Search NASA⌕ Search

SEARCH · Search NASA

Results for “Autonomous navigation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

NASA Small Spacecraft Technology (SST) Program - Recent and Upcoming Technology Demonstrations and Development Efforts

The Small Spacecraft Technology (SST) program within NASA’s Space Technology Mission Directorate, expands the ability to execute unique missions through rapid development and demonstration of capabilities for small spacecraft applicable to exploration, science and the commercial space sector. Through targeted development and frequent in space testing, the program: • Enables execution of missions at much lower cost than previously possible • Substantially reduces the time required for development of spacecraft • Enables new mission architectures through the use of small spacecraft • Expands the reach of small spacecraft to new destinations and challenging new environments • Enables the augmentation of existing assets and future missions with supporting small spacecraft. The program achieves its objectives through: • Identification and investment in the development of new subsystem technologies to enhance or expand the capabilities of small spacecraft • Sponsorship of flight demonstrations of new technologies, capabilities and applications for small spacecraft • Promotion of the use of small spacecraft as platforms for testing and demonstrating technologies and capabilities that might have more general applications in larger-scale spacecraft and systems Technologies funded by the program that are key to advancing the utility and capability of small spacecraft were demonstrated in 2022 and 2023. Notable on-orbit demonstrations include the following. • The Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment’s (CAPSTONE) navigation technology that was demonstrated for the first time in 2023 could provide autonomous onboard navigation information for future lunar missions, minimizing or eliminating human-in-the-loop mission operations. • The optical communications technology also demonstrated in 2023 by the TeraByte InfraRed Delivery (TBIRD) payload that launched on Pathfinder Technology Demonstrator-3, achieved 200 gigabit per second (Gbps) throughput on a space-to-ground optical link between a satellite in orbit and Earth, the highest data rate ever achieved by optical communications technology. • The precision laser pointing performance of NASA’s CubeSat Infrared CrossLink A (CLICK) spacecraft’s fine steering mirror control system was successfully demonstrated. This element of the laser communications system will be used to demonstrate two-way crosslink communication in low-Earth orbit by CLICK B/C anticipated to launch in late 2024. Investments in subsystem technology development through funding to university, industry, and other government partners in a number of areas will be discussed. Among others, topic areas include propulsion, autonomous swarm technology, edge computing, and thermal control. Additionally, the status of the CubeSat-alternative platform, DiskSat, strategies for accelerating the demonstration of technology payloads via the Realizing Rapid, Reduced-cost high-Risk Research (R5) project, and the status of recently completed and upcoming on-orbit demonstrations will also be presented.

Roger C Hunter↗
NASA NTRS2019

Navigation accuracy at Jupiter and Saturn using optical observations of planetary satellites

Autonomous on-board navigation has the potential to enable new types of missions and decrease reliance on NASA’s Deep Space Network for navigation purposes. Previous results have shown that navigating with only optical images of asteroids is feasible for inner planet cruise. In this study, we show that images of natural satellites can be used to navigate during approach and tour phases around the gas giants. We investigate the Jupiter and Saturn systems here, and specifically assess the performance of optical-only navigation for the Juno, Europa Clipper, and Cassini trajectories. Early approach phases and tours at Jupiter would require radiometric data to navigate, but the performance of optical-only data rivals the as-flown performance for Cassini at Saturn.

Broschart, Stephen B.↗
NASA NTRS2003

Navigation Concepts for the James Webb Space Telescope

This paper evaluates the performance that can be achieved using candidate ground and onboard navigation approaches for operation of the James Webb Space Telescope, which will be in an orbit about the Sun-Earth L2 libration point. The ground navigation approach processes standard range and Doppler measurements from the Deep Space Network The onboard navigation approach processes celestial object measurements and/or ground-to- spacecraft Doppler measurements to autonomously estimate the spacecraft s position and velocity and Doppler reference frequency. Particular attention is given to assessing the absolute position and velocity accuracy that can be achieved in the presence of the frequent spacecraft reorientations and momentum unloads planned for this mission. The ground navigation approach provides stable navigation solutions using a tracking schedule of one 30-minute contact per day. The onboard navigation approach that uses only optical quality celestial object measurements provides stable autonomous navigation solutions. This study indicates that unmodeled changes in the solar radiation pressure cross-sectional area and modeled momentum unload velocity changes are the major error sources. These errors can be mitigated by modeling these changes, by estimating corrections to compensate for the changes, or by including acceleration measurements.

Long, Anne↗
NASA NTRSDate not supplied

Collision Avoidance Approach Using Deep Reinforcement Learning

A method to enable autonomous robots moving in a 2D space collision free motivates the purposed approach for collision avoidance for autonomous UAM vehicles. Challenges of autonomous collision free navigation for both problems are similar. Agents in each environment do not know the intent, or goal, of the other. Finding the time efficient paths require some level of anticipation with neighboring agents which is computationally expensive. In the original work, these obstacles were overcome with a novel application of deep reinforcement learning which offloads the online computation to an offline learning algorithm. A value network that encodes the estimated time to the goal given the agent’s state and the observable portion of the other agent’s state is trained on a baseline policy and further refined with reinforcement learning to promote time efficient collision free navigation. Online, the value network efficiently informs the agent’s decision making in the face of uncertainty of the other agent’s next move. In this paper, challenges extending this methodology to the 3D environment of autonomous UAM vehicles with kinematic constraints are discussed and initial results shown.

Collision Avoidance↗
NASA NTRSDate not supplied

Collision Avoidance Approach Using Deep Reinforcement Learning

A method to enable autonomous robots moving in a 2D space collision free motivates the purposed approach for collision avoidance for autonomous UAM vehicles. Challenges of autonomous collision free navigation for both problems are similar. Agents in each environment do not know the intent, or goal, of the other. Finding the time efficient paths require some level of anticipation with neighboring agents which is computationally expensive. In the original work, these obstacles were overcome with a novel application of deep reinforcement learning which offloads the online computation to an offline learning algorithm. A value network that encodes the estimated time to the goal given the agent’s state and the observable portion of the other agent’s state is trained on a baseline policy and further refined with reinforcement learning to promote time efficient collision free navigation. Online, the value network efficiently informs the agent’s decision making in the face of uncertainty of the other agent’s next move. In this paper, challenges extending this methodology to the 3D environment of autonomous UAM vehicles with kinematic constraints are discussed and initial results shown.

Collision Avoidance↗
NASA NTRS1989

An onboard navigation system which fulfills Mars aerocapture guidance requirements

The development of a candidate autonomous onboard Mars approach navigation scheme capable of supporting aerocapture into Mars orbit is discussed. An aerocapture guidance and navigation system which can run independently of the preaerocapture navigation was used to define a preliminary set of accuracy requirements at entry interface. These requirements are used to evaluate the proposed preaerocapture navigation scheme. This scheme uses optical sightings on Deimos with a star tracker and an inertial measurement unit for instrumentation as a source for navigation nformation. Preliminary results suggest that the approach will adequately support aerocaputre into Mars orbit.

Brand, Timothy J.↗
NASA NTRS1989

Interaction dynamics of multiple mobile robots with simple navigation strategies

The global dynamic behavior of multiple interacting autonomous mobile robots with simple navigation strategies is studied. Here, the effective spatial domain of each robot is taken to be a closed ball about its mass center. It is assumed that each robot has a specified cone of visibility such that interaction with other robots takes place only when they enter its visibility cone. Based on a particle model for the robots, various simple homing and collision-avoidance navigation strategies are derived. Then, an analysis of the dynamical behavior of the interacting robots in unbounded spatial domains is made. The article concludes with the results of computer simulations studies of two or more interacting robots.

Wang, P. K. C.↗
NASA NTRS1991

Autonomous precision landing using terrain-following navigation

Terrain-following navigation studies that have been done over the past two years in the navigation system section at JPL are described. A descent to Mars scenario based on Mars Rover and Sample Return mission profiles is described, and navigation and image processing issues pertaining to descent phases where landmark picture can be obtained are examined. A covariance analysis is performed to verify that landmark measurements from a terrain-following navigation system can satisfy precision landing requirements. Image processing problems involving known landmarks in actual pictures are considered. Mission design alternatives that can alleviate some of these problems are suggested.

Vaughan, R. M.↗
NASA NTRS2024

Historical Retrospective on Orion GNC Design

On November 16, 2022, Artemis I successfully launched and began a nearly 26-day journey returning a human-rated spacecraft to the Moon for the first time in fifty years. The mission was a huge success and once again the world's attention was focused on the Moon. This paper will take a step back in time over the seventeen-plus years of design and development of the Orion Guidance Navigation and Control (GNC) system that carried the spacecraft 1.4 million miles around the Moon and landed safely back on earth off the coast of San Diego California. Key design decisions (good and not so good) and "first-ever" capabilities will be chronicled. This paper will explore such things as the most advanced on-board targeting system ever flown on a spacecraft, never-been-done-before autonomous planetary Optical Navigation, and the first-ever truly skip entry guided to the desired target within a few miles.

Guidance Navigation and Control↗
NASA NTRS2024

Historical Retrospective on Orion GNC Design

On November 16, 2022, Artemis I successfully launched and began a nearly 26-day journey returning a human-rated spacecraft to the Moon for the first time in fifty years. The mission was a huge success and once again the world's attention was focused on the Moon. This paper will take a step back in time over the seventeen-plus years of design and development of the Orion Guidance Navigation and Control (GNC) system that carried the spacecraft 1.4 million miles around the Moon and landed safely back on earth off the coast of San Diego California. Key design decisions (good and not so good) and "first-ever" capabilities will be chronicled. This paper will explore such things as the most advanced on-board targeting system ever flown on a spacecraft, never-been-done-before autonomous planetary Optical Navigation, and the first-ever truly skip entry guided to the desired target within a few miles.

Guidance Navigation and Control↗
NASA NTRS2013

Supporting Crewed Lunar Exploration with LiAISON Navigation

This paper examines the benefits of navigating a crewed vehicle between the Earth and the Moon using both ground tracking and satellite-to-satellite tracking. Linked Autonomous Interplanetary Satellite Orbit Navigation (LiAISON) is a new technique that has been shown to dramatically improve the navigation of lunar satellites, libration orbiters, and Earth orbiting satellites using scalar intersatellite observations. In this paper, LiAISON is applied to the problem of navigating a crewed vehicle to the Moon. It has been found that LiAISON observations improve the navigation accuracy enough to reduce the number of active ground tracking stations from six to three.

low-energy↗
DOE OSTI2024

A Vision–based Robust $\mathcal{H}$ ∞ Gain Scheduling Longitudinal and Lateral Following Controller for Autonomous Vehicles on Urban Curved Roads

Implementing advanced driver assistance systems (ADAS) in congested and intricate urban traffic scenarios poses significant challenges. To address the frequent stop–and–go motions exhibited by autonomous vehicles (AVs) navigating urban roads with changes in curvature, we propose a vision–based robust $\mathcal{H}$ ∞ adaptive cruise control system (ACC) for longitudinal control, plus a lane keeping assist system (LKAS) for lateral control. For the vision-based ACC, a weighted probability objective function for the vehicle following behavior is formulated. We incorporate $\mathcal{H}$ ∞ performance and gain scheduling techniques to mitigate the impact of uncertainty in visual sensor measurements. Furthermore, the optimal time headway is scheduled based on the velocity to ensure traffic flow efficiency and safety during the vehicle following process. For the LKAS, we introduce a road curvature estimation method that integrates lane and vehicle dynamics information to obtain the lateral and heading offsets. Next, the design criterion of the observer–based robust gain scheduling lateral motion controller is established by linear matrix inequality (LMI). Here, a series of experiments conducted within a camera–in–loop platform validate the proposed method.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1988

Automated low-thrust guidance for the orbital maneuvering vehicle

This paper describes the highly autonomous OMV Guidance Navigation and Control system. Emphasis is placed on a key feature of the design, the low thrust guidance algorithm. The two guidance modes, orbit change guidance and rendezvous guidance, are discussed in detail. It is shown how OMV will automatically transfer from its initial orbit to an arbitrary target orbit and reach a specified rendezvous position relative to the target vehicle.

Rose, Richard E.↗
NASA NTRS1991

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.

Yan, Jerry C.↗
NASA NTRS1991

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 1990s cannot enjoy an increased level of autonomy without the efficient implementation of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real-time demands are met for larger systems. Speedup via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial laboratories in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems is surveyed. The survey discusses multiprocessors for expert systems, parallel languages for symbolic computations, and mapping expert systems to multiprocessors. Results to date indicate that the parallelism achieved for these systems is small. The main reasons are (1) the body of knowledge applicable in any given situation and the amount of computation executed by each rule firing are small, (2) dividing the problem solving process into relatively independent partitions is difficult, and (3) implementation decisions that enable expert systems to be incrementally refined hamper compile-time optimization. In order to obtain greater speedups, data parallelism and application parallelism must be exploited.

Lau, Sonie↗
NASA NTRS1990

A positional estimation technique for an autonomous land vehicle in an unstructured environment

This paper presents a solution to the positional estimation problem of an autonomous land vehicle navigating in an unstructured mountainous terrain. A Digital Elevation Map (DEM) of the area in which the robot is to navigate is assumed to be given. It is also assumed that the robot is equipped with a camera that can be panned and tilted, and a device to measure the elevation of the robot above the ground surface. No recognizable landmarks are assumed to be present in the environment in which the robot is to navigate. The solution presented makes use of the DEM information, and structures the problem as a heuristic search in the DEM for the possible robot location. The shape and position of the horizon line in the image plane and the known camera geometry of the perspective projection are used as parameters to search the DEM. Various heuristics drawn from the geometric constraints are used to prune the search space significantly. The algorithm is made robust to errors in the imaging process by accounting for the worst care errors. The approach is tested using DEM data of areas in Colorado and Texas. The method is suitable for use in outdoor mobile robots and planetary rovers.

Talluri, Raj↗
NASA NTRS2000

The New Millenium Program: Serving Earth and Space Sciences

NASA has exciting plans for space science and Earth observations during the next decade. A broad range of advanced spacecraft and measurement technologies will be needed to support these plans within the existing budget and schedule constraints. Many of these technology needs are common to both NASA's Office of Earth Science (OES) and Office of Space Sciences (OSS). Even though some breakthrough technologies have been identified to address these needs, project managers have traditionally been reluctant to incorporate them into flight programs because their inherent development risk. To accelerate the infusion of new technologies into its OES and OSS missions, NASA established the New Millennium Program (NMP). This program analyzes the capability needs of these enterprises, identifies candidate technologies to address these needs, incorporates advanced technology suites into validation flights, validates them in the relevant space environment, and then proactively infuses the validated technologies into future missions to enhance their capabilities while reducing their life cycle cost. The NMP employs a cross-enterprise Science Working Group, the NASA Enterprise science and technology roadmaps to define the capabilities needed by future Earth and Space science missions. Additional input from the science community is gathered through open workshops and peer-reviewed NASA Research Announcement (NRAs) for advanced measurement concepts. Technology development inputs from the technology organizations within NASA, other government agencies, federally funded research and development centers (FFRDC's), U.S. industry, and academia are sought to identify breakthrough technologies that might address these needs. This approach significantly extends NASA's technology infrastructure. To complement other flight test programs that develop or validate of individual components, the NMP places its highest priority on system-level validations of technology suites in the relevant space environment. This approach is not needed for all technologies, but it is usually essential to validate advanced system architectures or new measurement concepts. The NMP has recently revised its processes for defining candidate validation flights, and selecting technologies for these flights. The NMP now employs integrated project formulation teams, 'Which include scientists, technologists, and mission planners, to incorporate technology suites into candidate validation flights. These teams develop competing concepts, which can be rigorously evaluated prior to selection for flight. The technology providers for each concept are selected through an open, competitive, process during the project formulation phase. If their concept is selected for flight, they are incorporated into the Project Implementation Team, which develops, integrates, tests, launches, and operates the technology validation flight. Throughout the project implementation phase, the Implementation Team will document and disseminate their validation results to facilitate the infusion of their validated technologies into future OSS and OES science missions. The NMP has successfully launched its first two Deep Space flights for the OSS, and is currently implementing its first two Earth Orbiting flights for the OES. The next OSS and OES flights are currently being defined. Even though these flights are focused on specific Space Science and Earth Science themes, they are designed to validate a range of technologies that could benefit both enterprises, including advanced propulsion, communications, autonomous operations and navigation, multifunctional structures, microelectronics, and advanced instruments. Specific examples of these technologies will be provided in our presentation. The processes developed by the NMP also provide benefits across the Space and Earth Science enterprises. In particular, the extensive, nation-wide technology infrastructure developed by the NMP enhances the access to breakthrough technologies for both enterprises.

Li, Fuk K.↗