Members Can Post Anonymously On This Site
Sharjah Observatory captured a series of rare impacts on the lunar surface (Video)
-
Similar Topics
-
By NASA
3 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Regolith Adherence Characterization, or RAC, is one of 10 science and technology instruments flying on NASA’s next Commercial Lunar Payload Services (CLPS) flight as part of the Blue Ghost Misison-1. Developed by Aegis Aerospace of Webster, Texas, RAC is designed to study how lunar dust reacts to more than a dozen different types of material samples, located on the payload’s wheels. Photo courtesy Firefly Aerospace The Moon may look like barren rock, but it’s actually covered in a layer of gravel, pebbles, and dust collectively known as “lunar regolith.” During the Apollo Moon missions, astronauts learned firsthand that the fine, powdery dust – electromagnetically charged due to constant bombardment by solar and cosmic particles – is extremely abrasive and clings to everything: gloves, boots, vehicles, and mechanical equipment. What challenges does that dust pose to future Artemis-era missions to establish long-term outposts on the lunar surface?
That’s the task of an innovative science instrument called RAC-1 (Regolith Adherence Characterization), one of 10 NASA payloads flying aboard the next delivery for the agency’s CLPS (Commercial Lunar Payload Services) initiative and set to be carried to the surface by Firefly Aerospace’s Blue Ghost 1 lunar lander.
Developed by Aegis Aerospace of Webster, Texas, RAC will expose 15 sample materials – fabrics, paint coatings, optical systems, sensors, solar cells, and more – to the lunar environment to determine how tenaciously the lunar dust sticks to each one. The instrument will measure accumulation rates during landing and subsequent routine lander operations, aiding identification of those materials which best repel or shed dust. The data will help NASA and its industry partners more effectively test, upgrade, and protect spacecraft, spacesuits, habitats, and equipment in preparation for continued exploration of the Moon under the Artemis campaign.
“Lunar regolith is a sticky challenge for long-duration expeditions to the surface,” said Dennis Harris, who manages the RAC payload for NASA’s CLPS initiative at the agency’s Marshall Space Flight Center in Huntsville, Alabama. “Dust gets into gears, sticks to spacesuits, and can block optical properties. RAC will help determine the best materials and fabrics with which to build, delivering more robust, durable hardware, products, and equipment.”
Under the CLPS model, NASA is investing in commercial delivery services to the Moon to enable industry growth and support long-term lunar exploration. As a primary customer for CLPS deliveries, NASA aims to be one of many customers on future flights. NASA’s Marshall Space Flight Center in Huntsville, Alabama, manages the development of seven of the 10 CLPS payloads carried on Firefly’s Blue Ghost lunar lander.
Learn more about. CLPS and Artemis at:
https://www.nasa.gov/clps
Alise Fisher
Headquarters, Washington
202-358-2546
Alise.m.fisher@nasa.gov
Headquarters, Washington
202-358-2546
Alise.m.fisher@nasa.gov
Corinne Beckinger
Marshall Space Flight Center, Huntsville, Ala.
256-544-0034
corinne.m.beckinger@nasa.gov
Share
Details
Last Updated Dec 20, 2024 EditorBeth RidgewayContactCorinne M. Beckingercorinne.m.beckinger@nasa.govLocationMarshall Space Flight Center Related Terms
Commercial Lunar Payload Services (CLPS) Artemis Marshall Space Flight Center Explore More
3 min read NASA Payload Aims to Probe Moon’s Depths to Study Heat Flow
Article 2 days ago 4 min read NASA Technology Helps Guard Against Lunar Dust
Article 8 months ago 4 min read NASA Collects First Surface Science in Decades via Commercial Moon Mission
Article 10 months ago Keep Exploring Discover Related Topics
Missions
Humans in Space
Climate Change
Solar System
View the full article
-
By NASA
4 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
The six SCALPSS cameras mounted around the base of Blue Ghost will collect imagery during and after descent and touchdown. Using a technique called stereo photogrammetry, researchers at Langley will use the overlapping images to produce a 3D view of the surface. Image courtesy of Firefly. Say cheese again, Moon. We’re coming in for another close-up.
For the second time in less than a year, a NASA technology designed to collect data on the interaction between a Moon lander’s rocket plume and the lunar surface is set to make the long journey to Earth’s nearest celestial neighbor for the benefit of humanity.
Developed at NASA’s Langley Research Center in Hampton, Virginia, Stereo Cameras for Lunar Plume-Surface Studies (SCALPSS) is an array of cameras placed around the base of a lunar lander to collect imagery during and after descent and touchdown. Using a technique called stereo photogrammetry, researchers at Langley will use the overlapping images from the version of SCALPSS on Firefly’s Blue Ghost — SCALPSS 1.1 — to produce a 3D view of the surface. An earlier version, SCALPSS 1.0, was on Intuitive Machines’ Odysseus spacecraft that landed on the Moon last February. Due to mission contingencies that arose during the landing, SCALPSS 1.0 was unable to collect imagery of the plume-surface interaction. The team was, however, able to operate the payload in transit and on the lunar surface following landing, which gives them confidence in the hardware for 1.1.
The SCALPSS 1.1 payload has two additional cameras — six total, compared to the four on SCALPSS 1.0 — and will begin taking images at a higher altitude, prior to the expected onset of plume-surface interaction, to provide a more accurate before-and-after comparison.
These images of the Moon’s surface won’t just be a technological novelty. As trips to the Moon increase and the number of payloads touching down in proximity to one another grows, scientists and engineers need to be able to accurately predict the effects of landings.
How much will the surface change? As a lander comes down, what happens to the lunar soil, or regolith, it ejects? With limited data collected during descent and landing to date, SCALPSS will be the first dedicated instrument to measure the effects of plume-surface interaction on the Moon in real time and help to answer these questions.
“If we’re placing things – landers, habitats, etc. – near each other, we could be sand blasting what’s next to us, so that’s going to drive requirements on protecting those other assets on the surface, which could add mass, and that mass ripples through the architecture,” said Michelle Munk, principal investigator for SCALPSS and acting chief architect for NASA’s Space Technology Mission Directorate at NASA Headquarters in Washington. “It’s all part of an integrated engineering problem.”
Under the Artemis campaign, the agency’s current lunar exploration approach, NASA is collaborating with commercial and international partners to establish the first long-term presence on the Moon. On this CLPS (Commercial Lunar Payload Services) initiative delivery carrying over 200 pounds of NASA science experiments and technology demonstrations, SCALPSS 1.1 will begin capturing imagery from before the time the lander’s plume begins interacting with the surface until after the landing is complete.
The final images will be gathered on a small onboard data storage unit before being sent to the lander for downlink back to Earth. The team will likely need at least a couple of months to
process the images, verify the data, and generate the 3D digital elevation maps of the surface. The expected lander-induced erosion they reveal probably won’t be very deep — not this time, anyway.
One of the SCALPSS cameras is visible here mounted to the Blue Ghost lander.Image courtesy of Firefly. “Even if you look at the old Apollo images — and the Apollo crewed landers were larger than these new robotic landers — you have to look really closely to see where the erosion took place,” said Rob Maddock, SCALPSS project manager at Langley. “We’re anticipating something on the order of centimeters deep — maybe an inch. It really depends on the landing site and how deep the regolith is and where the bedrock is.”
But this is a chance for researchers to see how well SCALPSS will work as the U.S. advances human landing systems as part of NASA’s plans to explore more of the lunar surface.
“Those are going to be much larger than even Apollo. Those are large engines, and they could conceivably dig some good-sized holes,” said Maddock. “So that’s what we’re doing. We’re collecting data we can use to validate the models that are predicting what will happen.”
The SCALPSS 1.1 project is funded by the Space Technology Mission Directorate’s Game Changing Development Program.
NASA is working with several American companies to deliver science and technology to the lunar surface under the CLPS initiative. Through this opportunity, various companies from a select group of vendors bid on delivering payloads for NASA including everything from payload integration and operations, to launching from Earth and landing on the surface of the Moon.
Share
Details
Last Updated Dec 19, 2024 EditorAngelique HerringLocationNASA Langley Research Center Related Terms
General Explore More
4 min read Statistical Analysis Using Random Forest Algorithm Provides Key Insights into Parachute Energy Modulator System
Article 6 hours ago 1 min read Program Manager at NASA Glenn Earns AIAA Sustained Service Award
Article 8 hours ago 2 min read An Evening With the Stars: 10 Years and Counting
Article 8 hours ago Keep Exploring Discover Related Topics
Missions
Humans in Space
Climate Change
Solar System
View the full article
-
By NASA
Congratulations to the selected teams and their schools who will participate in the Lunar Autonomy Challenge! 31 teams were selected for the qualifying round, engaging 229 students from colleges and universities in 15 states. Teams will now move on to a Qualifying Round where they will virtually explore and map the lunar surface using a digital twin of NASA’s lunar mobility robot, the ISRU Pilot Excavator (IPEx). Teams will develop software that can perform set actions without human intervention, navigating the digital IPEx in the harsh, low-light conditions of the Moon. The Qualifying Round will extend to February 28, when the top-scoring teams will proceed to the Final Round, with the winners announced in May 2025.
The Lunar Autonomy Challenge is a collaboration between NASA, The Johns Hopkins University (JHU) Applied Physics Laboratory (APL), Caterpillar Inc., and Embodied AI.
Learn more: https://lunar-autonomy-challenge.jhuapl.edu/
SchoolCityStateAmerican Public University SystemCharles TownWest VirginiaArizona State UniversityTempeArizonaCalifornia Polytechnic Institute, Pomona (1)PomonaCaliforniaCalifornia Polytechnic Institute, Pomona (2)PomonaCaliforniaCarnegie Mellon UniversityPittsburghPennsylvaniaEmbry Riddle Aeronautical UniversityDaytona BeachFloridaEssex County CollegeNewarkNew JerseyGeorgia Institute of Technology & Arizona State UniversityAtlanta & TempeGeorgia & ArizonaHarvard UniversityAllstonMassachusettsJohns Hopkins University Whiting School of EngineeringBaltimoreMarylandMassachusetts Institute of TechnologyCambridgeMassachusettsNew York University Tandon School of EngineeringBrooklynNew YorkNorth Carolina State UniversityRaleighNorth CarolinaPenn State (1)University ParkPennsylvaniaPenn State (2)University ParkPennsylvaniaPurdue UniversityWest LafayetteIndianaRochester Institute of TechnologyRochester New YorkRose Hulman Institue of TechnologyTerre HauteIndianaStanford UniversityStanfordCalifornia Texas A&M UniversityCollege StationTexasUniversity of AlabamaTuscaloosaAlabamaUniversity of Buffalo, State University of New YorkBuffaloNew YorkUniversity of California, StanislausTurlockCaliforniaUniversity of Illinois Urbana Champaign (1)UrbanaIllinoisUniversity of Illinois Urbana Champaign (2)UrbanaIllinoisUniversity of MarylandCollege ParkMarylandUniversity of Pennsylvania (1)Philadelphia PennsylvaniaUniversity of Pennsylvania (2)Philadelphia PennsylvaniaUniversity of Southern California & Stanford UniversityLos Angeles & StanfordCaliforniaWest Virginia UniversityMorgantownWest VirginiaWorcester Polytechnic InstituteWorcesterMassachusetts Keep Exploring Discover More Topics From NASA
Space Technology Mission Directorate
NASA’s Lunar Surface Innovation Initiative
ISRU Pilot Excavator
Education & Opportunities
We are committed to providing educational opportunities for students interested in pursuing professional experiences in the life science disciplines. Our…
View the full article
-
By NASA
2 Min Read Turn Supermoon Hype into Lunar Learning
Caption: The Earth-Moon distance to scale. Credits:
NASA/JPL-Caltech Supermoons get lots of publicity from the media, but is there anything to them beyond the hype? If the term “supermoon” bothers you because it’s not an official astronomical term, don’t throw up your hands. You can turn supermoon lemons into lunar lemonade for your star party visitors by using it to illustrate astronomy concepts and engaging them with great telescopic views of its surface!
Many astronomers find the frequent supermoon news from the media misleading, if not a bit upsetting! Unlike the outrageously wrong “Mars is as big as the moon” pieces that appear like clockwork every two years during Mars’s close approach to Earth, news about a huge full moon is more of an overstatement. The fact is that while a supermoon will indeed appear somewhat bigger and brighter in the sky, it would be difficult to tell the difference between an average full moon and a supermoon with the naked eye.
A whiteboard illustration of Earth’s Moon at perigee, or closest position to Earth. Credit: NASA There are great bits of science to glean from supermoon discussion that can turn supermoon questions into teachable moments. For example, supermoons are a great gateway into discussing the shape of the moon’s orbit, especially the concepts of apogee and perigee. Many people may assume that the moon orbits Earth in a perfect circle, when in fact its orbit is elliptical! The moon’s distance from Earth constantly varies, and so during its orbit it reaches both apogee (when it’s farthest from Earth), as well as perigee (closest to Earth). A supermoon occurs when the moon is at both perigee and in its full phase. That’s not rare; a full moon at closest approach to Earth can happen multiple times a year, as you may have noticed.
This activity is related to a Teachable Moment from Nov. 15, 2017. See “What Is a Supermoon and Just How Super Is It?” Credit: NASA/JPL While a human observer won’t be able to tell the difference between the size of a supermoon and a regular full moon, comparison photos taken with a telephoto lens can reveal the size difference between full moons. NASA has a classroom activity called Measuring the Supermoon where students can measure the size of the full moon month to month and compare their results.
Comparison of the size of an average full moon, compared to the size of a supermoon. NASA/JPL-Caltech Students can use digital cameras (or smartphones) to measure the moon, or they can simply measure the moon using nothing more than a pencil and paper! Both methods work and can be used depending on the style of teaching and available resources.
/wp-content/plugins/nasa-blocks/assets/images/media/media-example-01.jpg This landscape of “mountains” and “valleys” speckled with glittering stars is actually the edge of a nearby, young, star-forming region called NGC 3324 in the Carina Nebula. Captured in infrared light by NASA’s new James Webb Space Telescope, this image reveals for the first time previously invisible areas of star birth. NASA, ESA, CSA, and STScI View the full article
-
By NASA
9 Min Read Towards Autonomous Surface Missions on Ocean Worlds
Artist’s concept image of a spacecraft lander with a robot arm on the surface of Europa. Credits:
NASA/JPL – Caltech Through advanced autonomy testbed programs, NASA is setting the groundwork for one of its top priorities—the search for signs of life and potentially habitable bodies in our solar system and beyond. The prime destinations for such exploration are bodies containing liquid water, such as Jupiter’s moon Europa and Saturn’s moon Enceladus. Initial missions to the surfaces of these “ocean worlds” will be robotic and require a high degree of onboard autonomy due to long Earth-communication lags and blackouts, harsh surface environments, and limited battery life.
Technologies that can enable spacecraft autonomy generally fall under the umbrella of Artificial Intelligence (AI) and have been evolving rapidly in recent years. Many such technologies, including machine learning, causal reasoning, and generative AI, are being advanced at non-NASA institutions.
NASA started a program in 2018 to take advantage of these advancements to enable future icy world missions. It sponsored the development of the physical Ocean Worlds Lander Autonomy Testbed (OWLAT) at NASA’s Jet Propulsion Laboratory in Southern California and the virtual Ocean Worlds Autonomy Testbed for Exploration, Research, and Simulation (OceanWATERS) at NASA’s Ames Research Center in Silicon Valley, California.
NASA solicited applications for its Autonomous Robotics Research for Ocean Worlds (ARROW) program in 2020, and for the Concepts for Ocean worlds Life Detection Technology (COLDTech) program in 2021. Six research teams, based at universities and companies throughout the United States, were chosen to develop and demonstrate autonomy solutions on OWLAT and OceanWATERS. These two- to three-year projects are now complete and have addressed a wide variety of autonomy challenges faced by potential ocean world surface missions.
OWLAT
OWLAT is designed to simulate a spacecraft lander with a robotic arm for science operations on an ocean world body. The overall OWLAT architecture including hardware and software components is shown in Figure 1. Each of the OWLAT components is detailed below.
Figure 1. The software and hardware components of the Ocean Worlds Lander Autonomy Testbed and the relationships between them. NASA/JPL – Caltech The hardware version of OWLAT (shown in Figure 2) is designed to physically simulate motions of a lander as operations are performed in a low-gravity environment using a six degrees-of-freedom (DOF) Stewart platform. A seven DOF robot arm is mounted on the lander to perform sampling and other science operations that interact with the environment. A camera mounted on a pan-and-tilt unit is used for perception. The testbed also has a suite of onboard force/torque sensors to measure motion and reaction forces as the lander interacts with the environment. Control algorithms implemented on the testbed enable it to exhibit dynamics behavior as if it were a lightweight arm on a lander operating in different gravitational environments.
Figure 2. The Ocean Worlds Lander Autonomy Testbed. A scoop is mounted to the end of the testbed robot arm. NASA/JPL – Caltech The team also developed a set of tools and instruments (shown in Figure 3) to enable the performance of science operations using the testbed. These various tools can be mounted to the end of the robot arm via a quick-connect-disconnect mechanism. The testbed workspace where sampling and other science operations are conducted incorporates an environment designed to represent the scene and surface simulant material potentially found on ocean worlds.
Figure 3. Tools and instruments designed to be used with the testbed. NASA/JPL – Caltech The software-only version of OWLAT models, visualizes, and provides telemetry from a high-fidelity dynamics simulator based on the Dynamics And Real-Time Simulation (DARTS) physics engine developed at JPL. It replicates the behavior of the physical testbed in response to commands and provides telemetry to the autonomy software. A visualization from the simulator is shown on Figure 4.
To view this video please enable JavaScript, and consider upgrading to a web browser that
supports HTML5 video
Figure 7. Screenshot of OceanWATERS lander on a terrain modeled from the Atacama Desert. A scoop operation has just been completed. NASA/JPL – Caltech The autonomy software module shown at the top in Figure 1 interacts with the testbed through a Robot Operating System (ROS)-based interface to issue commands and receive telemetry. This interface is defined to be identical to the OceanWATERS interface. Commands received from the autonomy module are processed through the dispatcher/scheduler/controller module (blue box in Figure 1) and used to command either the physical hardware version of the testbed or the dynamics simulation (software version) of the testbed. Sensor information from the operation of either the software-only or physical testbed is reported back to the autonomy module using a defined telemetry interface. A safety and performance monitoring and evaluation software module (red box in Figure 1) ensures that the testbed is kept within its operating bounds. Any commands causing out of bounds behavior and anomalies are reported as faults to the autonomy software module.
Figure 5. Erica Tevere (at the operator’s station) and Ashish Goel (at the robot arm) setting up the OWLAT testbed for use. NASA/JPL – Caltech OceanWATERS
At the time of the OceanWATERS project’s inception, Jupiter’s moon Europa was planetary science’s first choice in searching for life. Based on ROS, OceanWATERS is a software tool that provides a visual and physical simulation of a robotic lander on the surface of Europa (see Figure 6). OceanWATERS realistically simulates Europa’s celestial sphere and sunlight, both direct and indirect. Because we don’t yet have detailed information about the surface of Europa, users can select from terrain models with a variety of surface and material properties. One of these models is a digital replication of a portion of the Atacama Desert in Chile, an area considered a potential Earth-analog for some extraterrestrial surfaces.
Figure 6. Screenshot of OceanWATERS. NASA/JPL – Caltech JPL’s Europa Lander Study of 2016, a guiding document for the development of OceanWATERS, describes a planetary lander whose purpose is collecting subsurface regolith/ice samples, analyzing them with onboard science instruments, and transmitting results of the analysis to Earth.
The simulated lander in OceanWATERS has an antenna mast that pans and tilts; attached to it are stereo cameras and spotlights. It has a 6 degree-of-freedom arm with two interchangeable end effectors—a grinder designed for digging trenches, and a scoop for collecting ground material. The lander is powered by a simulated non-rechargeable battery pack. Power consumption, the battery’s state, and its remaining life are regularly predicted with the Generic Software Architecture for Prognostics (GSAP) tool. To simulate degraded or broken subsystems, a variety of faults (e.g., a frozen arm joint or overheating battery) can be “injected” into the simulation by the user; some faults can also occur “naturally” as the simulation progresses, e.g., if components become over-stressed. All the operations and telemetry (data measurements) of the lander are accessible via an interface that external autonomy software modules can use to command the lander and understand its state. (OceanWATERS and OWLAT share a unified autonomy interface based on ROS.) The OceanWATERS package includes one basic autonomy module, a facility for executing plans (autonomy specifications) written in the PLan EXecution Interchange Language, or PLEXIL. PLEXIL and GSAP are both open-source software packages developed at Ames and available on GitHub, as is OceanWATERS.
Mission operations that can be simulated by OceanWATERS include visually surveying the landing site, poking at the ground to determine its hardness, digging a trench, and scooping ground material that can be discarded or deposited in a sample collection bin. Communication with Earth, sample analysis, and other operations of a real lander mission, are not presently modeled in OceanWATERS except for their estimated power consumption. Figure 7 is a video of OceanWATERS running a sample mission scenario using the Atacama-based terrain model.
To view this video please enable JavaScript, and consider upgrading to a web browser that
supports HTML5 video
Figure 7. Screenshot of OceanWATERS lander on a terrain modeled from the Atacama Desert. A scoop operation has just been completed. NASA/JPL – Caltech Because of Earth’s distance from the ocean worlds and the resulting communication lag, a planetary lander should be programmed with at least enough information to begin its mission. But there will be situation-specific challenges that will require onboard intelligence, such as deciding exactly where and how to collect samples, dealing with unexpected issues and hardware faults, and prioritizing operations based on remaining power.
Results
All six of the research teams funded by the ARROW and COLDTech programs used OceanWATERS to develop ocean world lander autonomy technology and three of those teams also used OWLAT. The products of these efforts were published in technical papers, and resulted in development of software that may be used or adapted for actual ocean world lander missions in the future. The following table summarizes the ARROW and COLDTech efforts.
Principal Investigator (PI) PI Institution Project Testbed Used Purpose of Project ARROW Projects Jonathan Bohren Honeybee Robotics Stochastic PLEXIL (SPLEXIL) OceanWATERS Extended PLEXIL with stochastic decision-making capabilities by employing reinforcement learning techniques. Pooyan Jamshidi University of South Carolina Resource Adaptive Software Purpose-Built for Extraordinary Robotic Research Yields (RASPBERRY SI) OceanWATERS & OWLAT Developed software algorithms and tools for fault root cause identification, causal debugging, causal optimization, and causal-induced verification. COLDTech Projects Eric Dixon Lockheed Martin Causal And Reinforcement Learning (CARL) for COLDTech OceanWATERS Integrated a model of JPL’s mission-ready Cold Operable Lunar Deployable Arm (COLDarm) into OceanWATERS and applied image analysis, causal reasoning, and machine learning models to identify and mitigate the root causes of faults, such as ice buildup on the arm’s end effector. Jay McMahon University of Colorado Robust Exploration with Autonomous Science On-board, Ranked Evaluation of Contingent Opportunities for Uninterrupted Remote Science Exploration (REASON-RECOURSE) OceanWATERS Applied automated planning with formal methods to maximize science return of the lander while minimizing communication with ground team on Earth. Melkior Ornik U Illinois, Urbana-Champaign aDaptive, ResIlient Learning-enabLed oceAn World AutonomY (DRILLAWAY) OceanWATERS & OWLAT Developed autonomous adaptation to novel terrains and selecting scooping actions based on the available image data and limited experience by transferring the scooping procedure learned from a low-fidelity testbed to the high-fidelity OWLAT testbed. Joel Burdick Caltech Robust, Explainable Autonomy for Scientific Icy Moon Operations (REASIMO) OceanWATERS & OWLAT Developed autonomous 1) detection and identification of off-nominal conditions and procedures for recovery from those conditions, and 2) sample site selection Acknowledgements: The portion of the research carried out at the Jet Propulsion Laboratory, California Institute of Technology was performed under a contract with the National Aeronautics and Space Administration (80NM0018D0004). The portion of the research carried out by employees of KBR Wyle Services LLC at NASA Ames Research Center was performed under a contract with the National Aeronautics and Space Administration (80ARC020D0010). Both were funded by the Planetary Science Division ARROW and COLDTech programs.
Project Leads: Hari Nayar (NASA Jet Propulsion Laboratory, California Institute of Technology), K. Michael Dalal (KBR, Inc. at NASA Ames Research Center)
Sponsoring Organizations: NASA SMD PESTO
View the full article
-
-
Check out these Videos
Recommended Posts
Join the conversation
You can post now and register later. If you have an account, sign in now to post with your account.
Note: Your post will require moderator approval before it will be visible.