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NASA NTRS2017

GPS/Optical/Inertial Integration for 3D Navigation Using Multi-Copter Platforms

In concert with the continued advancement of a UAS traffic management system (UTM), the proposed uses of autonomous unmanned aerial systems (UAS) have become more prevalent in both the public and private sectors. To facilitate this anticipated growth, a reliable three-dimensional (3D) positioning, navigation, and mapping (PNM) capability will be required to enable operation of these platforms in challenging environments where global navigation satellite systems (GNSS) may not be available continuously. Especially, when the platform's mission requires maneuvering through different and difficult environments like outdoor opensky, outdoor under foliage, outdoor-urban and indoor, and may include transitions between these environments. There may not be a single method to solve the PNM problem for all environments. The research presented in this paper is a subset of a broader research effort, described in [1]. The research is focused on combining data from dissimilar sensor technologies to create an integrated navigation and mapping method that can enable reliable operation in both an outdoor and structured indoor environment. The integrated navigation and mapping design is utilizes a Global Positioning System (GPS) receiver, an Inertial Measurement Unit (IMU), a monocular digital camera, and three short to medium range laser scanners. This paper describes specifically the techniques necessary to effectively integrate the monocular camera data within the established mechanization. To evaluate the developed algorithms a hexacopter was built, equipped with the discussed sensors, and both hand-carried and flown through representative environments. This paper highlights the effect that the monocular camera has on the aforementioned sensor integration scheme's reliability, accuracy and availability.

Dill, Evan T.↗

NASA NTRS1987

An approach to conducting observations of non-trackable objects utilizing the Spartan spacecraft

The approach taken in the design of the guidance and navigation system for a 48-hour observation of Halley's Comet near perihelion passage, utilizing the SPARTAN 200 series carrier, is discussed. Autonomous vehicle navigation techniques that utilized solar sensors, a single star tracker, a 3-axis gyro package, and two independent cooperative microprocessors are described. While the Spartan-Halley spacecraft was destroyed during the Space Shuttle Challenger explosion, it is believed that the present approach has considerable potential for application to future missions that require autonomous control to perform scientific observations of nontrackable moving targets.

Watzin, James G.↗

NASA NTRS1974

Space transportation system as seen by an astronaut

Discussion of the astronaut's role in the Space Shuttle and its associated payload operations. It is shown that there will be a shift in the astronaut's tasks as the Shuttle system matures. The Shuttle is designed for automatic guidance, navigation, and control, and the need for active piloting will accordingly decrease. With the shift to onboard autonomous operation, the system management role will expand. Direct tasks with delivery/recovery and laboratory/observatory payloads will continue to expand throughout the Shuttle program duration through the 1980s.

Haise, F. W., Jr.↗

NASA NTRS1992

Inertial navigation sensor integrated motion analysis for autonomous vehicle navigation

Recent work on INS integrated motion analysis is described. Results were obtained with a maximally passive system of obstacle detection (OD) for ground-based vehicles and rotorcraft. The OD approach involves motion analysis of imagery acquired by a passive sensor in the course of vehicle travel to generate range measurements to world points within the sensor FOV. INS data and scene analysis results are used to enhance interest point selection, the matching of the interest points, and the subsequent motion-based computations, tracking, and OD. The most important lesson learned from the research described here is that the incorporation of inertial data into the motion analysis program greatly improves the analysis and makes the process more robust.

Roberts, Barry↗

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

Guidance Navigation and Control↗

NASA NTRS1990

Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

Rodriguez, Guillermo↗

NASA NTRS1985

Computers in Aerospace Conference, 5th, Long Beach, CA, October 21-23, 1985, Technical Papers

Among the topics discussed are: access control models for a distributed CAIS-conforming system; a knowledge-based advisory system for casualty procedures; and automated interactive simulation modeling system. Consideration is also given to: reusable software concepts and software development methodologies; the electronic device aspects of neutral network memories; an expert system for automated satellite anomaly resolution; and the use of automatic programming techniques for fault-tolerant computing systems. Among additional topics discussed are: systems approaches to software fault tolerance; a Space Shuttle navigation validation system; and a vision-based road following system for an autonomous land vehicle.

Source record↗

NASA NTRS1992

Automatic rule generation for high-level vision

Many high-level vision systems use rule-based approaches to solving problems such as autonomous navigation and image understanding. The rules are usually elaborated by experts. However, this procedure may be rather tedious. In this paper, we propose a method to generate such rules automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.

Rhee, Frank Chung-Hoon↗

NASA NTRS2012

Water Detection Based on Color Variation

This software has been designed to detect water bodies that are out in the open on cross-country terrain at close range (out to 30 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). This detector exploits the fact that the color variation across water bodies is generally larger and more uniform than that of other naturally occurring types of terrain, such as soil and vegetation. Non-traversable water bodies, such as large puddles, ponds, and lakes, are detected based on color variation, image intensity variance, image intensity gradient, size, and shape. At ranges beyond 20 meters, water bodies out in the open can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. But at closer range, the color coming out of a water body dominates sky reflections, and the water cue from sky reflections is of marginal use. Since there may be times during UGV autonomous navigation when a water body does not come into a perception system s field of view until it is at close range, the ability to detect water bodies at close range is critical. Factors that influence the perceived color of a water body at close range are the amount and type of sediment in the water, the water s depth, and the angle of incidence to the water body. Developing a single model of the mixture ratio of light reflected off the water surface (to the camera) to light coming out of the water body (to the camera) for all water bodies would be fairly difficult. Instead, this software detects close water bodies based on local terrain features and the natural, uniform change in color that occurs across the surface from the leading edge to the trailing edge.

Rankin, Arturo L.↗

NASA NTRSDate not supplied

Low SWaP Onboard Satellite Navigation, Guidance, and Control Technology

Onboard autonomy is a necessity for responsive space operations. Autonomous navigation, guidance, and control (NGC) enables space missions to reduce their dependence on high demand ground assets and costly ground personnel. It also allows for in-situ decision making and higher return on mission data. A flight software and hardware system providing this capability, called “autoNGC,” is currently being developed at NASA Goddard Space Flight Center for infusion into multiple future missions. The first build of autoNGC, providing autonomous navigation for lunar orbiting spacecraft, is targeted for completion by Fall 2024. It provides sensor fusion of multiple measurement types including pseudo-range from a weak signal Global Navigation Satellite Service (GNSS) receiver, 1-way and 2-way direct to Earth (DTE) range and Doppler, bearing and range from optical camera sensed images, and an accelerometer. AutoNGC is also being targeted for future missions that involve small body proximity operations, Sun Earth Libration point orbits, and distributed systems missions (DSMs) including those at outer planets. AutoNGC flight software is being built upon the plug-and-play architecture of the core Flight System (cFS) [Ref. 1]. Figure (Slide 7) shows the message-based software bus layout of various software applications (“apps”) consisting of the standard cFS apps and autoNGC interface apps and libraries. Accurate onboard navigation and timing is obtained through the Goddard Enhanced Onboard Navigation System (GEONS) software library [Ref. 2], which fuses different measurement types through an extended Kalman filter (EKF) framework. Optical measurements that are ingested in GEONS are provided by the cFS Goddard Image Analysis and Navigation Tool (cGIANT) app [Ref. 3]. This app processes optical images to extract the bearing angles of the centroid of the imaged body (near or far), the range to the imaged body, and/or of the features on the surface of a body to perform terrain relative navigation (TRN). Measurement of range to the body’s center of mass can also be derived from the detection of the limb. The first build of autoNGC for a lunar orbiting spacecraft is a minimal size, weight, and power (SWaP) hardware design allowing for inclusion into CubeSats and SmallSat-size class buses. Advancements in miniaturized space processors, such as the SpaceCube 3.0 Mini and the SpaceCube Mini-Z [Ref. 4] are utilized for low SWaP while maintaining a high level of performance. Figure (Slide 11) shows the composition of the first autoNGC build. The current enclosure design has dimensions 12 cm x 17 cm x 13.5 cm. The box mass is expected to be less than 2 kg, and the nominal power is 21 W. The hardware interfaces are designed for flexibility with a variety of sensor inputs. The achievable navigation performance depends on the sensors utilized, including the onboard clock for 1-way pseudo-range measurements. Analysis using a configuration that consists of weak signal GPS, TRN, and 1-way DTE has shown position and velocity accuracies of 10 meters and 2 cm/s (3-σ ) RSS, respectively, with onboard time knowledge estimated to better than 13 ns (3-σ ), for a spacecraft in a representative 12-hour eccentric lunar orbit. Other measurement types such as x-rays from known pulsars (called XNAV) and cross-links can also be processed in GEONS. With the plug-and-play architecture of autoNGC, cFS apps can easily be added and replaced, even after launch. Goddard is actively seeking partners to collaborate in the development of additional capabilities for autoNGC, including industry, academia, and others across the US Government. Plans are being formulated to make the autoNGC software platform available for use by any US government organization to leverage the non-recurring engineering associated with the development of onboard autonomous NGC 3 capabilities. As advancements in space qualified sensors, microprocessors, and algorithms are made, the autoNGC platform provides a ready starting point for inclusion of these technologies.

C. J. Gramling↗

NASA NTRS1998

Relative navigation for spacecraft formation flying

The Goddard Space Flight Center Guidance, Navigation, and Control Center (GNCC) is currently developing and implementing advanced satellite systems to provide autonomous control of formation flyers. The initial formation maintenance capability will be flight-demonstrated on the Earth-Orbiter-1 (EO-1) satellite, which is planned under the National Aeronautics and Space Administration New Millennium Program to be a coflight with the Landsat-7 (L-7) satellite. Formation flying imposes relative navigation accuracy requirements in addition to the orbit accuracy requirements for the individual satellites. In the case of EO-1 and L-7, the two satellites are in nearly coplanar orbits, with a small difference in the longitude of the ascending node to compensate for the Earth's rotation. The GNCC has performed trajectory error analysis for the relative navigation of the EO-1/L-7 formation, as well as for a more advanced tracking configuration using cross-link satellite communications. This paper discusses the orbit determination and prediction accuracy achievable for EO-1 and L-7 under various tracking and orbit determination scenarios and discusses the expected relative separation errors in their formation flying configuration.

Hartman, Kate R.↗

NASA NTRS1998

Relative Navigation for Spacecraft Formation Flying

The Goddard Space Flight Center Guidance, Navigation, and Control Center (GNCC) is currently developing and implementing advanced satellite systems to provide autonomous control of formation flyers. The initial formation maintenance capability will be flight-demonstrated on the Earth-Orbiter-1 (EO-l) satellite, which is planned under the National Aeronautics and Space Administration New Millennium Program to be a coflight with the Landsat-7 (L-7) satellite. Formation flying imposes relative navigation accuracy requirements in addition to the orbit accuracy requirements for the individual satellites. In the case of EO-1 and L-7, the two satellites are in nearly coplanar orbits, with a small difference in the longitude of the ascending node to compensate for the Earth's rotation. The GNCC has performed trajectory error analysis for the relative navigation of the EO-1/L-7 formation, as well as for a more advanced tracking configuration using cross- link satellite communications. This paper discusses the orbit determination and prediction accuracy achievable for EO-1 and L-7 under various tracking and orbit determination scenarios and discusses the expected relative separation errors in their formation flying configuration.

Hartman, Kate R.↗

NASA NTRS2019

Lunar Navigation Beacon Network Using Global Navigation Satellite System Receivers

With the increasing traffic in the lunar regime as part of NASA efforts to return humans to the moon. In order to support these missions, new capabilities are needed to support autonomous navigation and inter-asset communication. Additionally, with maturation and flight demonstration of increasingly capable small satellites, there is an opportunity to embed technology into a small spacecraft as part of companion missions. This paper addresses one such architecture, taking advantage of a lunar lander vehicle to host a companion spacecraft to build out lunar navigation and communication capability. The backbone of this spacecraft is the Navigator GPS receiver. This hardware has continually broken records on high altitude GPS coverage and has the potential to support autonomous navigation at lunar distances. This research proposes a large cubesat built around this technology and catching a ride to the moon via a lander mission. The concept of operations includes the spacecraft deploying prior to the lunar sphere of influence and maneuvering to enter into a lunar orbit. With the Navigator receiver, this spacecraft is capable of a large amount of autonomy, with a limited need for ground-based orbit determination. This spacecraft will fly alongside the lander, acting as a navigation reference during cruise, descent, and post-landing for mission validation. To assess this mission scenario, three aspects are covered in detail herein: the feasibility and mission requirements for entering into a lunar orbit given deployment along a lander surface-bound trajectory, the performance capability of the receiver along this transfer trajectory and in lunar orbit, and the ability to support navigation of the lander itself. These three areas are discussed in detail, providing results that support feasibility of the mission and determination of initial requirements.

Anzalone, Evan J.↗

NASA NTRS2015

Advanced Bayesian Method for Planetary Surface Navigation

Autonomous Exploration, Inc., has developed an advanced Bayesian statistical inference method that leverages current computing technology to produce a highly accurate surface navigation system. The method combines dense stereo vision and high-speed optical flow to implement visual odometry (VO) to track faster rover movements. The Bayesian VO technique improves performance by using all image information rather than corner features only. The method determines what can be learned from each image pixel and weighs the information accordingly. This capability improves performance in shadowed areas that yield only low-contrast images. The error characteristics of the visual processing are complementary to those of a low-cost inertial measurement unit (IMU), so the combination of the two capabilities provides highly accurate navigation. The method increases NASA mission productivity by enabling faster rover speed and accuracy. On Earth, the technology will permit operation of robots and autonomous vehicles in areas where the Global Positioning System (GPS) is degraded or unavailable.

Center, Julian↗

NASA NTRS2006

Autonomous Navigation Error Propagation Assessment for Lunar Surface Mobility Applications

The NASA Vision for Space Exploration is focused on the return of astronauts to the Moon. While navigation systems have already been proven in the Apollo missions to the moon, the current exploration campaign will involve more extensive and extended missions requiring new concepts for lunar navigation. In this document, the results of an autonomous navigation error propagation assessment are provided. The analysis is intended to be the baseline error propagation analysis for which Earth-based and Lunar-based radiometric data are added to compare these different architecture schemes, and quantify the benefits of an integrated approach, in how they can handle lunar surface mobility applications when near the Lunar South pole or on the Lunar Farside.

Welch, Bryan W.↗

NASA NTRS1978

The role of autonomous satellite navigation in the NEEDS program

A number of applications of autonomous satellite navigation are discussed. They include the onboard annotation of all experimental data and the onboard correction of imaging data. The accuracy levels required for each function are presented. Two alternative techniques for achieving autonomous satellite navigation are considered. One technique utilizes data from the Global Positioning System (GPS). The other approach utilizes data from a geosynchronous relay satellite system such as the Tracking and Data Relay Satellite System (TDRSS). The TDRSS approach makes use of one-way range and Doppler data along with a time transfer mechanism. Comparative accuracy levels for the onboard determination of position, velocity, and time based upon the GPS and TDRSS approaches are presented.

Fuchs, A. J.↗

NASA NTRS1987

Reasoning and planning in dynamic domains: An experiment with a mobile robot

Progress made toward having an autonomous mobile robot reason and plan complex tasks in real-world environments is described. To cope with the dynamic and uncertain nature of the world, researchers use a highly reactive system to which is attributed attitudes of belief, desire, and intention. Because these attitudes are explicitly represented, they can be manipulated and reasoned about, resulting in complex goal-directed and reflective behaviors. Unlike most planning systems, the plans or intentions formed by the system need only be partly elaborated before it decides to act. This allows the system to avoid overly strong expectations about the environment, overly constrained plans of action, and other forms of over-commitment common to previous planners. In addition, the system is continuously reactive and has the ability to change its goals and intentions as situations warrant. Thus, while the system architecture allows for reasoning about means and ends in much the same way as traditional planners, it also posseses the reactivity required for survival in complex real-world domains. The system was tested using SRI's autonomous robot (Flakey) in a scenario involving navigation and the performance of an emergency task in a space station scenario.

Georgeff, M. P.↗