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By NASA
Software designed to give spacecraft more autonomy could support a future where swarms of satellites navigate and complete scientific objectives with limited human intervention.
Caleb Adams, Distributed Spacecraft Autonomy project manager, monitors testing alongside the test racks containing 100 spacecraft computers at NASA’s Ames Research Center in California’s Silicon Valley. The DSA project develops and demonstrates software to enhance multi-spacecraft mission adaptability, efficiently allocate tasks between spacecraft using ad-hoc networking, and enable human-swarm commanding of distributed space missions. Credit: NASA/Brandon Torres Navarrete Astronauts living and working on the Moon and Mars will rely on satellites to provide services like navigation, weather, and communications relays. While managing complex missions, automating satellite communications will allow explorers to focus on critical tasks instead of manually operating satellites.
Long duration space missions will require teaming between systems on Earth and other planets. Satellites orbiting the Moon, Mars, or other distant areas face communications delays with ground operators which could limit the efficiency of their missions.
The solution lies within the Distributed Spacecraft Autonomy (DSA) project, led by NASA’s Ames Research Center in California’s Silicon Valley, which tests how shared autonomy across distributed spacecraft missions makes spacecraft swarms more capable of self-sufficient research and maintenance by making decisions and adapting to changes with less human intervention.
Adding autonomy to satellites makes them capable of providing services without waiting for commands from ground operators. Distributing the autonomy across multiple satellites, operating like a swarm, gives the spacecraft a “shared brain” to accomplish goals they couldn’t achieve alone.
The DSA software, built by NASA researchers, provides the swarm with a task list, and shares each spacecraft’s distinct perspective – what it can observe, what its priorities are – and integrates those perspectives into the best plan of action for the whole swarm. That plan is supported by decision trees and mathematical models that help the swarm decide what action to take after a command is completed, how to respond to a change, or address a problem.
Sharing the Workload
The first in-space demonstration of DSA began onboard the Starling spacecraft swarm, a group of four small satellites, demonstrating various swarm technologies. Operating since July 2023, the Starling mission continues providing a testing and validation platform for autonomous swarm operations. The swarm first used DSA to optimize scientific observations, deciding what to observe without pre-programmed instructions. These autonomous observations led to measurements that could have been missed if an operator had to individually instruct each satellite.
The Starling swarm measured the electron content of plasma between each spacecraft and GPS satellites to capture rapidly changing phenomena in Earth’s ionosphere – where Earth’s atmosphere meets space. The DSA software allowed the swarm to independently decide what to study and how to spread the workload across the four spacecraft.
Because each Starling spacecraft operates as an independent member within the swarm, if one swarm member was unable to accomplish its work, the other three swarm members could react and complete the mission’s goals.
The Starling 1.0 demonstration achieved several firsts, including the first fully distributed autonomous operation of multiple spacecraft, the first use of space-to-space communications to autonomously share status information between multiple spacecraft, the first demonstration of fully distributed reactive operations onboard multiple spacecraft, the first use of a general-purpose automated reasoning system onboard a spacecraft, and the first use of fully distributed automated planning onboard multiple spacecraft. These achievements laid the groundwork for Starling 1.5+, an ongoing continuation of the satellite swarm’s mission using DSA.
Advanced testing of DSA onboard Starling shows that distributed autonomy in spacecraft swarms can improve efficiencies while reducing the workload on human operators.Credit: NASA/Daniel Rutter A Helping Hand in Orbit
After DSA’s successful demonstration on Starling 1.0, the team began exploring additional opportunities to use the software to support satellite swarm health and efficiency. Continued testing of DSA on Starling’s extended mission included PLEXIL (Plan Execution Interchange Language), a NASA-developed programming language designed for reliable and flexible automation of complex spacecraft operations.
Onboard Starling, the PLEXIL application demonstrated autonomous maintenance, allowing the swarm to manage normal spacecraft operations, correct issues, or distribute software updates across individual spacecraft.
Enhanced autonomy makes swarm operation in deep space feasible – instead of requiring spacecraft to communicate back and forth between their distant location and Earth, which can take minutes or hours depending on distance, the PLEXIL-enabled DSA software gives the swarm the ability to make decisions collaboratively to optimize their mission and reduce workloads.
Simulated Lunar Swarming
To understand the scalability of DSA, the team used ground-based flight computers to simulate a lunar swarm of virtual small spacecraft. The computers simulated a swarm that provides position, navigation, and timing services on the Moon, similar to GPS services on Earth, which rely on a network of satellites to pinpoint locations.
The DSA team ran nearly one hundred tests over two years, demonstrating swarms of different sizes at high and low lunar orbits. The lessons learned from those early tests laid the groundwork for additional scalability studies. The second round of testing, set to begin in 2026, will demonstrate even larger swarms, using flight computers that could later go into orbit with DSA software onboard.
The Future of Spacecraft Swarms
Orbital and simulated tests of DSA are a launchpad to increased use of distributed autonomy across spacecraft swarms. Developing and proving these technologies increases efficiency, decreases costs, and enhances NASA’s capabilities opening the door to autonomous spacecraft swarms supporting missions to the Moon, Mars, and beyond.
Milestones:
October 2018: DSA project development begins. April 2020: Lunar position, navigation, and timing (LPNT) simulation demonstration development begins. July 2023: DSA launches onboard the Starling spacecraft swarm. March 2024: DSA experiments onboard Starling reach the necessary criteria for success. July 2024: DSA software development begins for the Starling 1.5+ mission extension. September 2024: LPNT simulation demonstration concludes successfully. October 2024: DSA’s extended mission as part of Starling 1.5+ begins. Partners:
NASA Ames leads the Distributed Spacecraft Autonomy and Starling projects. NASA’s Game Changing Development program within the agency’s Space Technology Mission Directorate provided funding for the DSA experiment. NASA’s Small Spacecraft Technology program within the Space Technology Mission Directorate funds and manages the Starling mission and the DSA project.
Learn More:
Satellite Swarms for Science ‘Grow up’ at NASA Ames (NASA Story, June 2023) NASA’s Starling Mission Sending Swarm of Satellites into Orbit (NASA Story, July 2023) Swarming for Success: Starling Completes Primary Mission (NASA Story, May 2024) NASA Demonstrates Software ‘Brains’ Shared Across Satellite Swarms (NASA Story, February 2025) For researchers:
Distributed Spacecraft Autonomy Mission Page Distributed Spacecraft Autonomy TechPort Project Page Starling Mission Page For media:
Members of the news media interested in covering this topic should reach out to the NASA Ames newsroom.
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By NASA
Before astronauts venture around the Moon on Artemis II, the agency’s first crewed mission to the Moon since Apollo, Mark Cavanaugh is helping make sure the Orion spacecraft is safe and space-ready for the journey ahead.
As an Orion integration lead at NASA’s Johnson Space Center in Houston, he ensures the spacecraft’s critical systems— in both the U.S.-built crew module and European-built service module—come together safely and seamlessly.
Mark Cavanaugh stands in front of a mockup of the Orion spacecraft inside the Space Vehicle Mockup Facility at NASA’s Johnson Space Center in Houston.NASA/Robert Markowitz With nearly a decade of experience at NASA, Cavanaugh currently works within the Orion Crew and Service Module Office at Johnson. He oversees the technical integration of the European Service Module, which provides power, propulsion, and life support to Orion during Artemis missions to the Moon. His work includes aligning and verifying essential systems to keeping the crew alive, including oxygen, nitrogen, water storage, temperature regulation, and spacecraft structures.
In addition to his integration work, Cavanaugh is an Orion Mission Evaluation Room (MER) manager. The MER is the engineering nerve center during Artemis flights, responsible for real-time monitoring of the Orion spacecraft and real-time decision-making. From prelaunch to splashdown, Cavanaugh will lead a team of engineers who track vehicle health and status, troubleshoot anomalies, and communicate directly with the flight director to ensure the mission remains safe and on track.
Mark Cavanaugh supports an Artemis I launch attempt from the Passive Thermal Control System console on Aug. 29, 2022, in the Orion Mission Evaluation Room at NASA’s Johnson Space Center.NASA/Josh Valcarcel Cavanaugh’s passion for space exploration began early. “I’ve wanted to be an aerospace engineer since I was six years old,” he said. “My uncle, who is also an aerospace engineer, used to take me to wind tunnel tests and flight museums as a kid.”
That passion only deepened after a fifth-grade trip from Philadelphia to Houston with his grandfather. “My dream of working at NASA Johnson started when I visited the center for the first time,” he said. “Going from being a fifth grader riding the tram on the tour to contributing to the great work done at Johnson has been truly incredible.”
Turning that childhood dream into reality did not come with a straight path. Cavanaugh graduated from Pennsylvania State University in 2011, the same year NASA’s Space Shuttle Program ended. With jobs in the space industry in short supply, he took a position with Boeing in Houston, working on the International Space Station’s Passive Thermal Control System. He later supported thermal teams for the Artemis Moon rocket called the Space Launch System, and the Starliner spacecraft that flew astronauts Butch Wilmore and Suni Williams during their Boeing Crew Flight Test mission, before a mentor flagged a NASA job posting that turned out to be the perfect fit.
He joined NASA as the deputy system manager for Orion’s Passive Thermal Control System, eventually stepping into his current leadership role on the broader Orion integration team. “I’ve been very lucky to work with some of the best and most supportive teammates you can imagine,” he said.
Mark Cavanaugh with his mother, Jennifer, in front of the Artemis I Orion spacecraft following the thermal vacuum test at the Space Environments Complex at NASA’s Neil Armstrong Test Facility in Sandusky, Ohio. Cavanaugh says collaboration and empathy were key to solving challenges along the way. “I’ve learned to look at things from the other person’s perspective,” he said. “We’re all working toward the same incredible goal, even if we don’t always agree. That mindset helps keep things constructive and prevents misunderstandings.”
He also emphasizes the importance of creative problem-solving. “For me, overcoming technical challenges comes down to seeking different perspectives, questioning assumptions, and not being afraid to try something new—even if it sounds a little ridiculous at first.”
Mark Cavanaugh riding his motorcycle on the Circuit of the Americas track in Austin, Texas. Outside of work, Cavanaugh fuels his love of speed and precision by riding one of his three motorcycles. He has even taken laps at the Circuit of the Americas track in Austin, Texas.
When he is not on the track or in the control room, Cavanaugh gives back through student outreach. “The thing I always stress when I talk to students is that nothing is impossible,” he said. “I never thought I’d get to work in the space industry, let alone at NASA. But I stayed open to opportunities—even the ones that didn’t match what I originally imagined for myself.”
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By NASA
5 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Cloud cover can keep optical instruments on satellites from clearly capturing Earth’s surface. Still in testing, JPL’s Dynamic Targeting uses AI to avoid imaging clouds, yielding a higher proportion of usable data, and to focus on phenomena like this 2015 volcanic eruption in Indonesia Landsat 8 captured.NASA/USGS A technology called Dynamic Targeting could enable spacecraft to decide, autonomously and within seconds, where to best make science observations from orbit.
In a recent test, NASA showed how artificial intelligence-based technology could help orbiting spacecraft provide more targeted and valuable science data. The technology enabled an Earth-observing satellite for the first time to look ahead along its orbital path, rapidly process and analyze imagery with onboard AI, and determine where to point an instrument. The whole process took less than 90 seconds, without any human involvement.
Called Dynamic Targeting, the concept has been in development for more than a decade at NASA’s Jet Propulsion Laboratory in Southern California. The first of a series of flight tests occurred aboard a commercial satellite in mid-July. The goal: to show the potential of Dynamic Targeting to enable orbiters to improve ground imaging by avoiding clouds and also to autonomously hunt for specific, short-lived phenomena like wildfires, volcanic eruptions, and rare storms.
This graphic shows how JPL’s Dynamic Targeting uses a lookahead sensor to see what’s on a satellite’s upcoming path. Onboard algorithms process the sensor’s data, identifying clouds to avoid and targets of interest for closer observation as the satellite passes overhead.NASA/JPL-Caltech “The idea is to make the spacecraft act more like a human: Instead of just seeing data, it’s thinking about what the data shows and how to respond,” says Steve Chien, a technical fellow in AI at JPL and principal investigator for the Dynamic Targeting project. “When a human sees a picture of trees burning, they understand it may indicate a forest fire, not just a collection of red and orange pixels. We’re trying to make the spacecraft have the ability to say, ‘That’s a fire,’ and then focus its sensors on the fire.”
Avoiding Clouds for Better Science
This first flight test for Dynamic Targeting wasn’t hunting specific phenomena like fires — that will come later. Instead, the point was avoiding an omnipresent phenomenon: clouds.
Most science instruments on orbiting spacecraft look down at whatever is beneath them. However, for Earth-observing satellites with optical sensors, clouds can get in the way as much as two-thirds of the time, blocking views of the surface. To overcome this, Dynamic Targeting looks 300 miles (500 kilometers) ahead and has the ability to distinguish between clouds and clear sky. If the scene is clear, the spacecraft images the surface when passing overhead. If it’s cloudy, the spacecraft cancels the imaging activity to save data storage for another target.
“If you can be smart about what you’re taking pictures of, then you only image the ground and skip the clouds. That way, you’re not storing, processing, and downloading all this imagery researchers really can’t use,” said Ben Smith of JPL, an associate with NASA’s Earth Science Technology Office, which funds the Dynamic Targeting work. “This technology will help scientists get a much higher proportion of usable data.”
How Dynamic Targeting Works
The testing is taking place on CogniSAT-6, a briefcase-size CubeSat that launched in March 2024. The satellite — designed, built, and operated by Open Cosmos — hosts a payload designed and developed by Ubotica featuring a commercially available AI processor. While working with Ubotica in 2022, Chien’s team conducted tests aboard the International Space Station running algorithms similar to those in Dynamic Targeting on the same type of processor. The results showed the combination could work for space-based remote sensing.
Since CogniSAT-6 lacks an imager dedicated to looking ahead, the spacecraft tilts forward 40 to 50 degrees to point its optical sensor, a camera that sees both visible and near-infrared light. Once look-ahead imagery has been acquired, Dynamic Targeting’s advanced algorithm, trained to identify clouds, analyzes it. Based on that analysis, the Dynamic Targeting planning software determines where to point the sensor for cloud-free views. Meanwhile, the satellite tilts back toward nadir (looking directly below the spacecraft) and snaps the planned imagery, capturing only the ground.
This all takes place in 60 to 90 seconds, depending on the original look-ahead angle, as the spacecraft speeds in low Earth orbit at nearly 17,000 mph (7.5 kilometers per second).
What’s Next
With the cloud-avoidance capability now proven, the next test will be hunting for storms and severe weather — essentially targeting clouds instead of avoiding them. Another test will be to search for thermal anomalies like wildfires and volcanic eruptions. The JPL team developed unique algorithms for each application.
“This initial deployment of Dynamic Targeting is a hugely important step,” Chien said. “The end goal is operational use on a science mission, making for a very agile instrument taking novel measurements.”
There are multiple visions for how that could happen — possibly even on spacecraft exploring the solar system. In fact, Chien and his JPL colleagues drew some inspiration for their Dynamic Targeting work from another project they had also worked on: using data from ESA’s (the European Space Agency’s) Rosetta orbiter to demonstrate the feasibility of autonomously detecting and imaging plumes emitted by comet 67P/Churyumov-Gerasimenko.
On Earth, adapting Dynamic Targeting for use with radar could allow scientists to study dangerous extreme winter weather events called deep convective ice storms, which are too rare and short-lived to closely observe with existing technologies. Specialized algorithms would identify these dense storm formations with a satellite’s look-ahead instrument. Then a powerful, focused radar would pivot to keep the ice clouds in view, “staring” at them as the spacecraft speeds by overhead and gathers a bounty of data over six to eight minutes.
Some ideas involve using Dynamic Targeting on multiple spacecraft: The results of onboard image analysis from a leading satellite could be rapidly communicated to a trailing satellite, which could be tasked with targeting specific phenomena. The data could even be fed to a constellation of dozens of orbiting spacecraft. Chien is leading a test of that concept, called Federated Autonomous MEasurement, beginning later this year.
How AI supports Mars rover science Autonomous robot fleet could measure ice shelf melt Ocean world robot swarm prototype gets a swim test News Media Contact
Melissa Pamer
Jet Propulsion Laboratory, Pasadena, Calif.
626-314-4928
melissa.pamer@jpl.nasa.gov
2025-094
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Last Updated Jul 24, 2025 Related Terms
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By NASA
A NASA-sponsored team is creating a new approach to measure magnetic fields by developing a new system that can both take scientific measurements and provide spacecraft attitude control functions. This new system is small, lightweight, and can be accommodated onboard the spacecraft, eliminating the need for the boom structure that is typically required to measure Earth’s magnetic field, thus allowing smaller, lower-cost spacecraft to take these measurements. In fact, this new system could not only enable small spacecraft to measure the magnetic field, it could replace the standard attitude control systems in future spacecraft that orbit Earth, allowing them to provide the important global measurements that enable us to understand how Earth’s magnetic field protects us from dangerous solar particles.
Photo of the aurora (taken in Alaska) showing small scale features that are often present. Credit: NASA/Sebastian Saarloos
Solar storms drive space weather that threatens our many assets in space and can also disrupt Earth’s upper atmosphere impacting our communications and power grids. Thankfully, the Earth’s magnetic field protects us and funnels much of that energy into the north and south poles creating aurorae. The aurorae are a beautiful display of the electromagnetic energy and currents that flow throughout the Earth’s space environment. They often have small-scale magnetic features that affect the total energy flowing through the system. Observing these small features requires multiple simultaneous observations over a broad range of spatial and temporal scales, which can be accomplished by constellations of small spacecraft.
To enable such constellations, NASA is developing an innovative hybrid magnetometer that makes both direct current (DC) and alternating current (AC) magnetic measurements and is embedded in the spacecraft’s attitude determination and control system (ADCS)—the system that enables the satellite to know and control where it is pointing. High-performance, low SWAP+C (low-size, weight and power + cost) instruments are required, as is the ability to manufacture and test large numbers of these instruments within a typical flight build schedule. Future commercial or scientific satellites could use these small, lightweight embedded hybrid magnetometers to take the types of measurements that will expand our understanding of space weather and how Earth’s magnetic field responds to solar storms
It is typically not possible to take research-quality DC and AC magnetic measurements using sensors within an ADCS since the ADCS is inside the spacecraft and near contaminating sources of magnetic noise such as magnetic torque rods—the electromagnets that generate a magnetic field and push against the Earth’s magnetic field to control the orientation of a spacecraft. Previous missions that have flown both DC and AC magnetometers placed them on long booms pointing in opposite directions from the satellite to keep the sensors as far from the spacecraft and each other as possible. In addition, the typical magnetometer used by an ADCS to measure the orientation of the spacecraft with respect to the geomagnetic field does not sample fast enough to measure the high-frequency signals needed to make magnetic field observations.
A NASA-sponsored team at the University of Michigan is developing a new hybrid magnetometer and attitude determination and control system (HyMag-ADCS) that is a low-SWAP single package that can be integrated into a spacecraft without booms. HyMag-ADCS consists of a three-axis search coil AC magnetometer and a three-axis Quad-Mag DC magnetometer. The Quad-Mag DC magnetometer uses machine learning to enable boomless DC magnetometery, and the hybrid search-coil AC magnetometer includes attitude determination torque rods to enable the single 1U volume (103 cm) system to perform ADCS functions as well as collect science measurements.
The magnetic torque rod and search coil sensor (left) and the Quad-Mag magnetometer prototype (right). Credit: Mark Moldwin The HyMag-ADCS team is incorporating the following technologies into the system to ensure success.
Quad-Mag Hardware: The Quad-Mag DC magnetometer consists of four magneto-inductive magnetometers and a space-qualified micro-controller mounted on a single CubeSat form factor (10 x 10 cm) printed circuit board. These two types of devices are commercially available. Combining multiple sensors on a single board increases the instrument’s sensitivity by a factor of two compared to using a single sensor. In addition, the distributed sensors enable noise identification on small satellites, providing the science-grade magnetometer sensing that is key for both magnetic field measurements and attitude determination. The same type of magnetometer is part of the NASA Artemis Lunar Gateway Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) Noisy Environment Magnetometer in a Small Integrated System (NEMISIS) magnetometer scheduled for launch in early 2027.
Dual-use Electromagnetic Rods: The HyMag-ADCS team is using search coil electronics and torque rod electronics that were developed for other efforts in a new way. Use of these two electronics systems enables the electromagnetic rods in the HyMag-ADCS system to be used in two different ways—as torque rods for attitude determination and as search coils to make scientific measurements. The search coil electronics were designed for ground-based measurements to observe ultra-low frequency signals up to a few kHz that are generated by magnetic beacons for indoor localization. The torque rod electronics were designed for use on CubeSats and have flown on several University of Michigan CubeSats (e.g., CubeSat-investigating Atmospheric Density Response to Extreme driving [CADRE]). The HyMag-ADCS concept is to use the torque rod electronics as needed for attitude control and use the search coil electronics the rest of the time to make scientific AC magnetic field measurements.
Machine Learning Algorithms for Spacecraft Noise Identification: Applying machine learning to these distributed sensors will autonomously remove noise generated by the spacecraft. The team is developing a powerful Unsupervised Blind Source Separation (UBSS) algorithm and a new method called Wavelet Adaptive Interference Cancellation for Underdetermined Platforms (WAIC-UP) to perform this task, and this method has already been demonstrated in simulation and the lab.
The HyMag-ADCS system is early in its development stage, and a complete engineering design unit is under development. The project is being completed primarily with undergraduate and graduate students, providing hands-on experiential training for upcoming scientists and engineers.
Early career electrical engineer Julio Vata and PhD student Jhanene Heying-Melendrez with art student resident Ana Trujillo Garcia in the magnetometer lab testing prototypes. Credit: Mark Moldwin For additional details, see the entry for this project on NASA TechPort .
Project Lead: Prof. Mark Moldwin, University of Michigan
Sponsoring Organization: NASA Heliophysics Division’s Heliophysics Technology and Instrument Development for Science (H-TIDeS) program.
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Last Updated Jun 17, 2025 Related Terms
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By NASA
NASA Teams responsible for preparing and launching Artemis II at NASA’s Kennedy Space Center in Florida are set to begin a series of integrated tests to get ready for the mission. With the upper stage of the agency’s SLS (Space Launch System) integrated with other elements of the rocket, engineers are set to start the tests to confirm rocket and ground systems are working and communicating as planned.
While similar to the integrated testing campaign conducted for NASA’s uncrewed Artemis I test flight, engineers have added tests ahead of Artemis II to prepare for NASA’s first crewed flight under the Artemis campaign – an approximately 10-day journey by four astronauts around the Moon and back. The mission is another step toward missions on the lunar surface and helping the agency prepare for future astronaut missions to Mars.
Interface Verification Testing
Verifies the functionality and interoperability of interfaces across elements and systems. Teams will conduct this test from the firing room in the Launch Control Center and perform health and status checks of various systems and interfaces between the SLS core stage, the solid rocket boosters, and the ground systems. It will ensure different systems, including core stage engines and booster thrust control, work as planned. Teams also will perform the same series of tests with the interim cryogenic propulsion stage and Orion before conducting a final interface test with all segments.
Program Specific Engineering Test
Teams will conduct separate engineering tests for the core stage, rocket boosters, and upper stage following the interface verification tests for each part of the rocket.
End-to-End Communications Testing
Integrated test of SLS core and upper stages, and Orion command and telemetry radio frequencies with mission control at NASA’s Johnson Space Center in Houston to demonstrate flight controllers’ ability to communicate with the ground systems and infrastructure. This test uses a radio frequency antenna in the Vehicle Assembly Building (VAB), another near the launch pad that will cover the first few minutes of launch, as well as a radio frequency that use the Tracking Data Relay Satellite and the Deep Space Network. Teams will do two versions of this test – one with the ground equipment communicating with a radio and telemetry station for checkouts, and one with all the hardware and equipment communicating with communications infrastructure like it will on launch day.
Countdown Demonstration Test
Teams will conduct a launch day demonstration with the Artemis II astronauts to test launch countdown procedures and make any final necessary adjustments ahead of launch. This test will be divided into two parts. The first will be conducted while SLS and Orion are in the VAB and include the Artemis II crew departing their crew quarters after suiting up at the Neil A. Armstrong Operations and Checkout Building and driving to the VAB where they will enter Orion like they will on launch day and practice getting strapped in. Part two will be completed once the rocket is at the launch pad and will allow the astronauts and Artemis launch team to practice how to use the emergency egress system, which would be used in the event of an unlikely emergency at the launch pad during launch countdown.
Flight Termination System End-to-End Test
Test to ensure the rocket’s flight termination system can be activated in the event of an emergency. For public safety, all rockets are required to have a flight termination system. This test will be divided into two parts inside the VAB. The first will take place ahead of Orion getting stacked atop SLS and the second will occur before the rocket and spacecraft roll out to the launch pad.
Wet Dress Rehearsal
Teams will practice loading cryogenic liquid propellant inside SLS once it’s at the launch pad and run through the launch countdown sequences just prior to engine ignition. The rehearsal will run the Artemis II launch team through operations to load liquid hydrogen and liquid oxygen into the rocket’s tanks, conduct a full launch countdown, demonstrate the ability to recycle the countdown clock, and also drain the tanks to give them an opportunity to practice the timelines and procedures they will use for launch.
Teams will load more than 700,000 gallons of cryogenic, or super cold, propellants into the rocket at the launch pad on the mobile launcher according to the detailed timeline they will use on the actual launch day. They will practice every phase of the countdown, including weather briefings, pre-planned holds in the countdown, conditioning and replenishing the propellants as needed, and validation checks. The Artemis II crew will not participate in the rehearsal.
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