Viper – NASA's Moon Rover
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Introduction: NASA’s VIPER mission presents a unique operational paradigm within the history of robotic spaceflight. The proximity of the Moon to the Earth and the terrain elements (surface characteristics, light/shadow dynamics, communication links) of the lunar South Polar landing site create unprecedented operational conditions between these two planetary bodies. Apollo era lunar science and exploration included humans in situ to operate instruments and assimilate observational inputs in real-time. Previous lunar orbital missions have worked to operational timescales, e.g., decisional timelines and communication exchanges, that were weeks in length. Mars rover missions have worked to operational timescales, e.g., decisional timelines and communication exchanges between Mars and Earth, that were hours, days, and weeks in length. In the case of the VIPER mission, our operational decisioning for rover driving and instrument commanding will be compressed to minute-scale timeframes. These operational conditions directly impact the manner and speed with which the VIPER Science Team (VST) is required to synthesize and analyze data and produce timely science-driven decisions throughout surface mission operations. The VST shall provide mission enhancing scientific input to guide rover traverse planning and drill site confirmation and selection throughout surface operations. Further, the VST input will be of vital importance to the mission’s ability to maximize science return and to meet broader NASA objectives for future lunar in-situ resource utilization (ISRU)and exploration activities. The VST co-located in the Mission Science Center (MSC) will be responsive to the tactical operational cadence of the Mission Operations Center (MOC) and will provide further strategic and Long-Term Planning (LTP) guidance to the mission. The VIPER Science Operations & Integration(SO&I)team has developed an architecture that is focused on the infusion of science-decisioning into the operational framework and execution cadence of VIPER. NASA analog research has played a significant role in the construction of the VIPER science operations systems. As an example, the SO&I team has led analog missions that have focused on bringing together expertise in the sciences (natural, applied and social) and in operations in service of learning how to build and hold together interdisciplinary work environments and what tools are needed to support high tempo, high intensity integrated decisioning. These experiences have provided an essential foundation of knowledge to the VIPER team. Those analogs that specifically influenced the VIPER science operations construct were identified through a process of comparative analysis to prioritize those that offered relevance in whole or in part, and those that did not. The analog research output that provided extensibility to the VIPER science operations architecture included remote teams of humans and robots in cooperation (synchronous and asynchronous) with simulated earthbound systems, engineering and science teams, and the integrated assembly of tools that supported scientific analysis and data synthesis and provided infrastructure for the remote testing framework. Analogs which included real-time data monitoring, synthesis, visualization and access in a democratized and operationalized manner were of particular interest to the development of the VIPER MSC toolset both in terms of the technology and the processes used to develop the supporting infrastructure. We anticipate that each subsequent mission to the lunar south pole, whether with robots or humans, will be able to optimize science and exploration return by evolving strategies to infuse real-time collaborative science-decisioning. Furthermore, these efforts will result in a foundation for science operations development in support of human-robotic exploration of deep space and Mars. NASA analogs can continue to provide the opportunity to prepare, test and iterate on the operational concepts and tools that will support these ever-expanding space exploration efforts. Our presentation will include an overview of the VIPER Science Operations & Integration development process and specifics on what aspects of analog research have had a significant impact on our work systems.
The Volatiles Investigating Polar Exploration Rover (VIPER) is a lunar volatiles detection and measurement mission. VIPER will be launched to the Moon in late 2023 as a payload on the Commercial Lunar Payload Services(CLPS) flight provided by Astrobotic's Griffin lander. The VIPER rover is a solar powered, mobile robot de-signed to traverse up to 20 km during a mission lasting up to four lunar days. After landing in a south polar region, the VIPER rover will travel to investigate a range of Ice Stability Regions (ISRs) across scales from 100s of meters to kilometers and conduct surface and subsurface assessment of lunar water and other volatiles. VIPER includes a suite of rover-mounted instruments(three spectrometers and a drill), which the VIPER science mission team will use to characterize the nature of the volatiles and to create global lunar water resource maps.
The Volatiles Investigating Polar Exploration Rover (VIPER) will land in the southern polar region of the Moon and spend approximately 100-days prospecting for water ice. The information returned by VIPER will help determine how we can harvest the Moon's resources for future human space exploration. This information will also provide insight into the distribution and origin of water and other volatiles across the solar system. In this short talk, I will provide a brief overview of the VIPER mission, discuss some of the unique design features of the VIPER rover, and summarize VIPER's multi-modal operations approach.
The Radioisotope Power Systems (RPS) Program tasked the Compass Team to evaluate use of Dynamic Radioisotope Power Systems (DRPS) for lunar science rovers. The object was to identify their advantages and challenges as well as to influence the technology developments with flight-type requirements. This was easily done by using the promising Volatiles Investigating Polar Exploration Rover (VIPER) solar- powered rover mission as a platform to ‘swap in’ a DRPS. The ‘pickup truck bed’ approach allowed both simplified installation and operation of the DRPS while keeping the forward lunar surface ‘blocked’ from the DRPS waste heat which could sublimate the icy surface. It was found that with the Stirling DRPS option the mass is within the planned VIPER lander capability and is very close to VIPER mass and size (the DRPS replaces large battery pack/solar arrays). The Stirling DRPS option produced ~300 Watts electrical (We) using six general purpose heat source (GPHS) bricks and eight Stirling convertors. Replacing the solar/battery power with radioisotope power allows a continuous presence (instead of 6 hours) in a permanently shadowed region (PSR) and over 18 months of operations with minimal science impact (rearward surface heating). It was also found that use of a dynamic system (instead of a thermoelectric system) reduces the heat impact on the science environment two-to-three times. The DRPS, along with a relay link (like Gateway), can provide continuous access to PSRs. The system was also found to be capable of roving for 8 hours per day with a range of over 500 km in 18 months. Preliminary cost estimates fit into a Class D mission but only assuming VIPER heritage and launch, lander, operations, nuclear specific costs [National Environmental Policy Act (NEPA), fueling, transport, Launch Services Program (LSP), etc.] and DRPS are not included.
Conducting lunar science with a robot on the Moon that is commanded in real-time from Earth by distributed workgroups for long durations is a specific activity that has been developed by many projects including NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) mission. VIPER’s nominal mission period for surface operations was set for 100 Earth days (four lunar days). VIPER’s science knowledge acquisition was set to focus on characterizing the distribution of water and volatiles across a range of thermal environments, within a traverse planned to optimize science return across up to 20 km. While VIPER’s status is the subject of discussion, there is research and analysis from the development and simulations phases that are of benefit to the lunar science community and future remote science operations projects. Discussed here are some findings on the process of integrating lunar science with mission system operations.
Dr. Darlene S. Lim is a research scientist at NASA's Ames Research Center in California's Silicon Valley, and the Deputy Project Scientist and Science Operations Lead for NASA's Volatiles Investigating Polar Exploration Rover (VIPER) Lunar Mission. The VIPER lunar rover mission is a mobile robot that will go to the South Pole of the Moon to get a close-up view of the location and concentration of water ice that could eventually be harvested to sustain human exploration on the Moon, Mars — and beyond. VIPER represents the first resource mapping mission on another celestial body and presents a unique operational paradigm within the history of robotic spaceflight. Throughout her career, Darlene has led several NASA-funded programs that have been focused on blending field science research with the development of capabilities and concepts for future human-robotic spaceflight to the Moon and Mars. These research activities have taken her around the world, from pole to pole, land to sea, and to many lakes in between, where she has studied life in extreme environments, the way people conduct science, and how they need to be supported in their work of discovery and exploration. At the center of each of these endeavors is the human - the person who must interact with others, with technology, and with the environment of interest, to apply the scientific method towards the accrual and expansion of knowledge about the planet that we live on and beyond. Darlene has been working with teams of scientists and engineers from a variety of disciplines to hone her understanding of the process by which their interactions and research needs can be supported and enabled under intense operational conditions such as those associated with Moon and Mars exploration. Darlene’s presentation will take the audience through the arc of her research over the past two decades culminating in her on-going work with the NASA VIPER lunar rover mission.
In situ resource utilization (ISRU) technologies are a key advancement required to make human habitation on the Moon and Mars viable. The upcoming Volatiles Investigating Polar Exploration Rover (VIPER) mission will provide crucial correlations between volatiles and lunar geology to understand the water content available for ISRU on the moon. The mission will require the coordination of multi-disciplinary teams across the country making real time decisions based on rover instrument data. The virtual reality Mission Simulation System (vMSS) is a virtual reality platform designed at MIT by the Resource Exploration and Science of our Cosmic Environment (RESOURCE) team to provide teams with a collaboration interface for planetary missions like VIPER. Herein we determine the integration pathway for analog based datasets that are examples of VIPER's two main instruments, the near-infrared volatile spectrometer subsystem (NIRVSS) and the neutron spectrometer subsystem (NSS), into vMSS to provide the most valuable visualization tools. Focusing on improving situational awareness, decision making, reducing task load and incorporating comments from scientists working previous analogs and on the current VIPER mission, we recommend critical elements to implement into vMSS and the best approaches for data visualization. We present a review of relevant analogs and state of the art mission software. We have developed a design concept and path to flight of analysed instrument data integrated with data maps that allow for virtual manipulation and annotation between non-co-located team members. We focus on pre-mission mapping of a priori data for improved situational awareness, layering of analysed instrument data, correlative mapping and interactive capabilities for in-mission decision making, as well as archiving and annotation tools for post-mission analysis. Finally, we lay out the roadmap for the future development of immersive sample site visualization capabilities and the use of integrated instrument data in vMSS with automated temporal and geospatial planning.
The domestic nuclear power plant (NPP) fleet has historically relied on labor-intensive and time-consuming predictive maintenance (PdM) programs, thus driving up operation and maintenance (O&M) costs to achieve high-capacity factors. Artificial intelligence (AI) and machine-learning (ML) can help simplify complex problems such as diagnosing equipment degradation to enable more effective decision-making efforts. The benefits of AI will be felt through more efficient plant O&M, improved work processes, and better integration of people and technology. Together, these benefits hold the promise to make nuclear power more sustainable by reducing O&M costs while improving employee engagement. While AI and ML technologies hold significant promise for the nuclear industry, there are challenges or barriers to their adoption. Explainability and trustworthiness of AI are two salient challenges that need to be addressed for wider deployment of these technologies in NPPs. This research focuses specifically on addressing the explainability and trustworthiness of AI technologies to advance the human, technical, and organization (HTO) readiness levels in adopting a risk-informed PdM strategy at commercial NPPs. In addition, this approach can be adapted to enhance the acceptability of AI in other nuclear applications with a few application-specific modifications. The technical approach ensuring wider adoption of AI technologies was developed by Idaho National Laboratory (INL)—in collaboration with Public Service Enterprise Group (PSEG), Nuclear, LLC—by utilizing the circulating water system (CWS) at two PSEG-owned plant sites for demonstration. Focused user studies were performed in collaboration with subject matter experts (SMEs) from PSEG and other nuclear domains to enhance human and organization readiness by building trust in AI-informed technologies. VIsualization for PrEdictive maintenance Recommendation (VIPER)—a Battelle Energy Alliance, LLC, copyrighted software—was developed and expanded to provide a user-centric visualization by incorporating inputs from the collaborating utility, human factors engineering guidelines, and data analysts. The VIPER software enables users, who may be unfamiliar with ML in general, to be interactively engaged by asking technical questions about PdM, work orders, diagnosis results and their confidence levels, the kind of data being used, and the types of ML algorithms employed. This interactive engagement enhances explainability and builds trust. One of the enabling accomplishments was the integration of large language models (LLMs), both text-based and vision-based, in the VIPER software.
The Moon poles host large quantities of water-ice deposits in the permanently shadowed regions (PSRs), which are vital for enabling sustainable human space exploration, making these regions high-priority targets for upcoming Artemis missions [1]. Unfortunately, today, the best available orbital lunar imagery [2, 3] lacks the meter-scale resolution and signal needed to understand the geomorphology and trafficability of PSRs, complicating the planning and execution of future missions seeking to explore PSRs. We have developed an image enhancement tool called HORUS (Hyper-effective nOise Removal Unet Software) [4, 5], designed to enhance LRO Narrow-Angle Camera (NAC) optical low-light imagery of permanently shadowed regions by effectively removing the CCD-related, photon, and other residual noises that corrupt the images. The tool is composed of two deep learning neural networks trained on environmental metadata and real and synthetic imagery, the latter generated by a physical noise model (LROC). We demonstrated that HORUS effectively produces low-noise, high-resolution images (~1.5m/px), achieving a 5 to 10x improvement over existing long-exposure images of PSRs. HORUS allows scientists and engineers to identify geomorphic features (e.g., craters and boulders) in shadowed regions as small as 3 meters across as well as to peek inside of small shadowed regions, for the first time. The tool was deployed and thoroughly validated for NASA's VIPER mission [6], where it was applied to 20 candidate target regions across the lunar South Pole. Additionally, we conducted different approaches to validate the resulting HORUS-processed images. With HORUS denoised images, VIPER scientists can increase their confidence on what surface features (previously unseen) exist in the shadowed regions, helping them plan rover traverses more safely and efficiently (e.g., Fig. 1) In this manuscript, we will describe how VIPER scientists are utilizing HORUS denoised images to extract new information from the terrain and increase their confidence in what surface features exist in the shadowed regions. In combination with other high-resolution images and digital elevation maps, HORUS images are helping the team analyze potential lading and science sites, as well as planning traverses more safely and efficiently (e.g., Fig. 1). Additionally, we will describe how HORUS tool unlocks a broad range of scientific and exploration applications to other Artemis and CPLS missions to the lunar poles, including (but not limited to) geomorphic analysis, change detection, surface hazard detection, and terrain relative navigation.
The Radioisotope Power Systems (RPS) Program tasked the Compass Team to evaluate use of Dynamic Radioisotope Power Sources (DRPS) for lunar science rovers. The object was to identify their advantages and challenges as well as to influence the technology developments with flight-type requirements. This was done by using the promising Volatiles Investigating Polar Exploration Rover (VIPER) solar-powered rover mission as a platform to ‘swap in’ a DRPS. The resulting design used a ‘pickup truck bed’ approach which allowed simplified installation and operation of the DRPS while also keeping the forward lunar surface ‘blocked’ from the DRPS waste heat, which could sublimate the icy surface. It was found that with the Stirling DRPS option the mass is within the planned VIPER lander capability and is comparable to VIPER mass and size (the DRPS replaces large battery pack/solar arrays). The Stirling DRPS option produced ~300 Watts electrical (We) using six general purpose heat source (GPHS) bricks and eight Stirling convertors. Replacing the solar/battery power with radioisotope power allows a continuous presence (instead of six hours) in a permanently shadowed region (PSR) and over 18 months of operations with minimal science impact (rearward surface heating). It was also found that use of a dynamic system, instead of a thermoelectric system, reduces the heat impact on the science environment two-to-three times while still providing sufficient waste heat for the rover systems in the PSR (~ -200°C). The DRPS, along with a relay link (like Gateway), can provide extended access to PSR. The system was also found to be capable of roving for eight hours per day with a range of well over 100 km in 18 months.
The need for an accessible iterative approach for evaluating prospective artificial intelligence (AI)/ML based technologies in the nuclear industry is needed, given the nature of algorithms and rapid advancements. This paper explores existing heuristic design principles for user-centered design and evaluates them based on their relevancy and usefulness for evaluating AI/ ML based technologies. Researchers at the Idaho National Laboratory (INL) have developed a machine learning software application called VIsualization for PrEdictive maintenance Recommendation (VIPER), which is used to help users understand and engage with the tool to learn more about work orders, data used, predictive maintenance, and machine learning (ML) algorithms. Early user research studies used to access VIPER’s technology readiness level have occurred; however, there is room for further improvement of the software through heuristic evaluations along with other methods and user testing. This work describes the applicability of heuristic evaluation methods and cognitive walkthroughs to help ensure human readiness for prospective AI/ ML based applications, using VIPER as a candidate use case. This work supports industry in ensuring that prospective AI/ML based technologies are usable and useful for plant personnel at nuclear power plants, ultimately leading to their safe, reliable, and efficient use.
The need for an accessible iterative approach for evaluating prospective artificial intelligence (AI)/ML based technologies in the nuclear industry is needed, given the nature of algorithms and rapid advancements. This paper explores existing heuristic design principles for user-centered design and evaluates them based on their relevancy and usefulness for evaluating AI/ ML based technologies. Researchers at the Idaho National Laboratory (INL) have developed a machine learning software application called VIsualization for PrEdictive maintenance Recommendation (VIPER), which is used to help users understand and engage with the tool to learn more about work orders, data used, predictive maintenance, and machine learning (ML) algorithms. Early user research studies used to access VIPER?s technology readiness level have occurred; however, there is room for further improvement of the software through heuristic evaluations along with other methods and user testing. This work describes the applicability of heuristic evaluation methods and cognitive walkthroughs to help ensure human readiness for prospective AI/ ML based applications, using VIPER as a candidate use case. This work supports industry in ensuring that prospective AI/ML based technologies are usable and useful for plant personnel at nuclear power plants, ultimately leading to their safe, reliable, and efficient use. PowerPoint for conference that was reviewed in PRS and LRS PRS/CON-25-05379 and INL/CON-25-82946