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NASA NTRS2012

NASA's Desert RATS Science Backroom: Remotely Supporting Planetary Exploration

NASA's Desert Research and Technology Studies (Desert RATS) is a multi-year series of tests designed to exercise planetary surface hardware and operations in conditions where long-distance, multi-day roving is achievable. In recent years, a D-RATS science backroom has conducted science operations and tested specific operational approaches. Approaches from the Apollo, Mars Exploration Rovers and Phoenix missions were merged to become the baseline for these tests. In 2010, six days of lunar-analog traverse operations were conducted during each week of the 2-week test, with three traverse days each week conducted with voice and data communications continuously available, and three traverse days conducted with only two 1-hour communications periods per day. In 2011, a variety of exploration science scenarios that tested operations for a near-earth asteroid using several small exploration vehicles and a single habitat. Communications between the ground and the crew in the field used a 50-second one-way delay, while communications between crewmembers in the exploration vehicles and the habitat were instantaneous. Within these frameworks, the team evaluated integrated science operations management using real-time science operations to oversee daily crew activities, and strategic level evaluations of science data and daily traverse results. Exploration scenarios for Mars may include architectural similarities such as crew in a habitat communicating with crew in a vehicle, but significantly more autonomy will have to be given to the crew rather than step-by-step interaction with a science backroom on Earth.

Cohen, Barbara A.↗
NASA NTRSDate not supplied

Science Backroom Support for Sustained Lunar Surface

Sustained surface operations on the lunar surface will be supported by the Foundational Surface Habitat (FSH) at the Artemis Base Camp. Planning for FSH is still preliminary but includes notional science outfitting that will enable lunar science and support the science conducted during EVA traverses.

Geolab↗
NASA NTRS2013

Next-generation Strategies for Human Lunar Sorties

The science community has had success in remote field experiences using two distinctly different models for humans-in-the-loop: the Apollo Science Support team (science backroom), and the robotic exploration of Mars. In the Apollo experience, the science team helped train the crew, designed geologic traverses, and made real-time decisions by reviewing audio and video transmissions and providing recommendations for geologic sampling. In contrast, the Mars Exploration Rover (MER) and Mars Science Lab (MSL) missions have been conducted entirely robotically, with significant time delays between science- driven decisions and remote field activities. Distinctive operations methods and field methodologies were developed for MER/MSL [1,2] because of the reliance on the "backroom" science team (rather than astronaut crew members) to understand the surroundings. Additionally, data are relayed to the team once per day, giving the team many hours or even days to assimilate the data and decide on a plan of action.

Cohen, B. A.↗
NASA NTRS2014

Real-Time Science Operations to Support a Lunar Polar Volatiles Rover Mission

Future human exploration of the Moon will likely rely on in situ resource utilization (ISRU) to enable long duration lunar missions. Prior to utilizing ISRU on the Moon, the natural resources (in this case lunar volatiles) must be identified and characterized, and ISRU demonstrated on the lunar surface. To enable future uses of ISRU, NASA and the CSA are developing a lunar rover payload that can (1) locate near subsurface volatiles, (2) excavate and analyze samples of the volatile-bearing regolith, and (3) demonstrate the form, extractability and usefulness of the materials. Such investigations are important both for ISRU purposes and for understanding the scientific nature of these intriguing lunar volatile deposits. Temperature models and orbital data suggest near surface volatile concentrations may exist at briefly lit lunar polar locations outside persistently shadowed regions. A lunar rover could be remotely operated at some of these locations for the approx. 2-14 days of expected sunlight at relatively low cost. Due to the limited operational time available, both science and rover operations decisions must be made in real time, requiring immediate situational awareness, data analysis, and decision support tools. Given these constraints, such a mission requires a new concept of operations. In this paper we outline the results and lessons learned from an analog field campaign in July 2012 which tested operations for a lunar polar rover concept. A rover was operated in the analog environment of Hawaii by an off-site Flight Control Center, a rover navigation center in Canada, a Science Backroom at NASA Ames Research Center in California, and support teams at NASA Johnson Space Center in Texas and NASA Kennedy Space Center in Florida. We find that this type of mission requires highly efficient, real time, remotely operated rover operations to enable low cost, scientifically relevant exploration of the distribution and nature of lunar polar volatiles. The field demonstration illustrated the need for science operations personnel in constant communications with the flight mission operators and the Science Backroom to provide immediate and continual science support and validation throughout the mission. Specific data analysis tools are also required to enable immediate data monitoring, visualization, and decision making. The field campaign demonstrated that this novel methodology of real-time science operations is possible and applicable to providing important new insights regarding lunar polar volatiles for both science and exploration.

Moon; Volatiles; Rover; Missions↗
NASA NTRS2009

Science Operations for the 2008 NASA Lunar Analog Field Test at Black Point Lava Flow, Arizona

Surface science operations on the Moon will require merging lessons from Apollo with new operation concepts that exploit the Constellation Lunar Architecture. Prototypes of lunar vehicles and robots are already under development and will change the way we conduct science operations compared to Apollo. To prepare for future surface operations on the Moon, NASA, along with several supporting agencies and institutions, conducted a high-fidelity lunar mission simulation with prototypes of the small pressurized rover (SPR) and unpressurized rover (UPR) (Fig. 1) at Black Point lava flow (Fig. 2), 40 km north of Flagstaff, Arizona from Oct. 19-31, 2008. This field test was primarily intended to evaluate and compare the surface mobility afforded by unpressurized and pressurized rovers, the latter critically depending on the innovative suit-port concept for efficient egress and ingress. The UPR vehicle transports two astronauts who remain in their EVA suits at all times, whereas the SPR concept enables astronauts to remain in a pressurized shirt-sleeve environment during long translations and while making contextual observations and enables rapid (less than or equal to 10 minutes) transfer to and from the surface via suit-ports. A team of field geologists provided realistic science scenarios for the simulations and served as crew members, field observers, and operators of a science backroom. Here, we present a description of the science team s operations and lessons learned.

Garry W. D.↗
NASA NTRSDate not supplied

An Optimization Approach to Support Science Decision Making for Lunar Surface Exploration

Introduction: Scientific exploration is one of the three pillars of NASA’s Moon2Mars architecture, with crew surface extra vehicular activities (EVA) serving a critical enabling function. Development of surface EVA operational planning and execution, specifically integrating science and flight control teams (FCT), is currently being explored through analog scenarios. This integration, exercised, for example, through the Joint EVA and Hu-man Surface Mobility Test Team (JETT), allows for science input on EVA activities in near real-time through a Science Evaluation Room (SER), or Arte-mis science backroom, which integrates with the broader FCT through the Science Officer. The SER works within the FCT to support dynamic EVA planning in response to changes in operational constraints as well as science opportunities and re-prioritization, increasing the mission science return and accelerating the accomplishment of the Moon2Mars science objectives. The SER works within the FCT to provide recommendations to traverse execution in near real-time. One challenge is the requirement to deliver SER inputs to the FCT on operationally relevant timelines. Failure to do so may result in suboptimal execution of science exploration EVAs or even loss of key science objectives. To close this gap, we present a network optimization tool to allow the SER to provide rapid input to the FCT in response to changes in operational constraints or science opportunities. Inputs are predicated on approved science objectives, and clear rationale must be provided to the FCT for any requested change. Accordingly, this tool incorporates the Science Traceability Matrix (STM), SER prioritization scheme, and station characterization and action planning with operational constraints such as duration, traverse speed, and distance to maximize science objectives based on SER priorities, consistent with FCT operational requirements. Method: As a proof of concept, we used an existing linear programing software package used to simulate optimal routes through cellular metabolism. We built a Demonstrative Model with three STM objectives and four stations on a region of the Moon. The objectives were given an arbitrary prioritization and mapped to the stations through four possible crew actions. (Figs. 1 and 2). This station to STM mapping is consistent with the method used by the JETT5 Science Team to develop analog surface EVA science planning. We used a grid system with the landing site at the origin and the four stations placed across the positive x,y quadrant. Actions were assigned to each station and the accomplishment of those actions resulted in a numerical “reward” based on the ability of that action to achieve science objectives. The aggregate reward from each individual STM objective contributes to a global score (Science Yield), weighted by its priority. Operational constraints included a requirement to start and end at the landing site, 5 minutes each for initial station characterization and “clean up,” and variable total EVA time, traverse rate (fixed to 0.5 meters per second in our example), and time to perform each action (10, 5, 7, and 15 min for actions 1, 2, 3, and 4, respectively). Additional constraints and variables will be added in the future (e.g., sample mass, number of stations, traverse route constraints, illumination). Optimization. We converted the connections (arcs) between these stations (nodes) into a mixed integer linear programming optimization problem (arcs = constraints, nodes = variables) with the objective to maximize Science Yield. For any action, the Science Yield is equal to the relevance of that action to an STM objective [3, 2, and 1 point(s) for High, Med., and Low relevance, respectively], multiplied by the STM Objective Priority [3, 2, and 1 point(s) for High, Med., and Low priority, respectively]. This resulted in a model that computes the optimal station and action combination to maximize the Science Yield. These weightings can be adjusted by the SER as desired. Results: We explored three test cases for the Demonstrative Model. First, we set the maximum EVA duration to 120 minutes and computed the optimal route (Fig. 3A). The model suggested per-forming Actions 1 and 2 at Station P01, followed by Actions 1 and 2 at Station P02, and finally Actions 1 and 3 at Station P04 before returning to the Landing Site. Second, we adjusted the STM Objective Priori-ty order and computed the new optimal route (Fig. 3B). Under this situation, the model suggested per-forming all Actions at Station P02 followed by all Actions at Station P03. The previous test cases were relevant to SER planning activities. Next, we explored providing mid-EVA replanning input to the FCT. Scenario: While executing the Route in Fig. 3A the crew finishes at Station P01 and FCT decides that the EVA needs to finish in 45 minutes back at the Landing Site. FCT asks SER to recommend changes to the plan to accommodate this operation-al change. Using the model and incorporating these new constraints (start at Station P01, max. time of 45 min), the model suggested performing Actions 2 and 4 at Station P03 (Fig. 4), requiring 41 minutes to complete and return to the Landing Site. Interestingly, Station 3 was not part of the original route. Using the model, we determined the EVA would need 66 minutes, instead of 45, in order for the original Station P04 to yield a larger Science Yield than Station P03. The parametrization and simulation was per-formed in less than a minute, demonstrating the operational relevance of the approach. Future Efforts: The results from the Demonstrative Model suggest this tool can accelerate SER decision making on operationally relevant timelines. Use in analog activities, such as JETT5 or follow-ons, which have over a dozen stations for a crew to explore and over a dozen actions per station, will provide needed validation of the utility of this tool for planning EVAs, replanning mid-EVA, or planning follow-on EVAs based on previous results. Further integration with FCT execution monitoring tools may provide additional efficiency gains, al-lowing rapid and iterative exploration of operation-al and science decision space by the FCT and SER.

Science Operations↗
NASA NTRS2016

Analog Testing of Operations Concepts for Mitigation of Communication Latency During Human Space Exploration

OBJECTIVES: NASA Extreme Environment Mission Operations (NEEMO) is an underwater spaceflight analog that allows a true mission‐like operational environment and uses buoyancy effects and added weight to simulate different gravity levels. Three missions were undertaken from 2014‐2015, NEEMO's 18‐20. All missions were performed at the Aquarius undersea research habitat. During each mission, the effects of varying operations concepts and tasks type and complexity on representative communication latencies associated with Mars missions were studied. METHODS: 12 subjects (4 per mission) were weighed out to simulate near‐zero or partial gravity extravehicular activity (EVA) and evaluated different operations concepts for integration and management of a simulated Earth‐based science backroom team (SBT) to provide input and direction during exploration activities. Exploration traverses were planned in advance based on precursor data collected. Subjects completed science‐related tasks including presampling surveys, geologic‐based sampling, and marine‐based sampling as a portion of their tasks on saturation dives up to 4 hours in duration that were to simulate extravehicular activity (EVA) on Mars or the moons of Mars. One‐way communication latencies, 5 and 10 minutes between space and mission control, were simulated throughout the missions. Objective data included task completion times, total EVA times, crew idle time, translation time, SBT assimilation time (defined as time available for SBT to discuss data/imagery after it has been collected, in addition to the time taken to watch imagery streaming over latency). Subjective data included acceptability, simulation quality, capability assessment ratings, and comments. RESULTS: Precursor data can be used effectively to plan and execute exploration traverse EVAs (plans included detailed location of science sites, high‐fidelity imagery of the sites, and directions to landmarks of interest within a site). Operations concepts that allow for presampling surveys enable efficient traverse execution and meaningful Mission Control Center (MCC) interaction across long communication latencies and can be done with minimal crew idle time. Imagery and information from the EVA crew that is transmitted real‐time to the intravehicular (IV) crewmember(s) can be used to verify that exploration traverse plans are being executed correctly. That same data can be effectively used by MCC (across comm latency) to provide further instructions to the crew from a SBT on sampling priorities, additional tasks, and changes to the plan. Text / data capabilities are preferred over voice capabilities between MCC and IV when executing exploration traverse plans over communication latency. Autonomous crew planning tools can be effective at modifying existing plans if the objectives and constraints are clearly defined.

Chappell, Steven P.↗
NASA NTRS2015

Pre-Mission Input Requirements to Enable Successful Sample Collection by a Remote Field/EVA Team

This paper is intended to evaluate the sample collection process with respect to sample characterization and decision making. In some cases, it may be sufficient to know whether a given outcrop or hand sample is the same as or different from previous sampling localities or samples. In other cases, it may be important to have more in-depth characterization of the sample, such as basic composition, mineralogy, and petrology, in order to effectively identify the best sample. Contextual field observations, in situ/handheld analysis, and backroom evaluation may all play a role in understanding field lithologies and their importance for return. For example, whether a rock is a breccia or a clast-laden impact melt may be difficult based on a single sample, but becomes clear as exploration of a field site puts it into context. The FINESSE (Field Investigations to Enable Solar System Science and Exploration) team is a new activity focused on a science and exploration field based research program aimed at generating strategic knowledge in preparation for the human and robotic exploration of the Moon, near-Earth asteroids (NEAs) and Phobos and Deimos. We used the FINESSE field excursion to the West Clearwater Lake Impact structure (WCIS) as an opportunity to test factors related to sampling decisions. In contract to other technology-driven NASA analog studies, The FINESSE WCIS activity is science-focused, and moreover, is sampling-focused, with the explicit intent to return the best samples for geochronology studies in the laboratory. This specific objective effectively reduces the number of variables in the goals of the field test and enables a more controlled investigation of the role of the crewmember in selecting samples. We formulated one hypothesis to test: that providing details regarding the analytical fate of the samples (e.g. geochronology, XRF/XRD, etc.) to the crew prior to their traverse will result in samples that are more likely to meet specific analytical objectives than samples collected in the absence of this premission information. We conducted three tests of this hypothesis. Our investigation was designed to document processes, tools and procedures for crew sampling of planetary targets. This is not meant to be a blind, controlled test of crew efficacy, but rather an effort to recognize the relevant variables that enter into sampling protocol and to develop recommendations for crew and backroom training in future endeavors. Methods: One of the primary FINESSE field deployment objectives was to collect impact melt rocks and impact melt-bearing breccias from a number of locations around the WCIS structure to enable high precision geochronology of the crater to be performed [1]. We conducted three tests at WCIS after two full days of team participation in field site activities, including using remote sensing data and geologic maps, hiking overland to become familiar with the terrain, and examining previously-collected samples from other islands. In addition, the team members shared their projects and techniques with the entire team. We chose our "crew members" as volunteers from the team, all of whom had had moderate training in geologic fieldwork and became familiar with the general field setting. The first two tests were short, focused tests of our hypothesis. Test A was to obtain hydrothermal vugs; Test B was to obtain impact melt and intrusive rock as well as the contact between the two to check for contact metamorphism and age differences. In both cases, the test director had prior knowledge of the site geology and had developed a study-specific objective for sampling prior to deployment. Prior to the field deployment, the crewmember was briefed on the sampling objective and the laboratory techniques that would be used on the samples. At the field sites (Fig. 2), the crewmember was given 30 minutes to survey a small section of outcrop (10-15 m) and acquire a suite of three samples. The crewmember talked through his process and the test director kept track of the timeline in verbal cues to the crewmember. At the conclusion, the team member conducting the scientific study appraised the samples and train of thought. Test C was a 90-minute EVA simulation using two crewmembers working out of line-of-sight in communication with a science backroom. The science objectives were determined by the science backroom team in advance using a Gigapan image of the outcrop (Fig. 1). The science team formulated hypotheses for the outcrop units and created sampling objectives for impact-melt lithologies; the science team turned these into a science plan, which they communicated to the crew in camp prior to crew deployment. As part of the science plan, the science team also discussed their sample needs in depth with the crewmembers, including laboratory methods, objectives, and samples sizes needed. During the deployment, the two crewmembers relayed real-time information to the science backroom by radio with no time delay. Both the crew and science team re-evaluated their hypotheses and science plans in real-time. Discussion: Upon evaluation, we found that the focused tests (Tests A and B) were successful in meeting their scientific objectives. The crewmember used their knowledge of how the samples were to be used in further study (technique, sample size, and scientific need) to focus on the sampling task. The crewmember was comfortable spending minimal time describing and mapping the outcrop. The crewmember used all available time to get a good sample. The larger test was unsuccessful in meeting the sampling objectives. When the crewmembers began describing the lithologies, it was quickly apparent that the lithologies were not as the backroom expected and had communicated to the crew. When the outcrop wasn't as expected, the crew members instinctively switched to field characterization mode, taking significant time to characterize and map the outcrop. One crew member admitted that he "kind of lost track" of the sampling strategy as he focused on the basic outcrop characterization. This is the logical first step in a field geology campaign, that a significant amount of time must be spent by the crew and backroom to understand the outcrop and its significance. Basic field characterization of an outcrop is a focused activity that takes significant time and training [2, 3]. Sampling of representational lithologies can be added to this activity for little cost [4]. However, we have shown that identification of unusual or specific samples for laboratory study also takes significant time and knowledge. We suggest that sampling of this type be considered a separate activity from field characterization, and that crewmembers be trained in sampling needs for different kinds of studies (representative lithologies vs. specialized samples) to acquire a mindset for sampling similar to field mapping. Sampling activities should be given a significant amount of specifically allocated time in scheduling EVA activities; and in the better case, that sampling be done as a second activity to a previously studied outcrop where both crew and backroom are comfortable with its context and characteristics. Our hypothesis posited that crewmember knowledge of how the samples would be used upon return would aid them in choosing relevant samples. Our testing bore this hypothesis out to some extent. We therefore recommend that crewmember training should include exposure to the laboratory techniques and analyses that will be used on the samples to foster this knowledge. There is also the potential for increasing crewmember contextual knowledge real-time in the field through the introduction of in situ geochemical technologies such as field portable XRF. The presence of field portable geochemical technology could enable the astronauts to interrogate the samples for K abundance real-time, ensuring they could collect valuable and dateable samples [5]. Though simulations such as these can teach us a fair bit about decision making processes and timeline building, one EVA participant noted that when he wasn't collecting "real" samples, he wasn't at his best. This effect suggests that higher-fidelity studies involving truly remote participants conducting actual scientific studies merit further attention to capture lessons for application to future crew situations.

sample collection↗
NASA NTRS2018

Low-Latency Teleoperations: Operational Implications for Human Space Exploration

Low-latency teleoperations (LLT) is envisioned to be an element of human exploration missions in a number of different applications. LLT can be broadly considered to encompass any remote operation of an asset with a communication delay that is less than the human response time to allow for what is effectively "real-time" or "near real-time" operations. This paper will explore motivations and operational implications for why and how LLT might be used for human exploration space missions. LLT analyses have been performed under the auspices of the NASA Human Spaceflight Architecture Team (HAT) and Evolvable Mars Campaign (EMC). The EMC created a flexible, evolvable, capability-driven architectural strategy to enable a sustainable long-term human presence at Mars. LLT is envisioned to be part of that strategy for both in-space and on-surface applications, and this paper will expand on operational considerations within that broader strategic context, as well additional contexts. Some operational implications explored in this paper, derived largely from previous work, are: (1) crew mission support, for which we will address roles for Mission Control on earth, balanced with the capability for crew and robotic assets to operate independently, (2) science operations, with a focus on "backroom" support, highly dynamic science, and enhanced science return and efficiency, and (3) operational efficiency at a deep-space destination such as Mars, including implications for communications infrastructures and how to leverage and balance system autonomy with crew operations, both of which can inform the overall operational "choreography" between crew members, multiple shifts, and exploration assets.

human spaceflight↗
NASA NTRS2011

The Effect of Different Operations Modes on Science Capabilities During the 2010 Desert-RATS Test: Insights from the Geologist Crewmembers

The 2010 Desert RATS field test utilized two Space Exploration Vehicles (prototype planetary rovers) and four crewmembers (2 per rover) to conduct a geologic traverse across northern Arizona while testing continuous and twice-per-day communications paired with operation modes of separating and exploring individually (Divide & Conquer) and exploring together (Lead & Follow), respectively. This report provides qualitative conclusions from the geologist crewmembers involved in this test as to how these modes of communications and operations affected our ability to conduct field geology. Each mode of communication and operation provided beneficial capabilities that might be further explored for future Human Spaceflight Missions to other solar system objects. We find that more frequent interactions between crews and an Apollo-style Science Team on the Earth best enables scientific progress during human exploration. However, during multiple vehicle missions, this communication with an Earth-based team of scientists, who represent "more minds on the problem", should not come at the exclusion of (or significantly decrease) communication between the crewmembers in different vehicles who have the "eyes on the ground". Inter-crew communications improved when discussions with a backroom were infrequent. Both aspects are critical and cannot be mutually exclusive. Increased vehicle separation distances best enable encounters with multiple geologic units. However, seemingly redundant visits by multiple vehicles to the same feature can be utilized to provide improved process-related observations about the development and modification of the local terrain. We consider the value of data management, transfer, and accessibility to be the most important lesson learned. Crews and backrooms should have access to all data and related interpretations within the mission in as close to real-time conditions as possible. This ensures that while on another planetary surface, crewmembers are as educated as possible with respect to the observations and data they will need to collect at any moment.

Bleacher, Jacob E.↗
NASA NTRS2016

Pre-Mission Input Requirements to Enable Successful Sample Collection by A Remote Field/EVA Team

The FINESSE (Field Investigations to Enable Solar System Science and Exploration) team, part of the Solar System Exploration Virtual Institute (SSERVI), is a field-based research program aimed at generating strategic knowledge in preparation for human and robotic exploration of the Moon, near-Earth asteroids, Phobos and Deimos, and beyond. In contract to other technology-driven NASA analog studies, The FINESSE WCIS activity is science-focused and, moreover, is sampling-focused with the explicit intent to return the best samples for geochronology studies in the laboratory. We used the FINESSE field excursion to the West Clearwater Lake Impact structure (WCIS) as an opportunity to test factors related to sampling decisions. We examined the in situ sample characterization and real-time decision-making process of the astronauts, with a guiding hypothesis that pre-mission training that included detailed background information on the analytical fate of a sample would better enable future astronauts to select samples that would best meet science requirements. We conducted three tests of this hypothesis over several days in the field. Our investigation was designed to document processes, tools and procedures for crew sampling of planetary targets. This was not meant to be a blind, controlled test of crew efficacy, but rather an effort to explicitly recognize the relevant variables that enter into sampling protocol and to be able to develop recommendations for crew and backroom training in future endeavors.

FINESSE↗