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NASA NTRS2019

The Effect of a Hall Thruster-Like Magnetic Field on Operation of a 25-A Class Hollow Cathode

The effect of applying a Hall thruster-like magnetic field to a 25-A class hollow cathode is experimentally characterized. A magnetic simulator that approximated the magnetic field of NASA's HERMeS Hall thruster was used to apply magnetic fields of strengths that varied from 0 to 1.25 of the nominal HERMeS value Bnom. Cathode operation was characterized by parameters such as the discharge voltage, voltage and current oscillation magnitudes, and ion energy spectra. It was found that the application of the magnetic field profoundly affected the operation of the cathode. For the nominal xenon flow rate of 14.7 sccm, when increasing the magnetic field from 0 Bnom to 1.25 Bnom, the discharge voltage increased from 20 V to 40 V and the cathode orifice plate temperature increased from 934 ºC to 987 ºC. Oscillations of the discharge voltage, discharge current, and keeper voltage all remained relatively quiescent. However, the ion energy spectra changed profoundly between conditions, with little ion population above 50 V at 0 Bnom, yet a high-energy ion tail extending above 150 V at the 1.25 Bnom case. These high-energy ions appeared without an increase in the oscillation levels, indicating that previous cathode mode definitions may not apply with the Hall thruster-like magnetic field. The implications of these results on existing cathode operational mode definitions, component-level cathode testing, and operation in a Hall thruster are discussed.

Hall, Scott J.↗
NASA NTRS2019

In-Time System-Wide Safety Assurance (ISSA) Concept of Operations

Emerging operations involving Urban Air Mobility (UAM) poses a challenge to safety assurance and accessibility to the NAS. In particular, the public has a low tolerance for risk in aviation and the current NAS tends to be labor-intensive with limited ability to scale up for UAM. In response to this landscape, NASA is collaborating with industry to define an In-time Aviation Safety Management System (IASMS) Concept of Operations (ConOps) for a scalable UAM along with a service-oriented architecture. This architecture would better focus safety investments for technological solutions that overcome safety related barriers for emerging operations. By working with industry, consensus can be reached on desirable system traits that are based on integration of data and leverage increasingly autonomous and automated systems. These complex systems can identify anomalies, precursors, and trends that together enable more proactive management of operational risks.

Ellis, Kyle↗
NASA NTRS2019

Scalable Traffic Management for Emergency Response Operations (STEReO)

The Scalable Traffic Management for Emergency Response Operations (STEReO) project aims to apply various NASA technologies, such as Unmanned Aircraft System (UAS) Traffic Management (UTM) services, onboard-vehicle autonomy, novel approaches to communications and connectivity, and remote/virtual collaboration interfaces to current-day emergency response efforts to natural disasters. Today's emergency response efforts are based on long-standing procedures that are manaul in nature, and could benefit from modernization. In particular, the use of UAS vehicles is limited, primarily due to concerns surrounding dangerous interactions between manned/unmanned operations. STEReO hopes to introduce data exchanges that improve shared situation awareness, reduce manual coordination procedures, enable scalable and high-density air operations, collectivley bringing a positive impact to the incident response. When successful, STEReO technologies will improve efficiency and timeliness of the response and recovery phases of a disaster, resulting in substantial reductions to community harm, and will also accelerate NASA’s development of high-density resilient operations, benefitting other projects relying on increasing levels of autonomy and connectivity. The prepared material provides an overview of the STEReO project, for presentation at the 2019 Convergent Aeronautics Solution (CAS) Showcase event. The CAS showcase brings together all of the current CAS execution activities, highlighting NASA's high-risk investments in aeronautics research.

Mercer, Joey↗
NASA NTRS2019

Persistent Assets in Zero-G and on Planetary Surfaces: Enabled by Modular Technology and Robotic Operations

Space operations are on the cusp of a revolutionary new operational paradigm that leverages modular systems and recurring robotic visits to “Persistent Assets” enabling asset maintenance, repair, and enhancement. A “Persistent Asset” is defined here as any zero-g or planetary surface system that benefits from in-space assembly (ISA) or multiple visits for servicing, repairs, and upgrades. This term is an extension of the term “Persistent Platform” used by Ms. Pam Melroy at the Defense Advanced Research Projects Agency to describe the vision of the Agency for a geosynchronous Earth orbiting platform. In this paper, the term “Persistent Asset” is introduced to encompass not only zero-g systems; such as telecommunication platforms, Earth observing science platform, Department of Defense platforms, and scientific telescope systems, but also planetary surface systems that support missions such as human outposts, science stations, and in-situ resource utilization systems. In contrast to the current state of the art, where space systems are typically launched as a single unit and operated without any further physical intervention after launch; future systems will be maintained, enhanced and reconfigured in-situ as new technology becomes available or mission needs change. Visits to the persistent asset can be regularly scheduled or dictated by funding constraints enabling a pay-as-you-go approach, which is largely independent of time-constraints and able to exploit launches of opportunity. In this paper, historical in-space assembly activities which relied heavily on astronaut extra-vehicular activity will be reviewed as well as early robotic assembly activities. These approaches will be contrasted with emerging modular approaches supporting realization of a new Persistent Asset operational paradigm. The paper will define attributes of the Persistent Asset paradigm and illustrate advantages by applying the paradigm to two relevant applications: 1) a large space telescope backing structure and 2) the backbone structure for a solar electric transport vehicle. Finally, recently developed unique Persistent Asset elements (modules, and interface approaches) will be described.

Doggett, William R.↗
NASA NTRS2019

Prototyping Operational Autonomy for Space Traffic Management

Current state of the art in Space Traffic Management (STM) relies on a handful of providers for surveillance and collision prediction, and manual coordination between operators. Neither is scalable to support the expected 10x increase in spacecraft population in less than 10 years, nor does it support automated manuever planning. We present a software prototype of an STM architecture based on open Application Programming Interfaces (APIs), drawing on previous work by NASA to develop an architecture for low-altitude Unmanned Aerial System Traffic Management. The STM architecture is designed to provide structure to the interactions between spacecraft operators, various regulatory bodies, and service suppliers, while maintaining flexibility of these interactions and the ability for new market participants to enter easily. Autonomy is an indispensable part of the proposed architecture in enabling efficient data sharing, coordination between STM participants and safe flight operations. Examples of autonomy within STM include syncing multiple non-authoritative catalogs of resident space objects, or determining which spacecraft maneuvers when preventing impending conjunctions between multiple spacecraft. The STM prototype is based on modern micro-service architecture adhering to OpenAPI standards and deployed in industry standard Docker containers, facilitating easy communication between different participants or services. The system architecture is designed to facilitate adding and replacing services with minimal disruption. We have implemented some example participant services (e.g. a space situational awareness provider/SSA, a conjunction assessment supplier/CAS, an automated maneuver advisor/AMA) within the prototype. Different services, with creative algorithms folded into then, can fulfil similar functional roles within the STM architecture by flexibly connecting to it using pre-defined APIs and data models, thereby lowering the barrier to entry of new players in the STM marketplace. We demonstrate the STM prototype on a multiple conjunction scenario with multiple maneuverable spacecraft, where an example CAS and AMA can recommend optimal maneuvers to the spacecraft operators, based on a predefined reward function. Such tools can intelligently search the space of potential collision avoidance maneuvers with varying parameters like lead time and propellant usage, optimize a customized reward function, and be implemented as a scheduling service within the STM architecture. The case study shows an example of autonomous maneuver planning is possible using the API-based framework. As satellite populations and predicted conjunctions increase, an STM architecture can facilitate seamless information exchange related to collision prediction and mitigation among various service applications on different platforms and servers. The availability of such an STM network also opens up new research topics on satellite maneuver planning, scheduling and negotiation across disjoint entities.

space traffic management↗
NASA NTRS2019

TCL3 UTM (UAS Traffic Management) Flight Tests, Airspace Operations Laboratory (AOL) Report

The Technology Capability Level-3 (TCL3) flight tests were conducted at six different test sites located across the USA from March to May of 2018. The campaign resulted in over 830 data collection flights using 28 different aircraft and involving 20 flight crews. Flights not only varied in duration, but also in the environments and terrains over which they flew. The TCL3 tests highlighted four different types of tests: three tests focused on Communication, Navigation and Surveillance (CNS); six tests focused on Sense and Avoid (SAA) technologies; six tests focused on USS Data and Information Exchange (DAT); and five tests focused on exploring fundamental Concepts of the project (CON). This document presents data collected during the TCL3 tests that informed the operator’s experiences—the quality of the unmanned aerial system (UAS) Service Supplier (USS) information that the operator was provided with, the usefulness of this information, and the usability of the automation, both while airborne and on the ground. It is intended to complement the reports written by the test sites and the quantitative reports and presentations of the UAS Traffic Management (UTM) project. With the goal of instructing what the minimum information requirements and/or best practices might be in TCL3 operations, the driving enquiry was: How do you get the information you need, when you need it, to successfully fly a UAS in UTM airspace? This enquiry touches on two requirements for displays, which are to provide adequate situation awareness (SA) and to share information through a USS. The six test sites participating in the TCL3 tests flew a subset of the 20 tests (outlined above), with most sites working on a subset of each of the four types: Communications, Navigation and Surveillance (CNS); DAT; CON; and Sense and Avoid (SAA). The, mainly qualitative, data addressed in this report was collected by the AOL (Airspace Operations Laboratory) both on-site and remotely for each test. The data consists of the contents of end-of-day debriefs, end-of-day surveys, observer notes, and flight test information, all submitted as part of the Data Management Plan (DMP).

Martin, Lynne↗
NASA NTRS2020

A Summary Of: Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Sleep loss and circadian misalignment contribute to a meaningful proportion of operational accidents and incidents. Countermeasures and work scheduling designs aimed at mitigating fatigue are typically evaluated in controlled laboratory environments, but the effectiveness of translating such strategies to operational environments can be challenging to assess. This manuscript summarizes an approach for collecting sleep, circadian, fatigue, and performance data in a complex operational environment. We studied 44 airline pilots over 34 days while they flew a fixed schedule, which included a baseline data collection with 5 days of mid-morning flights, four early flights, four high-workload mid-day flights, and four late flights that landed after midnight. Each work block was separated by 3-4 days of rest. To assess sleep, participants wore a wrist-worn research-validated activity monitor continuously and completed daily sleep diaries. To assess the circadian phase, pilots were asked to collect all urine produced in four or eight hourly bins during the 24 h after each duty block for the assessment of 6-sulfatoxymelatonin (aMT6s), which is a biomarker of the circadian rhythm. To assess subjective fatigue and objective performance, participants were provided with a touchscreen device used to complete the Samn-Perelli Fatigue Scale and Psychomotor Vigilance Task (PVT) during and after each flight, and at wake-time, mid-day, and bedtime. Using these methods, it was found that sleep duration was reduced during early starts and late finishes relative to baseline. Circadian phase shifted according to duty schedule, but there was a wide range in the aMT6s peak between individuals on each schedule. PVT performance was worse on the early, high-workload, and late schedules relative to baseline. Overall, the combination of these methods was practical and effective for assessing the influence of sleep loss and circadian phase on fatigue and performance in a complex operational environment.

Arsintescu, Lucica↗
NASA NTRS2019

Medical System Concept of Operations for Mars Exploration Mission-11: Exploration Medical Capability (ExMC) Element - Human Research Program

NASA’s exploration missions to Mars will have durations of 2-3 years and will take humans farther away from Earth than ever before. This will result in a paradigm shift for mission planning, spacecraft design, human systems integration, and in-flight medical care. Constraints on real-time communication, resupply, and medical evacuation are major architectural drivers. These constraints require medical system development to be tightly integrated with mission and vehicle design to provide crew autonomy and enable mission success. This concept of operations provides a common vision of medical care for developing a medical system for Mars exploration missions. It documents an overview of the stakeholder needs and goals of a medical system and provides examples of the types of activities the system will be used for during the mission. Development of the concept of operations considers mission variables such as distance from Earth, duration of mission, time to definitive medical care, communication protocols between crewmembers and ground support, personnel capabilities and skill sets, medical hardware and software, and medical data management. The information provided in this document informs the ExMC Systems Engineering effort to define the functions to be provided by the medical system. In addition, this concept of operations will inform the subsequent systems engineering process of developing technical requirements, system architectures, interfaces, and verification and validation approaches for the medical system. This document supports the closure of ExMC Gap Med01: We do not have a concept of operations for medical care during exploration missions, corresponding to the ExMC-managed human system risk: Risk of Adverse Health Outcomes & Decrements in Performance due to Inflight Medical Conditions. This document is applicable to the ExMC Element Systems Engineering process and may be used for collaboration within the Human Research Program.

Urbina, Michelle↗
NASA NTRS2018

Persistent Assets in Zero-G and on Planetary Surfaces: Enabled by Modular Technology and Robotic Operations

Space operations are on the cusp of a revolutionary new operational paradigm that leverages modular systems and recurring robotic visits to “Persistent Assets” enabling asset maintenance, repair, and enhancement. A “Persistent Asset” is defined here as any zero-g or planetary surface system that benefits from in-space assembly (ISA) or multiple visits for servicing, repairs, and upgrades. This term is an extension of the term “Persistent Platform” used by Ms. Pam Melroy at the Defense Advanced Research Projects Agency to describe the vision of the Agency for a geosynchronous Earth orbiting platform. In this paper, the term “Persistent Asset” is introduced to encompass not only zero-g systems; such as telecommunication platforms, Earth observing science platform, Department of Defense platforms, and scientific telescope systems, but also planetary surface systems that support missions such as human outposts, science stations, and in-situ resource utilization systems. In contrast to the current state of the art, where space systems are typically launched as a single unit and operated without any further physical intervention after launch; future systems will be maintained, enhanced and reconfigured in-situ as new technology becomes available or mission needs change. Visits to the persistent asset can be regularly scheduled or dictated by funding constraints enabling a pay-as-you-go approach, which is largely independent of time-constraints and able to exploit launches of opportunity. In this paper, historical in-space assembly activities which relied heavily on astronaut extra-vehicular activity will be reviewed as well as early robotic assembly activities. These approaches will be contrasted with emerging modular approaches supporting realization of a new Persistent Asset operational paradigm. The paper will define attributes of the Persistent Asset paradigm and illustrate advantages by applying the paradigm to two relevant applications: 1) a large space telescope backing structure and 2) the backbone structure for a solar electric transport vehicle. Finally, recently developed unique Persistent Asset elements (modules, and interface approaches) will be described.

William R Doggett↗
NASA NTRSDate not supplied

Demonstration of Two Extended Visual Line of Sight Methods for Urban UAV Operations

This report describes two extended visual line of sight (EVLOS) methods developed and utilized during two flight campaigns over the campus of NASA Langley Research Center (LaRC): a chase vehicle method and a radio controlled (RC) pilot handoff method. These campaigns were performed to (a) evaluate small unmanned aerial system (sUAS) flight beyond the visual line of sight (BVLOS) of the ground control station operator and (b) test technologies under development to enable a transition from EVLOS to BVLOS operations. While an autonomous waypoint-based operational approach enabled minimal pilot intervention in both methods, range containment was enforced (a) manually via continual pilot visual monitoring and (b) autonomously via on-board contingency landing autonomy triggerable at the boundary of stay-in geofences. In the thirty-nine flights which utilized the chase vehicle, the pilot followed the sUAS flying a 1.2 km path at 40m altitude over urban streets. In the fifteen flights which utilized pilot handoff, a pilot at one end of a 1.5 km path initiated the flight at 120m altitude over buildings and trees, and at the midway point of the path transferred radio control to a pilot at the other end. In comparison, the chase vehicle method requires less ground crew and simpler avionics, while the pilot handoff method avoids schedule risk arising from street traffic congestion but better replicates actual direct routing for BVLOS flights. Collision risk with another aircraft was introduced in both campaigns and mitigated with the same manual and autonomous methods. Results from these campaigns serve as a basis for planned BVLOS operations at NASA LaRC.

Nicholas Rymer↗
NASA NTRS2021

Architecture and Operations of the OSIRIS-REx Independent Navigation Team

The Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (OSIRIS-REx) GoddardSpace Flight Center (GSFC) Independent Navigation Team (INT) performs center-finding and landmark-basedOptical Navigation (OpNav), Orbit Determination (OD), maneuver verification, and additional analyses in support ofnavigation operations motivated by a stringent set of science requirements. The INT has adopted a streamlined andagile approach to navigation operations support via a virtual operations environment, known as "OREX-NAV",which leverages existing capabilities of the Space Science Mission Operations (SSMO) virtual Multi-MissionOperations Center (vMMOC). The virtual environment architecture of OREX-NAV enables the INT to perform dailyoperational tasks and seamlessly interface with external mission networks, regardless of physical location. Throughthe automation and process adopted, the INT is able to keep pace with the rapid cadence of required deliverables.

OSIRIS-REx↗
NASA NTRSDate not supplied

Achieving Resilient In-Flight Performance for Advanced Air Mobility through Simplified Vehicle Operations

A research and development (R&D) approach is proposed for developing and validating concepts and technologies to achieve vehicle autonomy goals of Advanced Air Mobility (AAM) through Simplified Vehicle Operations (SVO). The approach applies resilience-engineering and human-automation teaming (HAT) principles to a framework for defining vehicle-based functions for the management of missions and flight trajectories, focusing initially on the en route flight domain. To achieve the SVO goal of reducing pilot training requirements and thereby increasing the pilot pool for AAM, while at the same time promoting ever-safer operations, a framework for identifying essential functions is proposed. In this framework, functions are first categorized by high-level functional purpose (mission management, flightpath management, tactical operations, and vehicle control) and then subcategorized by attributes of resilient-performing systems (abilities to monitor, respond, learn, and anticipate). The categorization by functional purpose provides structure within which HAT designs can be holistically explored and total levels of human vs. automation responsibility can be varied. The subcategorization by resilient-system attributes provides a mechanism for capturing safety-critical functions that may not be codified in current operational procedures and training curricula, particularly those where humans proactively enhance safety in currently undocumented ways. An R&D approach consisting of seven strategies is proposed in which automation engineering and human-factors communities can collaborate in the research, development, and design of an SVO roadmap to enable the ambitious objectives of AAM.

AAM↗
NASA NTRSDate not supplied

Control Concepts for Simplified Vehicle Operations of a Quadrotor eVTOL Vehicle

Urban Air Mobility (UAM) is a future mode of transportation that will require revolutionary new vehicle concepts and operations. One of the many challenges that these vehicles face is a complex flight control task in a challenging urban environment and in different flight regimes such as hover, forward flight as well as the transitions between both, with a focus on a low workload and minimum required pilot training. This paper discusses the development and evaluation of simplified vehicle operations concepts using representative aircraft models, controls, inceptors and displays. These four aspects are inseparably interconnected. This simplified vehicle operations concept will be evaluated by performing relevant operations within a realistic urban environment. Handling quality evaluations will be performed using modified Mission Task Elements, or Handling Quality Task Elements. This paper focuses on the initial development of controls, inceptors and displays.

Thomas Lombaerts↗
NASA NTRS2020

Designing and Training for Appropriate Trust in Increasingly Autonomous Advanced Air Mobility Operations: A Mental Model Approach: Version 1

To enable effective human-autonomy teaming (HAT) in Advanced Air Mobility (AAM) operations, the current paper presents a theoretical framework to design and train for appropriate trust in automation. The novel contribution of this work resides in connecting the construct of trust to mental models and showing how this method could be used to enable emerging HAT concepts such as Adaptive Trust Calibration. To contextualize this framework, in section 2 we discuss simplified vehicle operations (SVO) and remote vehicle operations (RVO), which are leading operational concepts within AAM. In section 3 we describe our perspective on automation and increasingly autonomous systems and present a brief discussion on human-automation interaction and human-autonomy teaming. In section 4 we provide a detailed discussion on the construct of trust in automation. In section 5 we present a framework that associates mental models with trust through principles of transparent design. Finally, in section 6 we present three descriptive models for designing and training for appropriate trust in increasingly autonomous systems.

Human-Autonomy Teaming↗
NASA NTRSDate not supplied

Reducing Barriers in Space Weather Research and Operations with Next-Generation Simulation Services at the Community Coordinated Modeling Center (CCMC)

Space weather forecasting capabilities are becoming increasingly important to the health of advanced technological infrastructure. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) serves as a key liaison in the US space weather program between the research and operations communities by providing a wide range of tools and capabilities that help to evaluate, compare, exercise, and archive the results of simulations of a growing list of space weather models. With its unique toolset, CCMC supports space weather research and model development that advances our understanding of space weather phenomena and improves forecasting skill, while also facilitating development of space weather applications and deployment of operational capabilities. Guided by experience from over 20 years of providing simulation services, feedback from its research, operational and educational users world-wide, recommendations from CCMC Advisory Group and Programmatic Review Panel, the CCMC has begun work on the next generation system for its simulation services and model output archives. The new system has been envisioned to employ state-of-the-art technologies and standards to provide a user-oriented experience while improving ease of access, transparency, interoperability with partner systems, and enhancing reliability by incorporating advanced automation for performance monitoring and intelligent failover. In the presentation, we will give an overview of the current CCMC ecosystem and discuss updates to some of the key services of the system, including Runs-on-Request, Instant Runs, and Continuous Runs. We will also describe how a planned expansion and standardization of data archival activities will enhance the role of CCMC as a world-class provider of heliophysics information for the research and analysis of space weather. It is our hope that this evolution of the services can further reduce the barriers and burdens on researchers, forecasters and decision makers who rely on CCMC for their daily research and operations.

Space Weather↗
NASA NTRSDate not supplied

Artemis Innovative Assembly and Integration Operations of the Launch Abort Systemat KSC

This paper describes the Artemis program assembly and integration approach that enables affordable and low risk processing operations for the Launch Abort System at KSC. NASA is currently developing the Artemis 1 spacecraft to meet the test objectives of an uncrewed orbital mission to the moon and return to earth in 2021. The Artemis Orion spacecraft consists of a Crew Module (CM), a Service Module (SM), and a Launch Abort System (LAS) to safely transport a crew of 4 to the moon and return to earth. The LAS enables the CM to have an abort capability for the crew during the launch phase of the mission from the launch pad throughout the ascent phase. The LAS includes motor elements for abort, attitude control, and stage separation is assembled at the Launch Abort System Facility (LASF) adjacent to the CM/SM (CSM) assembly operations in the Neil Armstrong Operations and Checkout Building (O&C) at KSC. The LAS integration to the CSM is completed in the LASF and the completed Artemis spacecraft is integrated to the Space Launch System (SLS) in the Vehicle Assembly Building (VAB) at KSC. A significant LAS development flight test milestone was recently completed in 2019 for the Ascent Abort (AA-2) flight test at Cape Canaveral Air Force Station where a high-altitude abort test was successfully achieved using a Peacekeeper booster stage exercising all of the LAS systems including propulsion, avionics, and pyrotechnics demonstrating he LAS readiness for crewed flight. The first operational flight of the LAS will be for the Artemis 2 mission which is the first crewed mission for the Orion program planned in 2023.

William J Koenig↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗