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NASA NTRSDate not supplied

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 NTRS2006

Integrating Terrain Maps Into a Reactive Navigation Strategy

An improved method of processing information for autonomous navigation of a robotic vehicle across rough terrain involves the integration of terrain maps into a reactive navigation strategy. Somewhat more precisely, the method involves the incorporation, into navigation logic, of data equivalent to regional traversability maps. The terrain characteristic is mapped using a fuzzy-logic representation of the difficulty of traversing the terrain. The method is robust in that it integrates a global path-planning strategy with sensor-based regional and local navigation strategies to ensure a high probability of success in reaching a destination and avoiding obstacles along the way. The sensor-based strategies use cameras aboard the vehicle to observe the regional terrain, defined as the area of the terrain that covers the immediate vicinity near the vehicle to a specified distance a few meters away.

Howard, Ayanna↗
NASA NTRS2013

Closed Loop Terminal Guidance Navigation for a Kinetic Impactor Spacecraft

A kinetic impactor spacecraft is a viable method to deflect an asteroid which poses a threat to the Earth. The technology to perform such a deflection has been demonstrated by the Deep Impact (DI) mission, which successfully collided with comet Tempel 1 in July 2005 using an onboard autonomous navigation system, called AutoNav, for the terminal phase of the mission. In this paper, we evaluate the ability of AutoNav to impact a wide range of scenarios that an deflection mission could encounter, varying parameters such as the approach velocity, phase angle, size of the asteroid, and the determination of spacecraft attitude. Using realistic Monte Carlo simulations, we tabulated the probability of success of the deflection as a function of these parameters, and the highest sensitivity to be due the spacecraft attitude determination mode. In addition, we also specifically analyzed the impact probability for a proposed mission which would send an impactor to the asteroid 1999RQ36. We conclude with some recommendations for future work.

closed loop guidance↗
NASA NTRS1978

On-board landmark navigation and attitude reference parallel processor system

An approach to autonomous navigation and attitude reference for earth observing spacecraft is described along with the landmark identification technique based on a sequential similarity detection algorithm (SSDA). Laboratory experiments undertaken to determine if better than one pixel accuracy in registration can be achieved consistent with onboard processor timing and capacity constraints are included. The SSDA is implemented using a multi-microprocessor system including synchronization logic and chip library. The data is processed in parallel stages, effectively reducing the time to match the small known image within a larger image as seen by the onboard image system. Shared memory is incorporated in the system to help communicate intermediate results among microprocessors. The functions include finding mean values and summation of absolute differences over the image search area. The hardware is a low power, compact unit suitable to onboard application with the flexibility to provide for different parameters depending upon the environment.

Gilbert, L. E.↗
NASA NTRS2005

Cerebellum Augmented Rover Development

Bio-Inspired Technologies and Systems (BITS) are a very natural result of thinking about Nature's way of solving problems. Knowledge of animal behaviors an be used in developing robotic behaviors intended for planetary exploration. This is the expertise of the JFL BITS Group and has served as a philosophical model for NMSU RioRobolab. Navigation is a vital function for any autonomous system. Systems must have the ability to determine a safe path between their current location and some target location. The MER mission, as well as other JPL rover missions, uses a method known as dead-reckoning to determine position information. Dead-reckoning uses wheel encoders to sense the wheel's rotation. In a sandy environment such as Mars, this method is highly inaccurate because the wheels will slip in the sand. Improving positioning error will allow the speed of an autonomous navigating rover to be greatly increased. Therefore, local navigation based upon landmark tracking is desirable in planetary exploration. The BITS Group is developing navigation technology based upon landmark tracking. Integration of the current rover architecture with a cerebellar neural network tracking algorithm will demonstrate that this approach to navigation is feasible and should be implemented in future rover and spacecraft missions.

King, Matthew↗
NASA NTRS2013

Unified Simulation and Analysis Framework for Deep Space Navigation Design

As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.

Anzalone, Evan↗
NASA NTRS2013

Terminal Guidance Navigation for an Asteroid Impactor Spacecraft

Near Earth Asteroids could potentially cause a great deal of devastation if one were to impact the Earth. If such an asteroid were found, the next step would be to mitigate the threat by one of several options, the most viable of which is to deflect the asteroids trajectory such that it misses the Earth by hitting it at a very high velocity with a spacecraft. The technology to perform such a deflection has been demonstrated by the Deep Impact (DI) mission, which successfully collided with comet Tempel 1 in July 2005 using an onboard autonomous navigation system, called AutoNav, for the terminal phase of the mission. In this paper, we evaluate the ability of AutoNav to impact a wide range of scenarios that an deflection mission could encounter, varying parameters such as the approach velocity, phase angle, size of the asteroid, and the determination of spacecraft attitude. Using realistic Monte Carlo simulations, we tabulated the probability of success of the deflection as a function of these parameters, and find the highest sensitivity to be due the spacecraft attitude determination mode. We conclude with some recommendations for future work.

autonomous navigation↗
NASA NTRS2026

X-Hab 2026: LiDAR-Powered Autonomous Charging Service Capability for Surface Rovers and Systems

This document details the timeline of the LiDAR-Powered Autonomous Charging Service Capability for Surface Rovers and Systems project, initiated by the Fall 2025 semester class and completed by the Spring 2026 semester class. This project focuses on developing a fully autonomous system composed of a mobile surface rover and an induction charging station with a robotic arm, both controlled by their own NVIDIA Jetson Orin Nano. Structural improvements to the rover suspension system and body eliminated excessive camber, reduced stress and strain on the plexiglass body, and improved maneuverability and durability of the rover. The charging station robotic arm was fully redesigned to increase reach while minimizing weight and increasing misalignment tolerance during docking on uneven terrain. Electrical system improvements addressed previous torque and power limitations of both the rover and charging station arm. High-torque servo motors were selected based on updated calculations which incorporated terrain slope and Factor of Safety, enabling zero-point turning for the rover and increased payload capacity of the charging station arm. Significant progress was made in autonomy and perception. The rover now employs 3D LiDAR and SLAM mapping for localization, mapping, and path planning. The Battery Monitoring System (BMS) was created to coordinate battery management between the rover and charging station. The BMS provides continuous monitoring of battery state of charge, temperature, current, and will enable the autonomous initiation, execution, and termination of the charging cycle via Bluetooth communication. Testing of the WIBOTIC induction charging system demonstrated reliable power transfer under both aligned and misaligned conditions. This project demonstrated the ability of an autonomously navigating surface rover to independently plan a path to the charging station, dock, and the charging station to autonomously deploy a robotic charging arm and initiate charging of the rover. This work details the progress made to demonstrate the feasibility of autonomous surface rover navigation and recharging systems.

Megan Steele↗
DOE OSTI2025

Sim2Real Autonomous Robotic Exploration [Poster]

Autonomous robots offer promising solutions for exploration in environments that are inaccessible or hazardous to humans. Despite this, physical training of such robots is often constrained by safety risks, high cost or limited accessibility. This project presents an end-to-end simulation to reality pipeline leveraging Nvidia Isaac Sim and Boston Dynamics' Spot to enable autonomous navigation in indoor environments. A reinforcement learning policy is first trained using Nvidia Isaac Lab to establish Spot's locomotion pattern. Virtual LiDAR sensors are then integrated to perform SLAM-based navigation using simulated odometry. Finally, the simulated navigation scheme is transferred to a physical Spot robot to inspect and record images of a real-world room by repeating the learnt trajectory. The proposed framework highlights the potential of scalable training in simulation and reliable deployment in physical environments. Future directions include dynamic trajectory generation in unseen and challenging environments and integration of environmental sensing like temperature, radiation or humidity via sensor and material simulation.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2002

Safe navigation on hazardous terrain

This paper presents a new strategy for autonomous navigation of field mobile robots on hazardous natural terrain using a fuzzy logic approach and a novel measure of terrain transversability.

mobile↗
NASA NTRS2004

Libration Point Navigation Concepts Supporting the Vision for Space Exploration

This work examines the autonomous navigation accuracy achievable for a lunar exploration trajectory from a translunar libration point lunar navigation relay satellite, augmented by signals from the Global Positioning System (GPS). We also provide a brief analysis comparing the libration point relay to lunar orbit relay architectures, and discuss some issues of GPS usage for cis-lunar trajectories.

Carpenter, J. Russell↗
NASA NTRS2003

Navigating a Mobile Robot Across Terrain Using Fuzzy Logic

A strategy for autonomous navigation of a robotic vehicle across hazardous terrain involves the use of a measure of traversability of terrain within a fuzzy-logic conceptual framework. This navigation strategy requires no a priori information about the environment. Fuzzy logic was selected as a basic element of this strategy because it provides a formal methodology for representing and implementing a human driver s heuristic knowledge and operational experience. Within a fuzzy-logic framework, the attributes of human reasoning and decision- making can be formulated by simple IF (antecedent), THEN (consequent) rules coupled with easily understandable and natural linguistic representations. The linguistic values in the rule antecedents convey the imprecision associated with measurements taken by sensors onboard a mobile robot, while the linguistic values in the rule consequents represent the vagueness inherent in the reasoning processes to generate the control actions. The operational strategies of the human expert driver can be transferred, via fuzzy logic, to a robot-navigation strategy in the form of a set of simple conditional statements composed of linguistic variables. These linguistic variables are defined by fuzzy sets in accordance with user-defined membership functions. The main advantages of a fuzzy navigation strategy lie in the ability to extract heuristic rules from human experience and to obviate the need for an analytical model of the robot navigation process.

Seraji, Homayoun↗
NASA NTRS2018

Initial Results of the Software-Driven Navigation for Station Experiment

To enable the next generation of robotic and human exploration of the solar system, improvements are needed to enable robust and accurate autonomous navigation. The purpose of this work is to take advantage of the growth in and use of software-defined platforms to incorporate additional navigation capability on existing assets, while also incorporating with new vehicle designs. The Software-driven Navigation for Station Experiment focuses on implementing two soft solutions to this: transmitting pseudolite signals to perform ranging and Doppler measurements as part of the signal coding (similar to underlying Global Navigation Satellite System approaches), and the Multi-spacecraft Autonomous Positioning System, which uses existing communication protocols to embed navigation and timing information to be shared among all assets in a peer-to-peer network. These technologies were implemented on the SCaN Testbed onboard the International Space Station and exercised over the course of mid-June and late-July 2018. This paper will discuss the operational architecture, experiment plan, and initial results from the data collected. One of the key conclusions of this work is the strong need for stable accurate clock synchronization across the dispersed space network.

Anzalone, Evan J.↗
NASA NTRS2013

The Role of X-Rays in Future Space Navigation and Communication

In the near future, applications using X-rays will enable autonomous navigation and time distribution throughout the solar system, high capacity and low-power space data links, highly accurate attitude sensing, and extremely high-precision formation flying capabilities. Each of these applications alone has the potential to revolutionize mission capabilities, particularly beyond Earth orbit. This paper will outline the NASA Goddard Space Flight Center vision and efforts toward realizing the full potential of X-ray navigation and communications.

Winternitz, Luke M. B.↗
NASA NTRS2022

Terrain Relative Navigation in a Lunar Landing Scenario Using autoNGC

NASA Goddard Space Flight Center is developing Autonomous Navigation Guidance and Control (autoNGC) as a flight software system for future onboard use for missions in a variety of orbital regimes, including cislunar space and beyond. This paper describes processor-in-the-loop (PIL) testing using a lunar landing scenario with terrain relative navigation (TRN) and weak-signal GPS. We give an overview of the autoNGC project and describe preliminary navigation simulation results. We also describe the TRN PIL tests on a flight-like development board, using simulated images rendered from Lunar Reconnaissance Orbit high-resolution digital terrain models. The navigation simulations show that weak-signal GPS combined with TRN during a descent from a low lunar parking orbit results in sufficiently low navigation uncertainties to support such a mission profile independent of ground-based navigation. The PIL tests show that onboard image processing and landmark correlation is achievable at a sufficiently high measurement rate.

Michael A Shoemaker↗
NASA NTRS2006

Key Issues for Navigation and Time Dissemination in NASA's Space Exploration Program

The renewed emphasis on robotic and human missions within NASA's space exploration program warrants a detailed consideration of how the positions of objects in space will be determined and tracked, whether they be spacecraft, human explorers, robots, surface vehicles, or science instrumentation. The Navigation Team within the NASA Space Communications Architecture Working Group (SCAWG) has addressed several key technical issues in this area and the principle findings are reported here. For navigation in the vicinity of the Moon, a variety of satellite constellations have been investigated that provide global or regional surface position determination and timely services analogous to those offered by GPS at Earth. In the vicinity of Mars, there are options for satellite constellations not available at the Moon due to the gravitational perturbations from Earth, such as two satellites in an aerostationary orbit. Alternate methods of radiometric navigation as considered, including one- and two-way signals, as well as autonomous navigation. The use of a software radio capable of receiving all available signal sources, such as GPS, pseudolites, and communication channels, is discussed. Methods of time transfer and dissemination are also considered in this paper.

Nelson, R. A.↗
NASA NTRSDate not supplied

Plans for NASA Contributions to Position, Navigation, and Timing at the Moon

Dating back to the Apollo missions, navigation in cislunar space has traditionally been performed with radiometric tracking and orbit estimation in Earth-based systems. The selected landing zones for Apollo enabled direct to Earth line of sight. Up to the present day, lunar orbiting science missions continue to rely on Earth sensors and processing. The upcoming Artemis and science missions seek different objectives, including landing and traversing in lunar locations occulted from view by Earth. Sustaining a burgeoning and diverse lunar mission set requires in-situ navigation capabilities that do not rely exclusively on Earth-based tracking and provide accurate and timely position, navigation, and timing (PNT) knowledge defined in a lunar reference system. These missions prefer a seamless transition from Earth-centric to lunar-centric PNT systems to reduce complexity and size, weight, and power (SWaP) on their missions. NASA’s heritage in successful high-altitude Global Navigation Satellite System (GNSS) reception is informing an expanded Space Service Volume to the moon and the development of lower SWaP GNSS receivers for the lunar missions. To overcome the geometric restrictions from GNSS –from both limited Dilution of Precision at the moon and lunar occultation – NASA is pursuing PNT services from the Lunar Communications Relay and Navigation System (LCRNS) as part of the interoperable LunaNet architecture to provide lunar-centric navigation services. For situations that require additional sensors, e.g. hazard detection, NASA’s optical navigation algorithms and close-range topographic sensors combine with observables from LunaNet in autonomous navigation software that brings robustness to the PNT solution. This presentation will provide an overview of NASA’s LCRNS PNT services, high-altitude GNSS and close-range sensors, processing algorithms and performance analysis, as well as efforts underway to define the underpinning Lunar Reference System.

Cheryl J. Gramling↗