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NASA NTRS2025

Temperature Variation Analysis of the STIM300 Inertial Measurement Unit

A key navigation instrument found on most autonomous and semi-autonomous platforms is the inertial measurement unit (IMU). This type of sensor is a combination of microelectromechanical systems (MEMS) that provide inertial information to the navigation system. Typical MEMS hardware include a gyroscope and an accelerometer (for rates and accelerations, respectively) within a single platform. The Near Earth Asteroid (NEA) Scout mission, slated to launch in October of 2018 (Author’s note: NEA Scout ultimately launch on November 16, 2022), carries an on-board IMU from Sensonor. This particular model has yet to see spaceflight, and questions about its on-orbit reliability remain. Dynamic tests were produced in the summer of 2016 by a visiting faculty member from Arkansas Tech University, Daniel Bullock. During these experiments, concerns about the noise characteristics of the sensor were raised, specifically relating to how temperature fluctuations affected the unit. It was found that the IMU took an extended period of time before reaching an internal steady state temperature. These tests often displayed large temperature variations, making the calculation of noise characteristics, such as bias drift, difficult to attribute entirely to noise. Static and dynamic tests were re-performed under more stringent constraints on temperature. Tests reported herein conclude that the IMU is adequately capable of providing inertial information for the NEA Scout mission.

Ivan Rodrigues Bertaska↗

NASA NTRS2010

Dynamic Optimization of Multi-Spacecraft Relative Navigation Configurations in the Earth-Moon System

In this paper, the notion of relative navigation introduced by Hill, Lo and Born is analyzed for a large class of periodic orbits in the Earth-Moon three-body problem, due to its potential in supporting Moon exploration efforts. In particular, a navigation metric is introduced and used as a cost function to optimize over a class of periodic orbits. While the problem could be solve locally as an optimal control problem, a dynamical based approach that allows for a global/systematic view of the problem is proposed. First, the simpler problem of multiple spacecraft placement on a given periodic orbit is solved before the notion of continuation and bifurcation analysis is used to expand the range of solutions thus obtained.

Three Body Problem↗

NASA NTRS2018

Sextant X-Ray Pulsar Navigation Demonstration: Initial On-Orbit Results

The Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) is a technology demonstration enhancement to the Neutron-star Interior Composition Explorer (NICER) mission. SEXTANT will be a first demonstration of in-space, autonomous, X-ray pulsar navigation (XNAV). Navigating using millisecond X-ray pulsars which could provide a GPS-like navigation capability available throughout our Solar System and beyond. NICER is a NASA Astrophysics Explorer Mission of Opportunity to the International Space Station that was launched and installed in June of 2017. During NICER's nominal 18-month base mission, SEXTANT will perform a number of experiments to demonstrate XNAV and advance the technology on a number of fronts. In this work, we review the SEXTANT, its goals, and present early results from SEXTANT experiments conducted in the first six months of operation. With these results, SEXTANT has made significant progress toward meeting its primary and secondary mission goals. We also describe the SEXTANT flight operations, calibration activities, and initial results.

Navigatio↗

NASA NTRS1989

Building an environment model using depth information

Modeling the environment is one of the most crucial issues for the development and research of autonomous robot and tele-perception. Though the physical robot operates (navigates and performs various tasks) in the real world, any type of reasoning, such as situation assessment, planning or reasoning about action, is performed based on information in its internal world. Hence, the robot's intentional actions are inherently constrained by the models it has. These models may serve as interfaces between sensing modules and reasoning modules, or in the case of telerobots serve as interface between the human operator and the distant robot. A robot operating in a known restricted environment may have a priori knowledge of its whole possible work domain, which will be assimilated in its World Model. As the information in the World Model is relatively fixed, an Environment Model must be introduced to cope with the changes in the environment and to allow exploring entirely new domains. Introduced here is an algorithm that uses dense range data collected at various positions in the environment to refine and update or generate a 3-D volumetric model of an environment. The model, which is intended for autonomous robot navigation and tele-perception, consists of cubic voxels with the possible attributes: Void, Full, and Unknown. Experimental results from simulations of range data in synthetic environments are given. The quality of the results show great promise for dealing with noisy input data. The performance measures for the algorithm are defined, and quantitative results for noisy data and positional uncertainty are presented.

Roth-Tabak, Y.↗

NASA NTRS2018

SEXTANT X-Ray Pulsar Navigation Demonstration: Additional On-Orbit Results

The Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) is a technology demonstration enhancement to the Neutron-star Interior Composition Explorer (NICER) mission, a NASA Astrophysics Explorer Mission of Opportunity to the International Space Station, launched in June of 2017. In late 2017, SEXTANT successfully completed a first demonstration of in-space and autonomous X-ray pulsar navigation (XNAV). This form of navigation relies on processing faint signals from millisecond pulsars-rapidly rotating neutron stars that appear to pulsate in the X-ray band-and could potentially provide a GPS-like navigation capability applicable throughout the solar-system and beyond. In this work, we briefly review prior SEXTANT results and then present new results focusing on: making use of the high- flux but rotationally unstable Crab pulsar, and using XNAV to estimate position, velocity, and time in the presence of an imperfect local clock.

Navigation↗

NASA NTRS2015

Raven: An On-Orbit Relative Navigation Demonstration Using International Space Station Visiting Vehicles

Since the last Hubble Servicing Mission five years ago, the Satellite Servicing Capabilities Office (SSCO) at the NASA Goddard Space Flight Center (GSFC) has been focusing on maturing the technologies necessary to robotically service orbiting legacy assets-spacecraft not necessarily designed for in-flight service. Raven, SSCO's next orbital experiment to the International Space Station (ISS), is a real-time autonomous non-cooperative relative navigation system that will mature the estimation algorithms required for rendezvous and proximity operations for a satellite-servicing mission. Raven will fly as a hosted payload as part of the Space Test Program's STP-H5 mission, which will be mounted on an external ExPRESS Logistics Carrier (ELC) and will image the many visiting vehicles arriving and departing from the ISS as targets for observation. Raven will host multiple sensors: a visible camera with a variable field of view lens, a long-wave infrared camera, and a short-wave flash lidar. This sensor suite can be pointed via a two-axis gimbal to provide a wide field of regard to track the visiting vehicles as they make their approach. Various real-time vision processing algorithms will produce range, bearing, and six degree of freedom pose measurements that will be processed in a relative navigation filter to produce an optimal relative state estimate. In this overview paper, we will cover top-level requirements, experimental concept of operations, system design, and the status of Raven integration and test activities.

Rendezvous↗

NASA NTRSDate not supplied

Tall Lunar Towers: Systems Analysis of a Lunar-Surface-Assembled Power, Communication, and Navigation Infrastructure

The National Aeronautics and Space Administration (NASA) intends to develop and maintain a human-lunar presence, requiring infrastructure on the Lunar South Pole. To keep pace with the continued growth in cislunar activity, there is national interest in developing a global lunar infrastructure network for power and Communication, Position, Navigation, and Timing (CPNT). Demonstrating autonomous construction capabilities is an infrastructure-enabling objective. This study explores several architecture trade studies to assess the feasibility of alternative lunar infrastructure concepts. 50 m towers, for instance, enable solar power generation up to 99% of a lunar year in addition to acting as wide-range communication and navigation surface relays. The infrastructure network considered in this study consisted of tower platforms, utilities hosted on the towers, and both crewed and robotic end users. High-level trades were analyzed, such as tower height, location, and distributed vs centralized power grids. Results indicated that even with minimal permanent surface assets (darkness survival power loads on the order of 5 kW or greater), at any of the five locations considered, taller towers resulted in lower infrastructure mass than shorter towers; up to 24% system mass savings were realized by reducing battery mass. Simultaneously, taller towers increased the range of communication coverage; a 50 m tower on the Connecting Ridge had 5 kg more structure and 76% more line-of-sight coverage to a two-meter-tall end user than a 10 m tower with the same location and user height. Leveraging a grid of tall towers for nominal power and communication would not only save up to 2,800 kg in battery mass but would be more maintainable and allow users to take advantage of generational upgrades.

lunar infrastructure↗

NASA NTRS2008

Overview of Terrain Relative Navigation Approaches for Precise Lunar Landing

The driving precision landing requirement for the Autonomous Landing and Hazard Avoidance Technology project is to autonomously land within 100m of a predetermined location on the lunar surface. Traditional lunar landing approaches based on inertial sensing do not have the navigational precision to meet this requirement. The purpose of Terrain Relative Navigation (TRN) is to augment inertial navigation by providing position or bearing measurements relative to known surface landmarks. From these measurements, the navigational precision can be reduced to a level that meets the 100m requirement. There are three different TRN functions: global position estimation, local position estimation and velocity estimation. These functions can be achieved with active range sensing or passive imaging. This paper gives a survey of many TRN approaches and then presents some high fidelity simulation results for contour matching and area correlation approaches to TRN using active sensors. Since TRN requires an a-priori reference map, the paper concludes by describing past and future lunar imaging and digital elevation map data sets available for this purpose.

Terrain Relative Navigation (TRN)↗

NASA NTRS2017

Open-Loop Flight Testing of COBALT GN&C Technologies for Precise Soft Landing

A terrestrial, open-loop (OL) flight test campaign of the NASA COBALT (CoOperative Blending of Autonomous Landing Technologies) platform was conducted onboard the Masten Xodiac suborbital rocket testbed, with support through the NASA Advanced Exploration Systems (AES), Game Changing Development (GCD), and Flight Opportunities (FO) Programs. The COBALT platform integrates NASA Guidance, Navigation and Control (GN&C) sensing technologies for autonomous, precise soft landing, including the Navigation Doppler Lidar (NDL) velocity and range sensor and the Lander Vision System (LVS) Terrain Relative Navigation (TRN) system. A specialized navigation filter running onboard COBALT fuzes the NDL and LVS data in real time to produce a precise navigation solution that is independent of the Global Positioning System (GPS) and suitable for future, autonomous planetary landing systems. The OL campaign tested COBALT as a passive payload, with COBALT data collection and filter execution, but with the Xodiac vehicle Guidance and Control (G&C) loops closed on a Masten GPS-based navigation solution. The OL test was performed as a risk reduction activity in preparation for an upcoming 2017 closed-loop (CL) flight campaign in which Xodiac G&C will act on the COBALT navigation solution and the GPS-based navigation will serve only as a backup monitor.

Carson, John M., III↗

NASA NTRS2011

Intelligent Autonomy for Unmanned Surface and Underwater Vehicles

As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic systems to perform a high level of on-board decisionmaking, which would otherwise be performed by humanoperators. With more decision making capabilities, less a priori knowledge of the area of operations would be required, as these systems would be able to sense and adapt to changing environmental conditions, such as unknown topography, currents, obstructions, bays, harbors, islands, and river channels. Existing vehicle sensors would be dual-use; that is they would be utilized for the primary mission, which may be mapping or hydrographic reconnaissance; as well as for autonomous hazard avoidance, route planning, and bathymetric-based navigation. This paper describes a tightly integrated instantiation of an autonomous agent called CARACaS (Control Architecture for Robotic Agent Command and Sensing) developed at JPL (Jet Propulsion Laboratory) that was designed to address many of the issues for survivable ASV/AUV control and to provide adaptive mission capabilities. The results of some on-water tests with US Navy technology test platforms are also presented.

environmental sensing↗

NASA NTRS2001

Testing the Preliminary X-33 Navigation System

The X-33 Reusable Launch Vehicle (RLV) must meet the demanding requirements of landing autonomously on a narrow landing strip following a flight that reaches an altitude of up to 200,000 feet and a speed in excess of Mach 9 with significant in-flight energy bleed-off maneuvers. To execute this flight regimen a highly reliable avionics system has been designed that includes three LN-100G Inertial Navigation System/Global Positioning System (INS/GPS) units as the primary navigation system for the X-33. NASA's Marshall Space Flight Center (MSFC) tested an INS/GPS system in real-time simulations to determine the ability of this navigation suite to meet the in flight and autonomous landing requirements of the X-33 RLV. A total of sixty-one open loop tests were performed to characterize the navigation accuracy of the LN-100G. Twenty-seven closed-loop tests were also performed to evaluate the performance of the X-33 Guidance, Navigation and Control (GN&C) algorithms with the real navigation hardware. These closed-loop tests were also designed to expose any integration or operational issues with the real-time X-33 vehicle simulation. Dynamic road tests of the INS/GPS were conducted by Litton to assess the performance of differential and nondifferential INS/GPS hybrid navigation solutions. The results of the simulations and road testing demonstrate that this novel solution is capable of meeting the demanding requirements of take-off, in-flight navigation, and autonomous landing of the X-33 RLV. This paper describes the test environment developed to stimulate the LN-100G and discusses the results of this test effort. This paper also presents recommendations for a navigation system suitable to an operational RLV system.

Lomas, James J.↗

NASA NTRS2010

High Speed Lunar Navigation for Crewed and Remotely Piloted Vehicles

Increased navigation speed is desirable for lunar rovers, whether autonomous, crewed or remotely operated, but is hampered by the low gravity, high contrast lighting and rough terrain. We describe lidar based navigation system deployed on NASA's K10 autonomous rover and to increase the terrain hazard situational awareness of the Lunar Electric Rover crew.

Pedersen, L.↗

NASA NTRS2019

Airborne Radar for sUAS Sense and Avoid

A primary challenge for the safe integration of small UAS operations into the National Airspace System (NAS) is traffic deconfliction, both from manned and unmanned aircraft. The UAS Traffic Management (UTM) project being conducted at the National Aeronautics and Space Administration (NASA) considers a layered approach to separation provision, ranging from segregation of operations through airspace volumes (geofences) to autonomous sense and avoid (SAA) technologies for higher risk, densely occupied airspace. Cooperative SAA systems, such as Automatic Dependent Surveillance-Broadcast (ADS-B) and/or vehicle-to-vehicle communication systems provide significant additional risk mitigation but they fail to adequately mitigate collision risks for non-cooperative (non-transponder equipped) airborne aircraft. The RAAVIN (Radar on Autonomous Aircraft to Verify ICAROUS Navigation) flight test being conducted by NASA and the Mid-Atlantic Aviation Partnership (MAAP) was designed to investigate the applicability and performance of a prototype, commercially available sUAS radar to detect and track non-cooperative airborne traffic, both manned and unmanned. The radar selected for this research was a Frequency Modulated Continuous Wave (FMCW) radar with 120 degree azimuth and 80 degree elevation field of view operating at 24.55GHz center frequency with a 200 MHz bandwidth. The radar transmits 2 watts of power thru a Metamaterial Electronically Scanning Array antenna in horizontal polarization. When the radar is transmitting, personnel must be at least 1 meter away from the active array to limit nonionizing radiation exposure. The radar physical dimensions are 18.7cm by 12.1cm by 4.1cm and it weighs less than 820 grams making it well suited for installation on small UASs. The onboard, SAA capability, known as ICAROUS, (Independent Configurable Architecture for Reliable Operations of Unmanned Systems), developed by NASA to support sUAS operations, will provide autonomous guidance using the traffic radar tracks from the onboard radar. The RAAVIN set of studies will be conducted in three phases. The first phase included outdoor, ground-based radar evaluations performed at the Virginia Tech’s Kentland Farm testing range in Blacksburg, VA. The test was designed to measure how well the radar could detect and track a small UAS flying in the radar’s field of view. The radar was used to monitor 5 test flights consisting of outbound, inbound and crossing routes at different ranges and altitudes. The UAS flown during the ground test was the Inspire 2, a quad copter weighing less than 4250 grams (10 pounds) at maximum payload. The radar was set up to scan and track targets over its full azimuthal field of view from 0 to 40 degrees in elevation. The radar was configured to eliminate tracks generated from any targets located beyond 2000 meters from the radar and moving at velocities under 1.45 meters per second. For subsequent phases of the study the radar will be integrated with a sUAS platform to evaluate its performance in flight for SAA applications ranging from sUAS to manned GA aircraft detections and tracking. Preliminary data analysis from the first outdoor ground tests showed the radar performed well at tracking the vehicle as it flew outbound and repeatedly maintained a track out to 1000 meters (maximum 1387 meters) until the vehicle slowed to a stop to reverse direction to fly inbound. As the Inspire flew inbound tracks from beyond 800 meters, a reacquisition time delay was consistently observed between when the Inspire exceeds a speed of 1.45 meters per second and when the radar indicated an inbound target was present and maintained its track. The time delay varied between 6 seconds to over 37 seconds for the inbound flights examined, and typically resulted in about a 200 meter closure distance before the Inspire track was maintained. The radar performed well at both acquiring and tracking the vehicle as it flew crossing routes out past 400 meters across the azimuthal field of view. The radar and ICAROUS software will be integrated and flown on a BFD-1400-SE8-E UAS during the next phase of the RAAVIN project. The main goal at the conclusion of this effort is to determine if this radar technology can reliably support minimum requirements for SAA applications of sUAS. In particular, the study will measure the range of vehicle detections, lateral and vertical angular errors, false and missed/late detections, and estimated distance at closest point of approach after an avoidance maneuver is executed. This last metric is directly impacted by sensor performance and indicates its suitability for the task.

Szatkowski, George N.↗

NASA NTRS1986

Autonomous Orbital Calculation for Satellites

Onboard orbital navigation system reduces dependence on Earth-tosatellite links. Report discusses mathematics of proposed navigation subsystem that keeps geostationary satellite in proper orbit without ground control. Subsystem uses data from Earth and Sun sensors to activate thrusters for station-keeping maneuvers. With sensors already on satellites for determining attitude, subsystem maintains satellite within 3 degrees of specified equatorial longitude for up to 6 months. With more accurate sensors, subsystem able to maintain orbit within 0.1 degrees.

Mease, K. D.↗

NASA NTRS2009

Lunar Landing Trajectory Design for Onboard Hazard Detection and Avoidance

The Autonomous Landing and Hazard Avoidance Technology (ALHAT) Project is developing the software and hardware technology needed to support a safe and precise landing for the next generation of lunar missions. ALHAT provides this capability through terrain-relative navigation measurements to enhance global-scale precision, an onboard hazard detection system to select safe landing locations, and an Autonomous Guidance, Navigation, and Control (AGNC) capability to process these measurements and safely direct the vehicle to a landing location. This paper focuses on the key trajectory design issues relevant to providing an onboard Hazard Detection and Avoidance (HDA) capability for the lander. Hazard detection can be accomplished by the crew visually scanning the terrain through a window, a sensor system imaging the terrain, or some combination of both. For ALHAT, this hazard detection activity is provided by a sensor system, which either augments the crew s perception or entirely replaces the crew in the case of a robotic landing. Detecting hazards influences the trajectory design by requiring the proper perspective, range to the landing site, and sufficient time to view the terrain. Following this, the trajectory design must provide additional time to process this information and make a decision about where to safely land. During the final part of the HDA process, the trajectory design must provide sufficient margin to enable a hazard avoidance maneuver. In order to demonstrate the effects of these constraints on the landing trajectory, a tradespace of trajectory designs was created for the initial ALHAT Design Analysis Cycle (ALDAC-1) and each case evaluated with these HDA constraints active. The ALHAT analysis process, described in this paper, narrows down this tradespace and subsequently better defines the trajectory design needed to support onboard HDA. Future ALDACs will enhance this trajectory design by balancing these issues and others in an overall system design process.

Paschall, Steve↗

NASA NTRS1989

Planetary Rover local navigation and hazard avoidance

A Planetary Rover will have to be able to navigate through its local environment autonomously, due to communication delays. This implies that the vehicle must be able to sense its environment, plan a course through that environment, and react appropriately to unexpected situations as they appear. All this must be done while guiding the vehicle toward the goals that have been given to it from its operators on the earth. This paper describes research at the Jet Propulsion Laboratory which concentrates on the sensing, perception, planning and execution monitoring that must be carried out by the rover to ensure that a safe and efficient path is found by the rover, and that that path is performed correctly.

Miller, David P.↗

NASA NTRS1993

Compact Optical Correlator

Optical cross-correlator indicates position of target (if any) in scene matching target encoded in matched filter. Size reduced by use of prisms to fold optical path. Device designed, assembled from commercial components, and tested to verify feasibility of miniaturization for eventual incorporation into navigational and/or control systems of autonomous vehicles. For example, aircraft equipped with optical correlator recognizes prescribed target and measures its position, so that it lands on target under automatic control.

Scholl, Marija S.↗

NASA NTRS1992

Continuous motion using task-directed stereo vision

The performance of autonomous mobile robots performing complex navigation tasks can be dramatically improved by directing expensive sensing and planning in service of the task. The task-direction algorithms can be quite simple. In this paper we describe a simple task-directed vision system which has been implemented on a real outdoor robot which navigates using stereo vision. While the performance of this particular robot was improved by task-directed vision, the performance of task-directed vision in general is influenced in complex ways by many factors. We briefly discuss some of these, and present some initial simulated results.

Gat, Erann↗