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Multi-Agent Swarm State of the Art Report

The Next-Generation Multi-Agent Swarm (NGS) Study conducted by NASA’s Ames Research Center for NASA’s Space Technology Mission Directorate (STMD) will develop a comprehensive understanding of emerging multi-agent swarm capabilities. The study aims to identify existing swarm capabilities and asses their potential for persistent lunar space situational awareness, surface monitoring, and distributed autonomy demonstrations. A key objective is to inform the design of a next-generation multi-agent swarm that can perform autonomous distributed remote sensing, position, navigation, and timing (PNT) services, automated deployment that leverages autonomy, edge computing, and interoperable networking to enable cooperative operations without the need for immediate human operation. This study will address specific shortfalls identified by STMD, including intelligent multi-agent constellations, autonomy, edge computation, position, navigation, and timing for small spacecraft, small spacecraft propulsion, and space situational awareness (1625, 1438, 1433, 1557, 1431, 1430, 1589). The NASA Ames Mission Design Center (MDC) will provide subject matter expertise to support systems engineering trades, while experts in autonomy and spacecraft swarms in NASA’s Intelligent Systems Division will lead the study and focus on identifying emerging next-generation swarm capabilities. The study objectives include: capturing the current state-of-the-art for multi-agent swarm capabilities, evaluating technologies and creating technology roadmaps, and developing at least one new technology demonstration mission concept. This initial NGS study report surveys the current state of the art in technology areas relevant for the next-generation multi-agent swarm design. Our primary focus is on surveying relevant deployed space systems1, supplemented with selective analysis of relevant proposed missions and technology developments that have yet to fly.

agent

NASA Systems Autonomy Demonstration Project: Advanced Automation Demonstration of Space Station Freedom Thermal Control System

The NASA Systems Autonomy Demonstration Project (SADP) was initiated in response to Congressional interest in Space station automation technology demonstration. The SADP is a joint cooperative effort between Ames Research Center (ARC) and Johnson Space Center (JSC) to demonstrate advanced automation technology feasibility using the Space Station Freedom Thermal Control System (TCS) test bed. A model-based expert system and its operator interface were developed by knowledge engineers, AI researchers, and human factors researchers at ARC working with the domain experts and system integration engineers at JSC. Its target application is a prototype heat acquisition and transport subsystem of a space station TCS. The demonstration is scheduled to be conducted at JSC in August, 1989. The demonstration will consist of a detailed test of the ability of the Thermal Expert System to conduct real time normal operations (start-up, set point changes, shut-down) and to conduct fault detection, isolation, and recovery (FDIR) on the test article. The FDIR will be conducted by injecting ten component level failures that will manifest themselves as seven different system level faults. Here, the SADP goals, are described as well as the Thermal Control Expert System that has been developed for demonstration.

Jeffrey Dominick

Remote Guidance of a Mothership-Daughtership Formation for Asteroid Exploration

This work presents an application of Model Predictive Control to maintain long-term stability for a three-satellite formation around the asteroid Apophis via remote guidance. The mothership and two daughterships perform tomographic characterization with a bistatic radar. The mothership estimates the states of all three spacecraft and determines the necessary control to maintain the desired antipodal daughtership states. An Extended Kalman Filter estimates the mothership states. A Batch Least Squares algorithm estimates the daughtership states and performs maneuver reconstruction for the mothership-administered thrust commands under thruster and gravitational uncertainty. The formulation maintains the antipodal angle with growing instability amidst these uncertainties.

Guidance

Enabling Reliable, Fault-Tolerant Autonomous Lunar Habitats with High-Performance Spaceflight Computing

The lunar surface presents unfavorable constraints and harsh living conditions. To address these challenges, autonomous habitats will require complex integrated systems that combine advanced software, high-performance hardware, and cutting-edge sensors to ensure sustainability, safety, and operational efficiency. Consequently, maintaining a sustainable presence on the Moon requires reliable infrastructure and efficient development, precise monitoring, and utilization of resources within a lunar installation. These elements are essential not only to ensure that lunar settlement can be long-term, self-sustaining, and resource-efficient, but also to serve as a foundation for future missions and eventual human habitation on Mars. Humans are not native to the Moon; therefore, our survival and ability to thrive will depend on autonomous systems that can foster safety and resilience through high-availability architectures, graceful degradation, and highly fault-tolerant spaceflight hardware capable of continuing operation during failures. This requires advanced human-rated distributed systems architectures with specialized electronics, scalable capabilities, and an integrated design approach. Unlike current practices focused on short-term missions and regularly maintained components, permanent lunar compute systems must be designed for extended operations beyond mission durations. This paper explores the necessity of transitioning toward fault- tolerant, highly autonomous hardware systems designed for multi-year missions. It also identifies critical subsystems that require high levels of autonomy, supported by radiation-hardened processors and extreme thermal loads, which are essential to mitigate long-term degradation and ensure sustainable lunar habitation. Finally, the paper aligns with NASA’s identified Civil Space Shortfalls, particularly in high-performance onboard computing, advanced data acquisition, extreme-environment avionics, radiation monitoring and countermeasures, and autonomous health management. It proposes NASA’s new High-Performance Spaceflight Computing (HPSC) processor as a turnkey solution, delivering 100 times the performance-per-watt of legacy rad-hard CPUs and enabling onboard AI, edge computing, and fault-tolerant features essential for sustained lunar autonomy and beyond.

Sarkis S Mikaelian

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl

Parallel Processing and Expert Systems

Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 90's cannot enjoy an increased level of autonomy without the efficient use of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real time demands are met for large expert systems. Speed-up via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial labs in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems was surveyed. The survey is divided into three major sections: (1) multiprocessors for parallel expert systems; (2) parallel languages for symbolic computations; and (3) measurements of parallelism of expert system. Results to date indicate that the parallelism achieved for these systems is small. In order to obtain greater speed-ups, data parallelism and application parallelism must be exploited.

Jerry C Yan

Power Optimal Control Allocation for Distributed Electric Propulsion in a Series/Parallel Hybrid Powertrain

This paper describes a thrust allocation scheme that minimizes power consumption in an electrified powertrain with Distributed Electric Propulsion. It takes advantage of an observation about component efficiency maps, that efficiency is often highest at high torque/high speed conditions. This optimal approach is demonstrated to satisfy total thrust and net yaw axis torque requirements, making it suitable for utilizing differential thrust for maneuvering.

electrified aircraft propulsion

Power Optimal Control Allocation for Distributed Electric Propulsion in a Series/Parallel Hybrid Powertrain

This paper describes a thrust allocation scheme that minimizes power consumption in an electrified powertrain with Distributed Electric Propulsion. It takes advantage of an observation about component efficiency maps, that efficiency is often highest at high torque/high speed conditions. This optimal approach is demonstrated to satisfy total thrust and net yaw axis torque requirements, making it suitable for utilizing differential thrust for maneuvering.

electrified aircraft propulsion

Power Optimal Control Allocation for Distributed Electric Propulsion in a Series/Parallel Hybrid Powertrain

This paper describes a thrust allocation scheme that minimizes power consumption in an electrified powertrain with Distributed Electric Propulsion. It takes advantage of an observation about component efficiency maps, that efficiency is often highest at high torque/high speed conditions. This optimal approach is demonstrated to satisfy total thrust and net yaw axis torque requirements, making it suitable for utilizing differential thrust for maneuvering.

electrified aircraft propulsion

Mass Economy Evaluation for Integrated ECLSS and Propulsion Architecture

As missions in Low Earth Orbit (LEO) lengthen and extend to deep space, minimizing resupply needs becomes vital for sustaining crewed operations. Traditional life support systems depend on consumables resupplied from Earth, a method that is increasingly impractical for missions beyond LEO, such as lunar outposts or Mars transit. Long-duration missions require more efficient, autonomous systems that can recycle essential resources, particularly water and oxygen, to minimize the frequency and mass of resupply missions. The Environmental Control and Life Support System (ECLSS) is essential to such missions, with the International Space Station (ISS) serving as a testbed for advanced water recovery and partial oxygen recycling via physico-chemical methods. Yet, ECLSS and propulsion subsystems generally operate independently, despite overlapping requirements and potential areas for synergy. For instance, ECLSS byproducts, water, CO₂, and hydrogen, could be repurposed for propulsion, potentially reducing dedicated propellant mass and increasing overall system efficiency. One promising approach is to develop shared-resource architectures that integrate ECLSS with propulsion systems. This study examines the potential of such integration through the Sabatier CO₂ reduction process, focusing on water management as a key factor in system mass trade-offs. The Sabatier reaction produces water and methane from metabolic CO₂ and electrolytic hydrogen, partially closing the life support loop and providing methane, which could serve as a propellant. This integration could minimize waste, reduce resupply requirements, and enhance mission mass efficiency. A dynamic modeling framework will be used to simulate resource flows over long missions, capturing interactions between life support and propulsion. By comparing integrated versus separate system configurations, the study aims to quantify mass benefits and penalties, informing future habitat designs and trade studies for missions prioritizing autonomy and mass efficiency.

ECLSS

Mass Economy Evaluation for Integrated ECLSS and Propulsion Architecture

As missions in low Earth orbit (LEO) lengthen and extend to deep space, minimizing resupply needs becomes vital for sustaining crewed operations. Traditional life support systems depend on consumables resupplied from Earth, a method that is increasingly impractical for missions beyond LEO, such as lunar outposts or Mars transit. Long-duration missions require more efficient, autonomous systems that can recycle essential resources, particularly water and oxygen, to minimize the frequency and mass of resupply missions. The Environmental Control and Life Support System (ECLSS) is essential to such missions, with the International Space Station (ISS) serving as a testbed for advanced water recovery and partial oxygen recycling via physico-chemical methods. Yet, ECLSS and propulsion subsystems generally operate independently, despite overlapping requirements and potential areas for synergy. For instance, ECLSS byproducts, water, CO 2 , and hydrogen, could be repurposed for propulsion, potentially reducing dedicated propellant mass and increasing overall system efficiency. One promising approach is to develop shared-resource architectures that integrate ECLSS with propulsion systems. This study examines the potential of such integration through the Sabatier CO₂ reduction process, focusing on water management as a key factor in system mass trade-offs. The Sabatier reaction produces water and methane from metabolic CO 2 and electrolytic hydrogen, partially closing the life support loop and providing methane, which could serve as a propellant. This integration could minimize waste, reduce resupply requirements, and enhance mission mass efficiency. A dynamic modeling framework will be used to simulate resource flows over long missions, capturing interactions between life support and propulsion. By comparing integrated versus separate system configurations, the study aims to quantify mass benefits and penalties, informing future habitat designs and trade studies for missions prioritizing autonomy and mass efficiency.

ECLSS

Augmentation of the Space Station Module Power Management and Distribution Breadboard

The space station module power management and distribution (SSM/PMAD) breadboard models power distribution and management, including scheduling, load prioritization, and a fault detection, identification, and recovery (FDIR) system within a Space Station Freedom habitation or laboratory module. This 120 VDC system is capable of distributing up to 30 kW of power among more than 25 loads. In addition to the power distribution hardware, the system includes computer control through a hierarchy of processes. The lowest level consists of fast, simple (from a computing standpoint) switchgear that is capable of quickly safing the system. At the next level are local load center processors, (LLP's) which execute load scheduling, perform redundant switching, and shed loads which use more than scheduled power. Above the LLP's are three cooperating artificial intelligence (AI) systems which manage load prioritizations, load scheduling, load shedding, and fault recovery and management. Recent upgrades to hardware and modifications to software at both the LLP and AI system levels promise a drastic increase in speed, a significant increase in functionality and reliability, and potential for further examination of advanced automation techniques. The background, SSM/PMAD, interface to the Lewis Research Center test bed, the large autonomous spacecraft electrical power system, and future plans are discussed.

Bryan Walls

The thermal engine of Venus: Implications from the impact crater distribution

Questions concerning the state of Venus' volcanological activity are currently under investigation. These questions were raised by the imaging radar and altimetric data obtained by the Magellan spacecraft, which began mapping Venus in Sept. 1990. Clues about the answers to these questions are provided by the nature and distribution of impact craters on the surface of Venus. Statistical tests show that the distribution of craters on Venus cannot be distinguished from a completely spatially random population. Further, the majority of craters look relatively pristine; only about 5 percent of the observed craters appear to be embayed or flooded by lavas. The simplest interpretation of these observations is a model in which the impact craters lie on a surface that has been undisturbed by volcanological and tectonic processes since the time the surface was formed. Counting up the number of craters and estimating the rate at which meteoroids strike the surface then gives an age for the venusian surface of 500 million years; in this model the volcanic activity since that time has been essentially nil. This scenario is described as a 'production' model, or perhaps more appropriately, a 'catastrophic' model.

Phillips, Roger J.

Automatic battery formation cycler and controller

Automatic battery formation cycler and controller to determine charge capacity and to perform charge-discharge operations for electrochemical cells intended for satellite power sources

CHARGE DISTRIBUTION