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At least 487 records · Page 27

Assessing Malaria Risks in Greater Mekong Subregion based on Environmental Parameters

At 4,200 km, the Mekong River is the tenth longest river in the world. It directly and indirectly influences the lives of hundreds of millions of inhabitants in its basin. The riparian countries - Thailand, Myanmar, Cambodia, Laos, Vietnam, and a small part of China - form the Greater Mekong Subregion (GMS). This geographical region has the misfortune of being the world's epicenter of falciparum malaria, which is the most severe form of malaria caused by Plasmodium falciparum. Depending on the country, approximately 50 to 90% of all malaria cases are due to this species. In the Malaria Modeling and Surveillance Project, we have been developing techniques to enhance public health s decision capability for malaria risk assessments and controls. The main objectives are: 1) identifying the potential breeding sites for major vector species; 2) implementing a malaria transmission model to identify the key factors that sustain or intensify malaria transmission; and 3) implementing a risk algorithm to predict the occurrence of malaria and its transmission intensity. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Socioeconomic factors that may influence malaria transmissions will also be incorporated into the predictive models.

Kiang, Richard↗

Malaria Modeling and Surveillance for the Greater Mekong Subregion

At 4,200 km, the Mekong River is the tenth longest river in the world. It directly and indirectly influences the lives of hundreds of millions of inhabitants in its basin. The riparian countries - Thailand, Myanmar, Cambodia, Laos, Vietnam, and a small part of China - form the Greater Mekong Subregion (GMS). This geographical region has the misfortune of being the world's epicenter of falciparum malaria, which is the most severe form of malaria caused by Plasmodium falciparum. Depending on the country, approximately 50 to 90% of all malaria cases are due to this species. In the Malaria Modeling and Surveillance Project, we have been developing techniques to enhance public health's decision capability for malaria risk assessments and controls. The main objectives are: 1) Identifying the potential breeding sites for major vector species; 2) Implementing a malaria transmission model to identify the key factors that sustain or intensify malaria transmission; and 3) Implementing a risk algorithm to predict the occurrence of malaria and its transmission intensity. The potential benefits are: 1) Increased warning time for public health organizations to respond to malaria outbreaks; 2) Optimized utilization of pesticide and chemoprophylaxis; 3) Reduced likelihood of pesticide and drug resistance; and 4) Reduced damage to environment. Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. These parameters are extracted from NASA Earth science data sets. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records.

Kiang, Richard↗

Exploiting Lunar Natural and Augmented Thermal Environments for Exploration and Research

Near the poles of the Moon, there are permanently shadowed craters whose surface temperatures never exceed 100 K. Craters within craters, commonly referred to as double-shaded craters, have areas where even colder regions exist with, in many cases, temperatures that should never exceed 50 K. The presence of water ice possibly existing in permanently shaded areas of the moon has been hypothesized, discussed, and studied since Watson et al. [1] predicted the possibility of ice on the moon. Ingersoll et al. [2] estimated that the maximum sublimation rate for ice is less than 1 cm per billion years for these types of environments. These potential ice stores have many uses for lunar exploration, potentially providing precious water and rocket fuel for any human exploration or future colonization. The temperatures within these regions offer unprecedented high-vacuum cryogenic environments, which in their natural state could support cryogenic applications such as high-temperature superconductors and associated devices that could be derived. The potential application of naturally occurring cryogenic environments in conjunction with simple methods to augment these environments to achieve even colder temperatures opens the potential use of many additional cryogenic techniques. Besides ice stores and the potential for continuous solar illumination for power production, the unique cryogenic conditions at the lunar poles provide an environment that could reduce the power, weight, and total mass that would have to be carried from the Earth to the Moon for lunar exploration and research.

Ryan, Robert E.↗

Critical Phenomena in Microgravity: Past, Present, and Future

This review provides an overview of the progress in using the low-gravity environment of space to explore critical phenomena and test modern theoretical predictions. Gravity-induced variations in the hydrostatic pressure and the resulting density gradients adversely affect ground-based measurements near fluid critical points. Performing measurements in a low-gravity environment can significantly reduce these difficulties. A number of significant experiments have been performed in low-Earth orbit. Experiments near the lambda transition in liquid helium explored the regime of large correlation lengths and tested the theoretical predictions to a level of precision that could not be obtained on Earth. Other studies have validated theoretical predictions for the divergence in the viscosity as well as the unexpected critical speeding up of the thermal equilibrium process in pure fluids near the liquid-gas critical point. We describe the scientific content of previously flown low-gravity investigations of critical phenomena as well as those in the development stage, and associated ground-based work.

renormalization-group theory↗

Surveillance and Control of Malaria Transmission in Thailand using Remotely Sensed Meteorological and Environmental Parameters

These slides address the use of remote sensing in a public health application. Specifically, this discussion focuses on the of remote sensing to detect larval habitats to predict current and future endemicity and identify key factors that sustain or promote transmission of malaria in a targeted geographic area (Thailand). In the Malaria Modeling and Surveillance Project, which is part of the NASA Applied Sciences Public Health Applications Program, we have been developing techniques to enhance public health's decision capability for malaria risk assessments and controls. The main objectives are: 1) identification of the potential breeding sites for major vector species; 2) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity; 3) implementation of a dynamic transmission model to identify the key factors that sustain or intensify malaria transmission. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. !> Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of the remotely sensed parameters. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Discrete event simulations are used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to the Greater Mekong Subregion. Our models have been applied to malaria in Indonesia, Korea, and other regions in the world with similar success.

Kiang, Richard K.↗

Compact Rare Earth Emitter Hollow Cathode

A compact, high-current, hollow cathode utilizing a lanthanum hexaboride (LaB6) thermionic electron emitter has been developed for use with high-power Hall thrusters and ion thrusters. LaB6 cathodes are being investigated due to their long life, high current capabilities, and less stringent xenon purity and handling requirements compared to conventional barium oxide (BaO) dispenser cathodes. The new cathode features a much smaller diameter than previously developed versions that permit it to be mounted on axis of a Hall thruster ( internally mounted ), as opposed to the conventional side-mount position external to the outer magnetic circuit ("externally mounted"). The cathode has also been reconfigured to be capable of surviving vibrational loads during launch and is designed to solve the significant heater and materials compatibility problems associated with the use of this emitter material. This has been accomplished in a compact design with the capability of high-emission current (10 to 60 A). The compact, high-current design has a keeper diameter that allows the cathode to be mounted on the centerline of a 6- kW Hall thruster, inside the iron core of the inner electromagnetic coil. Although designed for electric propulsion thrusters in spacecraft station- keeping, orbit transfer, and interplanetary applications, the LaB6 cathodes are applicable to the plasma processing industry in applications such as optical coatings and semiconductor processing where reactive gases are used. Where current electrical propulsion thrusters with BaO emitters have limited life and need extremely clean propellant feed systems at a significant cost, these LaB6 cathodes can run on the crudest-grade xenon propellant available without impact. Moreover, in a laboratory environment, LaB6 cathodes reduce testing costs because they do not require extended conditioning periods under hard vacuum. Alternative rare earth emitters, such as cerium hexaboride (CeB6) can be used in this configuration with possibly an even longer emitter life. This cathode is specifically designed to integrate on the centerline of a high-power Hall thruster, thus eliminating the asymmetries in the plasma discharge common to cathodes previously mounted externally to the thruster s magnetic circuit. An alternative configuration for the cathode uses an external propellant feed. This diverts a fraction of the total cathode flow to an external feed, which can improve the cathode coupling efficiency at lower total mass flow rates. This can improve the overall thruster efficiency, thereby decreasing the required propellant loads for different missions. Depending on the particular mission, reductions in propellant loads can lead to mission enabling capabilities by allowing launch vehicle step-down, greater payload capability, or by extending the life of a spacecraft.

Watkins, Ronald↗

The Successful Implementation of NASA Orbital Debris Requirements for the Retirement of TDRS-1

TDRS-1 was decommissioned on October 28th 2009 following more than 26 years of operation. The Grand Old Dame of the TDRSS constellation wa s launched aboard the maiden voyage of the Space Shuttle Challenger ( STS-6) in April 1983. TDRS-1 survived a malfunction of the Inertial Upper Stage eventually utilizing its own propulsion system to success fully reach its assigned station in geosynchronous orbit. The anomalo us beginning of the TDRS-1 mission was not without lasting consequenc es as the primary reaction control system (A-side) was completely di sabled with an apparent propellant leak and the secondary system (B-s ide) suffered damage to its negative roll thruster rendering the thru ster inoperable. Following decommissioning the challenge to completin g a successful TDRS-1 end-of-mission (EOM) was the implementation of the stringent orbital debris requirements of NPR 8715.6 with a parti ally functioning spacecraft not originally designed to meet those req uirements. The TDRS-1 EOM had three key goals: 1) removal of the spac ecraft from geosynchronous orbit; 2) depletion of the remaining prope llant; and 3) passivation of all other sources of energy storage or generation. The TDRS-1 EOM approach was one of minimizing risks while accomplishing the goals above. The orbit raising portion of EOM was accomplished using deltavelocity operations already proven during pre vious stationchanging maneuvers. The propellant depletion approach wa s necessarily more aggressive as over 20 hours of burn time was requ ired to deplete the remaining fuel. A novel approach utilizing a spin ning, thrusting, passively controlled spacecraft configuration was ut ilized to achieve reasonable burn durations that met schedule constra ints. This nonstandard configuration required careful analysis of ele ctrical, thermal, and communication subsystems. The configuration wa s thoroughly simulated prior to the start of operations and carefully characterized during the initial spin period and first burn. Passiva tion was by definition a unique operation not previously performed wi thin the TDRS 1-7 constellation. Use was made of a TDRS spacecraft si mulator to verify the operational procedure to mitigate risks and pro vide crew training. TDRS-1 orbit raising maneuvers commenced on June 5th 2010 and completed on June 14th with an apogee 370 km and a peri gee 352 km above geosynchronous altitude. 127 kg of propellant were e stimated to be remaining in the tanks at the completion of orbit rais ing. TDRS-1 was placed in its spinning orientation on June 16th and the first fuel depletion burn was performed the following day. A seri es of 10 depletion burns were performed ending on June 26th when both propellant tank pressures experienced dramatic drops. Final passivat ion was performed on June 27 th deactivating electronics, removing t he batteries from the bus and solar arrays, and disabling the space-t o-ground communications equipment. The Second TDRS Ground Terminal (S TGT) continued to open loop track TDRS-1 for several days attempting command reacquisition several times a day. All attempts were unsucce ssful confirming passivation was achieved. The TDRS-1 orbit at passiv ation was an orbital debris compliant 36,319 x 36,128 km in height. W hile differing spacecraft designs may preclude mimicking the exact TD RS-1 EOM approach, the TDRS-1 campaign serves to demonstrate that pr e-NPR 8715.6 designs can be made to meet the requirements resulting i n a reduced orbit debris environment for future missions

Mirczak, Walter↗

Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.

Huang, Yiteng↗

Microbiological Lessons Learned from the Space Shuttle

After 30 years of being the centerpiece of NASA s human spacecraft, the Space Shuttle will retire. This highly successful program provided many valuable lessons for the International Space Station (ISS) and future spacecraft. Major microbiological risks to crewmembers include food, water, air, surfaces, payloads, animals, other crewmembers, and ground support personnel. Adverse effects of microorganisms are varied and can jeopardize crew health and safety, spacecraft systems, and mission objectives. Engineering practices and operational procedures can minimize the negative effects of microorganisms. To minimize problems associated with microorganisms, appropriate steps must begin in the design phase of new spacecraft or space habitats. Spacecraft design must include requirements to control accumulation of water including humidity, leaks, and condensate on surfaces. Materials used in habitable volumes must not contribute to microbial growth. Use of appropriate materials and the implementation of robust housekeeping that utilizes periodic cleaning and disinfection will prevent high levels of microbial growth on surfaces. Air filtration can ensure low levels of bioaerosols and particulates in the breathing air. The use of physical and chemical steps to disinfect drinking water coupled with filtration can provide safe drinking water. Thorough preflight examination of flight crews, consumables, and the environment can greatly reduce pathogens in spacecraft. The advances in knowledge of living and working onboard the Space Shuttle formed the foundation for environmental microbiology requirements and operations for the International Space Station (ISS) and future spacecraft. Research conducted during the Space Shuttle Program resulted in an improved understanding of the effects of spaceflight on human physiology, microbial properties, and specifically the host-microbe interactions. Host-microbe interactions are substantially affected by spaceflight. Astronaut immune functions were found to be altered. Selected microorganisms were found to become more virulent during spaceflight. The increased knowledge gained on the Space Shuttle resulted in further studies of the host-microbe interactions on the ISS to determine if countermeasures were necessary. Lessons learned from the Space Shuttle Program were integrated into the ISS resulting in the safest space habitat to date.

Pierson, Duane L.↗

Glovebox for GeoLab Subsystem in HDU1-PEM

The GeoLab glovebox was designed to enable the preliminary examination, by astronauts, of geological samples collected from the surface of another planetary body. The collected information would then aid scientists in making decisions about sample curation and prioritization for return to Earth for study. This innovation was designed around a positive- pressure-enriched nitrogen environment glovebox to reduce sample handling contamination. The structure was custom-designed to fit in section H of NASA s Habitat Demonstration Unit 1 Pressurized Excursion Module (HDU1- PEM). In addition, the glovebox was designed to host analytical instruments in a way that prevents sample contamination.

Evans, Cynthia↗

The Effects of Long Duration Bed Rest on Functional Mobility and Balance: Relationship to Resting State Motor Cortex Connectivity

NASA offers researchers from a variety of backgrounds the opportunity to study bed rest as an experimental analog for space flight. Extended exposure to a head-down tilt position during long duration bed rest can resemble many of the effects of a low-gravity environment such as reduced sensory inputs, body unloading and increased cephalic fluid distribution. The aim of our study is to a) identify changes in brain function that occur with prolonged bed rest and characterize their recovery time course; b) assess whether and how these changes impact behavioral and neurocognitive performance. Thus far, we completed data collection from six participants that include task based and resting state fMRI. The data have been acquired through the bed rest facility located at the University of Texas Medical Branch (Galveston, TX). Subjects remained in bed with their heads tilted down 6 degrees below their feet for 70 consecutive days. Behavioral measures and neuroimaging assessments were obtained at seven time points: a) 7 and 12 days before bed rest; b) 7, 30, and 65 days during bed rest; and c) 7 and 12 days after bed rest. Functional connectivity magnetic resonance imaging (FcMRI) analysis was performed to assess the connectivity of motor cortex in and out of bed rest. We found a decrease in motor cortex connectivity with vestibular cortex and the cerebellum from pre bed rest to in bed rest. We also used a battery of behavioral measures including the functional mobility test and computerized dynamic posturography collected before and after bed rest. We will report the preliminary results of analyses relating brain and behavior changes. Furthermore, we will also report the preliminary results of a spatial working memory task and vestibular stimulation during in and out of bed rest.

Erdeniz, B.↗

The Effects of Long Duration Bed Rest as a Spaceflight Analogue on Resting State Sensorimotor Network Functional Connectivity and Neurocognitive Performance

Long duration spaceflight has been associated with detrimental alterations in human sensorimotor systems and neurocognitive performance. Prolonged exposure to a head-down tilt position during long duration bed rest can resemble several effects of the microgravity environment such as reduced sensory inputs, body unloading and increased cephalic fluid distribution. The question of whether microgravity affects other central nervous system functions such as brain functional connectivity and its relationship with neurocognitive performance is largely unknown, but of potential importance to the health and performance of astronauts both during and post-flight. The aims of the present study are 1) to identify changes in sensorimotor resting state functional connectivity that occur with extended bed rest exposure, and to characterize their recovery time course; 2) to evaluate how these neural changes correlate with neurocognitive performance. Resting-state functional magnetic resonance imaging (rsfMRI) data were collected from 17 male participants. The data were acquired through the NASA bed rest facility, located at the University of Texas Medical Branch (Galveston, TX). Participants remained in bed with their heads tilted down six degrees below their feet for 70 consecutive days. RsfMRI data were obtained at seven time points: 7 and 12 days before bed rest; 7, 50, and 65 days during bed rest; and 7 and 12 days after bed rest. Functional connectivity magnetic resonance imaging (fcMRI) analysis was performed to measure the connectivity of sensorimotor networks in the brain before, during, and post-bed rest. We found a decrease in left putamen connectivity with the pre- and post-central gyri from pre bed rest to the last day in bed rest. In addition, vestibular cortex connectivity with the posterior cingulate cortex decreased from pre to post bed rest. Furthermore, connectivity between cerebellar right superior posterior fissure and other cerebellar regions decreased from pre bed rest to the last day in bed rest. In contrast, connectivity within the default mode network remained stable over the course of bed rest. We also utilized a battery of behavioral measures including spatial working memory tasks and measures of functional mobility and balance. These behavioral measurements were collected before, during, and after bed rest. We will report the preliminary findings of correlations observed between brain functional connectivity and behavioral performance changes. Our results suggest that sensorimotor brain networks exhibit decoupling with extended periods of reduced usage. The findings from this study could aid in the understanding and future design of targeted countermeasures to alleviate the detrimental health and neurocognitive effects of long-duration spaceflight.

Cassady, K.↗

Blunt-Body Aerothermodynamic Database from High-Enthalpy CO2 Testing in an Expansion Tunnel

An extensive database of heating, pressure, and flow field measurements on a 70-deg sphere-cone blunt body geometry in high-enthalpy, CO2 flow has been generated through testing in an expansion tunnel. This database is intended to support development and validation of computational tools and methods to be employed in the design of future Mars missions. The test was conducted in an expansion tunnel in order to avoid uncertainties in the definition of free stream conditions noted in previous studies performed in reflected shock tunnels. Data were obtained across a wide range of test velocity/density conditions that produced various physical phenomena of interest, including laminar and transitional/turbulent boundary layers, non-reacting to completely dissociated post-shock gas composition and shock-layer radiation. Flow field computations were performed at the test conditions and comparisons were made with the experimental data. Based on these comparisons, it is recommended that computational uncertainties on surface heating and pressure, for laminar, reacting-gas environments can be reduced to +/-10% and +/-5%, respectively. However, for flows with turbulence and shock-layer radiation, there were not sufficient validation-quality data obtained in this study to make any conclusions with respect to uncertainties, which highlights the need for further research in these areas.

Hollis, Brian R.↗

Green Light for Green Flight: NASA's Contributions to Environmentally Friendly Aviation

Although the shape and speed of commercial airliners have not changed significantly since the late-1950s, many aspects of performance such as range and fuel efficiency, and environmental impacts including noise and emissions have improved tremendously. By the beginning of the 21st century, however, it became clear that more work was necessary. Heightened sensitivity to, and understanding of, the impact of aviation on the environment and the reduced availability of low-cost energy placed the spotlight directly on aircraft efficiency and reducing environmental impacts. This realization spawned one of NASA's most ambitious aviation projects to date - the Environmentally Responsible Aviation project.

Peter W. Merlin↗

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU)processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗

ICE-RASSOR: Intelligent Capabilities Enhanced

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RAS-SOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar sur-face, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensing. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensory. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗

Towards Autonomous Lunar Resource Excavation via Reinforcement Learning

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. The goal of reinforcement learning is for an agent to learn a policy (task strategy) through interactions with an environment. When the agent performs an action, a change occurs in environment state and a numerical reward is received which informs the agent whether the action performed was good or not. Since reinforcement learning algorithms learn through trial-and-error, a simulation is a desirable first environment for development and learning. We developed two simulations, the first is a 2D excavation simulation developed to facilitate parameter selection, and a 3D simulation developed using a game physics engine, to simulate simplified soil interactions and increase the fidelity of the dynamic models of the robotic agents. The development of this 3D simulation has enabled the training of additional sensing capabilities and research both at the granular mechanics and operations levels. We experimented with various virtual sensor payloads to identify a combination that enabled efficient excavation operation and learning. Our reward function is based on how much material is excavated per step. A penalty is also received for leaving the dig site and to smooth the acceleration of the drum arms. We implemented pseudo time-of-flight sensors to report distance from each drum to ground and the height above ground which was found to be more efficient than existing solutions. Our findings suggest that reinforcement learning for autonomous operations has learned viable trenching strategies within 3000 training episodes in our simplified 2D environment and helped identify desirable sensing capabilities, arrangements, and considerations such as the positioning of time-of-flight sensors. Future work includes expanding our simulation to more complex environments and scenarios, and transfer learning from simulation to RASSOR 2.0 hardware for deployment in the Regolith Test Bin at NASA's Kennedy Space Center.

rassor↗