of more science, the team would have more time in which to debate which samples to return. Without this, the team would have to decide far more quickly about where to drill with less contextual information about the overall geology of the landing site.
If there will be a retrieval rover to grab these samples, it will face a similar problem of minimum success criteria for sample retrieval. But the risks it would face are different. Unlike Mars 2020, which would simultaneously explore, sample, and cache, the retrieval rover would travel over known terrain. It would likely travel to a single cache depot—or just a few of the most promising cache depots—to gather the previously-collected samples and place them in the return rocket.
The evolution of caching from its original single-container concept—a concept, I should mention, that’s been around for years—to the adaptive cache strategy illustrates the natural process of designing a mission. It’s only when you really get down and dirty with a problem that these types of subtle complexities arise.
Mars 2020 is maturing into a real mission. There are teams of people working every day to solve the practical, irritating problems of exploring Mars and storing samples for eventual return to Earth. Adaptive caching is the most visible example of one of the many thousands of clever solutions, compromises, and workarounds that every mission must face to succeed in exploring our solar system. The very fact that we face (and solve!) these problems is, in itself, remarkable.