Supporting Astronaut Autonomous Operations in Future Deep Space Missions
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Natalia Russi-Vigoya↗
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Multi-Beam Range Imager for Autonomous Operations
For space operations using Space Station Freedom, the real-time range imager will be very valuable in terms of refueling and docking, as well as space exploration.
robotics↗
Auto-Gopher-II – A wireline rotary-hammer ultrasonic drill that operates autonomously
An important challenge of exploring the solar system is the ability to penetrate at great depths the subsurface of planetary bodies for sample collection. The requirements of the drilling system are minimal mass, volume and energy consumption. To address this challenge, a deep drill, called the Auto-Gopher II, is currently being developed as a joint effort between JPL’s NDEAA laboratory and Honeybee Robotics Corp. The Auto-Gopher II is a wireline rotaryhammer drill that combines breaking formations by hammering using a piezoelectric actuator and removing the cuttings by rotating a fluted bit. The hammering is produced by the Ultrasonic/Sonic Drill/Corer (USDC) mechanism that has been developed by the JPL team as an adaptable tool for many drilling and coring applications. The USDC uses an intermediate free-flying mass to convert high frequency vibrations of a piezoelectric transducer horn tip into sonic hammering of the drill bit. The USDC concept was used in a previous task to develop an Ultrasonic/Sonic Ice Gopher and then integrated into a rotary hammer device to develop the Auto-Gopher-I. The lessons learned from these developments are being integrated into the development of the Auto-Gopher-II, an autonomous deep wireline drill with integrated cuttings and sample management and drive electronics. In this paper the latest development will be reviewed including the piezoelectric actuator, cuttings removal and retention flutes and drive electronics.
Paulsen, Gale L.↗
NASA SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis
Using state-of-the-art artificial intelligence (AI)frameworks onboard spacecraft is challenging because common spacecraft processors cannot provide comparable performance to datacenters with server-grade CPUs and GPUs available for terrestrial applications and advanced deep-learning networks. This limitation makes small, lo w-p o we r AI microchip architectures, such as the Google Coral Edge Tensor Processing Unit (TPU), attractive for space missions where the application-specific design enables both high-performance and power-efficient computing for AI applications. To address these challenging considerations for space deployment, this research introduces the design and capabilities of a CubeSat-sized Edge TPU-based co-processor card, known as the SpaceCube Low-power Ed g e Artificial Intelligence Resilient Node (SC-LEARN). This design conforms to NASA’s CubeSat Card Specification (CS2) for integration into next-generation SmallSat and CubeSat systems. This paper describes the overarching architecture and design of the SC-LEARN, as well as, the supporting test card designed for rapid prototyping and evaluation. The SC-LEARN was developed with three operational modes: (1) a high-performance parallel-processing mode,(2)a fault-tolerant mode for onboard resilience, and (3) a power-saving mode with cold spares. Importantly, this research also elaborates on both training and quantization of Tensor Flow models for the SC-LEARN for use onboard with representative, open-source datasets. Lastly, we describe future research plans, including radiation-beam testing and flight demonstration.
Advanced avionics↗
Towards Alternative Position, Navigation and Timing Technologies supporting Autonomous Operations for Advanced Air Mobility
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APNT PNT GPS AAM Autonomy↗
High Density Vertiplex Sub-Project: Scalable Autonomous Operations(SAO) Prototype Assessment HHITL Sim/Flight Test
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Louis J Glaab↗
High Density Vertiplex: Scalable Autonomous Operations Prototype Assessment Simulation
Urban Air Mobility (UAM) is a rapidly growing topic within the field of aviation because of the impact a refined ecosystem and uncrewed aerial vehicles could have on modern society, such as urban air mobility, cargo, and emergency transport. Before the UAM concept can be actualized, research is needed to understand how to integrate these new classes of vehicles and operations into the National Airspace System. One under-researched but critical piece of infrastructure required for UAM operations is Vertiport operations. Vertiports are the envisioned takeoff and landing locations for these uncrewed aerial vehicles. To accommodate the high use of the vertiport, new technologies and roles will be required for optimal use. At NASA, the High Density Vertiplex sub-project targets research into vertiports. The High Density Vertiplex team created an Urban Air Mobility ecosystem to test and evaluate different concepts and tools used to support higher density operations at vertiports. Part of the test and evaluation included the Prototype Assessment Operations simulation of highdensity operations around a vertiport to study vertiport management and vertiport operations. The research team also evaluated how the prototype Urban Air Mobility ecosystem supported fleet managers, ground control station operators, and vertiport managers in execution of nominal and off-nominal high-density operations. Results from this simulation provided insight regarding UAM ecosystem research and development and vertiport automation systems.
Small Uncrewed Aerial Vehicle (sUAS)↗
High Density Vertiplex: Scalable Autonomous Operations Prototype Assessment Simulation
Urban Air Mobility is a rapidly growing topic within the field of aviation because of the impact a refined ecosystem and uncrewed aerial vehicles could have on modern society, such as urban air, cargo, and emergency transport. Before the UAM concept can be actualized, research is needed to understand how to integrate these new classes of vehicles and operations into the National Airspace System. One under-researched but critical piece of infrastructure required for UAM operations is Vertiport operations. Vertiports are the envisioned takeoff and landing locations for these uncrewed aerial vehicles. To accommodate the high use of the vertiport, new technologies and roles will be required for optimal use. At NASA, the High Density Vertiplex sub-project targets research into vertiports. The High Density Vertiplex team created their own Advanced Air Mobility ecosystem to test and evaluate different concepts and tools used to support higher density operations at vertiports. Part of the test and evaluation included the Prototype Assessment Operations simulation of high-density operations around a vertiport to study vertiport management and vertiport operations. The research team also evaluated how their simulated Urban Air Mobility ecosystem supported fleet managers, ground control station operators, and vertiport managers in execution of nominal and off-nominal high-density operations. Takeaways from this simulation helped the team evaluate well how the users of the ecosystem were able to use the components of the ecosystem to complete Urban Air Mobility missions.
Small Uncrewed Aerial Vehicle (sUAS)↗
System for the highly autonomous operation of a modular liquid-metal reactor with steam cycle
The invention relates to a nuclear plant in which the power of a nuclear reactor is controlled via demand of a connected electric grid. A naturally circulating nuclear reactor coolant loop is linked to a water/steam loop by means of a steam generator. The water/steam loop consists of an electric power generating unit and a water recirculating and steam control system. The generator is coupled to an external power grid. As power requirements of the grid change, a controller linked to the generator and a three way valve divides steam flow between the expansion turbine and a feedwater heater to boost or retard the power output. Altering the steam flow changes the pressure and temperature in the water/steam system and thus the coolant flow rate. The change in coolant flow allows the reactor core to regulate its reactivity to reach a state of equilibrium to the demand for electric power.
Vilim, Richard B.↗
Adaptive Multi-Sensor Fusion Based Object Tracking for Autonomous Urban Air Mobility Operations
Autonomous operations are a crucial aspect in the context of Urban Air Mobility and other emerging aviation markets. In order to enable this autonomy, systems must be able to build independently an accurate and detailed understanding of the own vehicle state as well as the surrounding environment, this includes detecting and avoiding moving objects in the sky, which can be cooperative (aircraft, UAM vehicles, etc.) as well as noncooperative (smaller drones, birds, ...). This paper focuses on the object tracking part that relies on adaptive multi-sensor fusion, taking into account specific properties and limitations of different sensor types. Results show the impact of dropouts of individual sensors on the accuracy of the tracking results for this adaptive sensor fusion approach.
sensor fusion↗
Adaptive Multi-Sensor Fusion Based Object Tracking for Autonomous Urban Air Mobility Operations
Autonomous operations are a crucial aspect in the context of Urban Air Mobility and other emerging aviation markets. In order to enable this autonomy, systems must be able to build independently an accurate and detailed understanding of the own vehicle state as well as the surrounding environment, this includes detecting and avoiding moving objects in the sky, which can be cooperative (aircraft, UAM vehicles, etc.) as well as noncooperative (smaller drones, birds, ...). This paper focuses on the object tracking part that relies on adaptive multi-sensor fusion, taking into account specific properties and limitations of different sensor types. Results show the impact of dropouts of individual sensors on the accuracy of the tracking results for this adaptive sensor fusion approach.
object tracking↗
Distributed Ground Sensor Fusion Based Object Tracking for Autonomous Advanced Air Mobility Operations
Autonomous operations are a crucial aspect in the context of Advanced Air Mobility and other emerging aviation markets. In order to enable this autonomy, an accurate and detailed understanding of the positions of the various vehicles in the air is necessary. Full localization independent of on-board sensors makes the system suitable for noncooperative vehicles. This paper focuses on the object tracking part that relies on distributed ground-based sensor fusion, considering specific properties and limitations of different sensor types. Results show satisfactory performance in nominal scenarios with full coverage. Dropouts of individual sensors affect the accuracy of the tracking results, which agrees with expectations for partial coverage, when full localization is not achievable anymore. Finally, a study is performed to identify which parameters have the largest impact on the fit error.
Autonomous↗
Autonomous System Operations for Lunar Safe Haven Establishment and Sustainment
To enable a sustainable, permanent human lunar presence, NASA must provide a safe haven shelter to protect astronauts and equipment from radiation, thermal extremes, and micro-meteoroids (MM). Planning and development for a robust Safe Haven includes an examination of NASA activities in site preparation, excavation, regolith transfer, surface operations, autonomous monitoring and maintenance, advanced manufacturing, and in-situ resource utilization (ISRU) for identifying the best approaches when implementing a safe haven shelter. These NASA activities were reviewed as a part of a trade study conducted at NASA Langley to assess technological needs and estimated technology readiness levels (TRL). This paper presents a thorough review of the role and level of autonomy in the establishment and sustainment operations of a Lunar Safe Haven.
Walter J Waltz↗
Autonomous System Operations for Lunar Safe Haven Establishment and Sustainment
To enable a sustainable, permanent human lunar presence, NASA must provide a safe haven shelter to protect astronauts and equipment from radiation, thermal extremes, and micro-meteoroids (MM). Planning and development for a robust Safe Haven includes an examination of NASA activities in site preparation, excavation, regolith transfer, surface operations, autonomous monitoring and maintenance, advanced manufacturing, and in-situ resource utilization (ISRU) for identifying the best approaches when implementing a safe haven shelter. These NASA activities were reviewed as a part of a trade study conducted at NASA Langley to assess technological needs and estimated technology readiness levels (TRL). This paper presents a thorough review of the role and level of autonomy in the establishment and sustainment operations of a Lunar Safe Haven.
Walter J Waltz↗
Autonomous Cryogenic Load Operations: KSC Autonomous Test Engineer
The KSC Autonomous Test Engineer (KATE) program has a long history at KSC. Now a part of the Autonomous Cryogenic Load Operations (ACLO) mission, this software system has been sporadically developed over the past 20+ years. Originally designed to provide health and status monitoring for a simple water-based fluid system, it was proven to be a capable autonomous test engineer for determining sources of failure in. the system, As part.of a new goal to provide this same anomaly-detection capability for a complicated cryogenic fluid system, software engineers, physicists, interns and KATE experts are working to upgrade the software capabilities and graphical user interface. Much progress was made during this effort to improve KATE. A display ofthe entire cryogenic system's graph, with nodes for components and edges for their connections, was added to the KATE software. A searching functionality was added to the new graph display, so that users could easily center their screen on specific components. The GUI was also modified so that it displayed information relevant to the new project goals. In addition, work began on adding new pneumatic and electronic subsystems into the KATE knowledgebase, so that it could provide health and status monitoring for those systems. Finally, many fixes for bugs, memory leaks, and memory errors were implemented and the system was moved into a state in which it could be presented to stakeholders. Overall, the KATE system was improved and necessary additional features were added so that a presentation of the program and its functionality in the next few months would be a success.
Shrading, Nicholas J.↗
Autonomous System Subversion Tactics: Prototypes and Recommended Countermeasures
One of the fielding requirements for Advanced and Small Modular Reactors (AR/SMR) is the ability to support remote and autonomous operations. Autonomous Control Systems (ACS) are found on platforms such as Autonomous Space Vehicles, Cruise Missiles, and advanced driver-assistance systems. Each of these ACS implementations depends upon a set of decision support subsystems responsible for supporting Autonomous Mission Managers (names vary based upon field and author preferences). These Autonomous Mission Managers receive inputs from system sensors (e.g., LIDAR collection from an automobile travelling down a street; transients from a nuclear reactor), and perform a set of classifications (e.g., Red Traffic Light; Small Pedestrian at 10m; Load Rejection; Single Coolant Pump Trip), and then use these classifications in combination with recommendation algorithms to achieve platform goals (e.g., Stop the Vehicle at the Traffic Light, Avoid the Small Pedestrian; Trip the Reactor to prevent a Safety Event). The design, implementation, and fielding of an ACS capability will alter the cyber-attack surface such that existing risk management plans will need to be updated to include how to protect and defend against data-science and decision-support-system attack classes. These attack classes would include protection of the design and training environments where algorithm selection and testing and training data would be obvious attack vectors. These attack classes would also require an informed set of detection and response procedures to identify anomalous behaviors and document best practices for anomaly assessment and vulnerability mitigation and remediation. Last year we published a Cyber Threat Assessment Methodology for Autonomous and Remote Operations for AR/SMRs along with a companion publication on Cyber Attack and Defense Use Cases. The focus of the methodology was on describing and enumerating ACS processes, components, and functions such that security engineers could: evaluate subversion options against the target; identify threat actor attributes and capabilities derived from each subversion option; and identify security controls and response countermeasures. The Use Cases document offered detailed methodology examples including an assessment of a Military Base SMR, an Autonomous System Decision Loop, and implementation of AR/SMR Machine Learning algorithms. Our proposal at the end of last year was to focus on implementation of subversion prototypes related to the last Use Case area: AR/SMR Machine Learning (ML) Algorithms. We included six attack scenarios in our Use Cases paper: a Poisoning Attack against ML functions implemented using an FPGA; a Trojaning Attack against ML classifiers exploiting the excitability of Nuclear Engineers; a Backdooring Attack against ML Training environments to ensure persistence of an attack vector; a False Positive Evasion Attack against multi-factor Access Control Systems using clever inputs; an Inference Attack against ML models by an Insider with access to the Operational environment; and an Adversarial Reprogramming Attack against a Material Access Control Video Surveillance System. At the beginning of this year these six attack scenarios were provided to our research teams at Georgia Tech and Idaho State University and each team successfully implemented a subversion attack against a ML implementation to include transient misclassifications. While this is a notable outcome from this type of research, this paper offers the reader insight into not only how to structure and execute these types of attacks, but into the thought process behind how the researcher investigated the problem space, performed initial algorithm implementation, and the trial-and-error behind arriving at the successful subversion prototypes. We include in this paper a set of associated Scenarios on how these subversion prototypes could be implemented and an initial set of guidance for AR/SMR architects, Nuclear Regulators, and Cyber Defenders to implement awareness and defense capabilities into their current operational portfolios.
42 ENGINEERING↗
NASA Study: Interruptions in Multi-Vehicle Supervision (DRACO) (Distracted Remote-operators in Autonomous Concepts of Operation 2024)
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workload↗
Advanced Communication Architectures and Technologies for Missions to the Outer Planets
Missions to the outer planets would be considerably enhanced by the implementation of a future space communication infrastructure that utilizes relay stations placed at strategic locations in the solar system. These relay stations would operate autonomously and handle remote mission command and data traffic on a prioritized demand access basis. Such a system would enhance communications from that of the current direct communications between the planet and Earth. The system would also provide high rate data communications to outer planet missions, clear communications paths during times when the sun occults the mission spacecraft as viewed from Earth, and navigational "lighthouses" for missions utilizing onboard autonomous operations. Additional information is contained in the original extended abstract.
Bhasin, K.↗