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At least 289 records · Page 16

Transitioning Autonomous Systems Technology Research to a Flight Software Environment

NASA has developed methods and algorithms for autonomous spacecraft operations,including automated planning and scheduling, fault diagnostics and impact determination,procedure management and display. Making the transition from technology research tooperational flight software requires overcoming significant technical, programmatic andcultural challenges. Technology research is aimed at developing methods that performspecific functions correctly, but the resulting software may not be designed for flightprocessors with limited CPU, memory and network resources, and may not be easilyintegrated into spacecraft flight software. Our objective in the Autonomous Systems andOperations Project is to make significant strides toward the transformation from technologyto operational use. Our focus was twofold: maturing research grade autonomy software intoa flight software environment using broadly accepted languages and tools; and integratingautonomy applications with each other and with representative systems and their data andcommand interfaces. For a target flight software environment, we chose Core FlightSoftware, developed by Goddard Space Flight Center as a common operating systemindependent framework. Our hardware integration environment was provided by theIntegrated Power and Avionics Systems (iPAS) Lab at Johnson Space Center, in whichvarious subsystem development has been conducted to address engineering challenges forthe vehicles and systems required for long-duration missions into the solar system. The iPASand its network of connected facilities provides realistic subsystem hardware or simulationsof spacecraft power, life support, guidance, navigation and control, and command and datahandling subsystems. Interfaces between autonomy applications and the subsystems beingassessed and controlled were developed, assessed and refined. The hardware and softwareenvironment using CFS and the iPAS facility has proven to be a highly flexible and realisticenvironment in which to rapidly integrate applications in an iterative, low cost setting. Usingthe integration environment we have developed, we will turn our focus to performance andsizing analysis to determine the computational requirements for full-scale deployment ofautonomy technology. Scalability of reasoners and the spacecraft models upon which theyoperate, and robustness across the full range of spacecraft conditions and environments willbe explored and improved. We are making significant contributions to the future programsthat will build the spacecraft that will take humans beyond the Earth-Moon system, in whichprogram Systems Engineers will be able to accurately and confidently design in accurate,robust and mature autonomous operations systems.

Flight Software↗

A Long Distance Laser Altimeter for Terrain Relative Navigation and Spacecraft Landing

A high precision laser altimeter was developed under the Autonomous Landing and Hazard Avoidance (ALHAT) project at NASA Langley Research Center. The laser altimeter provides slant-path range measurements from operational ranges exceeding 30 km that will be used to support surface-relative state estimation and navigation during planetary descent and precision landing. The altimeter uses an advanced time-of-arrival receiver, which produces multiple signal-return range measurements from tens of kilometers with 5 cm precision. The transmitter is eye-safe, simplifying operations and testing on earth. The prototype is fully autonomous, and able to withstand the thermal and mechanical stresses experienced during test flights conducted aboard helicopters, fixed-wing aircraft, and Morpheus, a terrestrial rocket-powered vehicle developed by NASA Johnson Space Center. This paper provides an overview of the sensor and presents results obtained during recent field experiments including a helicopter flight test conducted in December 2012 and Morpheus flight tests conducted during March of 2014.

Pierrottet, Diego F.↗

Autonomous docking ground demonstration (category 3)

The NASA Johnson Space Center (JSC) is involved in the development of an autonomous docking ground demonstration. The demonstration combines the technologies, expertise and facilities of the JSC Tracking and Communications Division (EE), Structures and Mechanics Division (ES), and the Navigation, Guidance and Control Division (EG) and their supporting contractors. The autonomous docking ground demonstration is an evaluation of the capabilities of the laser sensor system to support the docking phase (12ft to contact) when operated in conjunction with the Guidance, Navigation and Control Software. The docking mechanism being used was developed for the Apollo Soyuz Test Program. This demonstration will be conducted using the Six-Degrees of Freedom (6-DOF) Dynamic Test System (DTS). The DTS environment simulates the Space Station Freedom as the stationary or target vehicle and the Orbiter as the active or chase vehicle. For this demonstration the laser sensor will be mounted on the target vehicle and the retroreflectors on the chase vehicle. This arrangement was used to prevent potential damage to the laser. The sensor system. GN&C and 6-DOF DTS will be operated closed-loop. Initial condition to simulate vehicle misalignments, translational and rotational, will be introduced within the constraints of the systems involved. Detailed description of each of the demonstration components (e.g., Sensor System, GN&C, 6-DOF DTS and supporting computer configuration) including their capabilities and limitations will be discussed. A demonstration architecture drawing and photographs of the test configuration will be presented.

Lamkin, Steve L.↗

Payload-Directed Control of Geophysical Magnetic Surveys

Using non-navigational (e.g. imagers, scientific) sensor information in control loops is a difficult problem to which no general solution exists. Whether the task can be successfully achieved in a particular case depends highly on problem specifics, such as application domain and sensors of interest. In this study, we investigate the feasibility of using magnetometer data for control feedback in the context of geophysical magnetic surveys. An experimental system was created and deployed to (a) assess sensor integration with autonomous vehicles, (b) investigate how magnetometer data can be used for feedback control, and (c) evaluate the feasibility of using such a system for geophysical magnetic surveys. Finally, we report the results of our experiments and show that payload-directed control of geophysical magnetic surveys is indeed feasible.

Lee, Ritchie↗

Liaison-Supplemented Navigation of a Crewed Vehicle in a Lunar Halo Orbit

This paper offers an early examination of the challenges of navigating a crewed vehicle, with all of the associated unmodeled accelerations that arise from the crew's activities, in an orbit about the Earth-Moon L2 point. The combination of the unstable nature of libration orbits with the lack of acceleration knowledge makes the station keeping strategy challenging. It is found that a combination of ground tracking and satellite-to-satellite tracking produces the most favorable navigation accuracy. This paper examines the costs and benefits of applying LiAISON (Linked Autonomous Interplanetary Satellite Orbit Navigation) to a crewed mission in an unstable L2 orbit.

ARTEMIS↗

Autonomous Constrained Control for Arbitrary Thruster Configurations of Gimbaling Thrusters in SE(3)

In order to develop robust autonomy in spacecraft, it is desirable to develop methods for guiding and controlling arbitrarily-configured spacecraft with any combination of thrusters of various types, i.e. either static reaction control system thrusters and gimbaling thrusters. Scenarios in which autonomous selection of thrusters may be needed include the case of a stuck or inhibited thruster that restricts the motion of the vehicle, vehicles with changing mass properties such as logistics modules or tugs, or vehicles that have imposed constraints on thrusters during docking in order to avoid plume impingement on a space station or adjacent spacecraft. To that end, a spacecraft must be able to rapidly and autonomously reconfigure thruster firing histories and update guidance protocols in accordance with newly imposed constraints. In this paper, a methodology is presented that enables a spacecraft to autonomously select thrusters of any configuration and type in order to optimally match a desired 6-degree-of-freedom navigation and control within the special Euclidean SE(3) framework. The residual motion imposed by off-nominal thruster configurations or thrusters that are not fully controllable is identified by the spacecraft and solved for over time, both for static reaction control systems and for the case of gimbaling thrusters.

GN&C↗

Planetary Aerobots: A Program for Robotic Balloon Exploration

The exploration of the solar system has proceeded in several phases beginning with flyby missions, proceeding to orbiters, then to probes and landers and finally mobile vehicles that operate on the surface and in its atmosphere. For the most accessible planetary bodies, Venus and Mars, we are now entering the phase of mobile exploration of the surface and atmosphere.

robotically-controlled↗

Multiple-Agent Air/Ground Autonomous Exploration Systems

Autonomous systems of multiple-agent air/ground robotic units for exploration of the surfaces of remote planets are undergoing development. Modified versions of these systems could be used on Earth to perform tasks in environments dangerous or inaccessible to humans: examples of tasks could include scientific exploration of remote regions of Antarctica, removal of land mines, cleanup of hazardous chemicals, and military reconnaissance. A basic system according to this concept (see figure) would include a unit, suspended by a balloon or a blimp, that would be in radio communication with multiple robotic ground vehicles (rovers) equipped with video cameras and possibly other sensors for scientific exploration. The airborne unit would be free-floating, controlled by thrusters, or tethered either to one of the rovers or to a stationary object in or on the ground. Each rover would contain a semi-autonomous control system for maneuvering and would function under the supervision of a control system in the airborne unit. The rover maneuvering control system would utilize imagery from the onboard camera to navigate around obstacles. Avoidance of obstacles would also be aided by readout from an onboard (e.g., ultrasonic) sensor. Together, the rover and airborne control systems would constitute an overarching closed-loop control system to coordinate scientific exploration by the rovers.

Fink, Wolfgang↗

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS↗

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS↗

A Survey of Autonomous Navigation Techniques Applicable to Lunar Surface Exploration

As humanity returns to the Moon, and more and more attention is being paid to lunar surface operations, there is a greater need than ever for methods of surface navigation. These could be methods of computer-assisted orienteering for astronauts exploring on foot during an Extra-Vehicular Activity (EVA), or methods of solving the Lost-on-the-Moon problem to initialize a crewed or autonomous rover’s state estimate. It may also be necessary to process navigation data associated with surface samples or other surface operations a posteriori to better understand where that analysis occurred. Autonomous rover operation will also require Hazard Detection and Avoidance (HDA) and terrain-aware pathfinding. While navigation on the surface of the Moon will likely rely on Earth-based assets such as the Deep Space Network (DSN) or communication with other spacecraft (e.g., LunaNet, LCRNS, pre-deployed moon beacons, a nearby lander) it may be necessary to navigate in a loss-of-communication scenario. This paper analyzes the methods of surface navigation used on other celestial bodies, such as those used during the Apollo missions and autonomous exploration of Mars, as well as novel methods which have been studied but not yet implemented which may prove useful. It is shown that the navigator has myriad options when processing data from an Inertial Measurement Unit (IMU), a star tracker, (rover) wheel encoders, optical cameras, and LIght Detection and Ranging (LIDAR) sensors. The intention of this paper is to provide a broad overview of what has been done and what could be done, to aid those designing vehicles and/or missions to the lunar surface.

Paul D Mckee↗

A Survey of Autonomous Navigation Techniques Applicable to Lunar Surface Exploration

As humanity returns to the Moon, and more and more attention is being paid to lunar surface operations, there is a greater need than ever for methods of surface navigation. These could be methods of computer-assisted orienteering for astronauts exploring on foot during an Extra-Vehicular Activity (EVA), or methods of solving the Lost-on-the-Moon problem to initialize a crewed or autonomous rover’s state estimate. It may also be necessary to process navigation data associated with surface samples or other surface operations a posteriori to better understand where that analysis occurred. Autonomous rover operation will also require Hazard Detection and Avoidance (HDA) and terrain-aware pathfinding. While navigation on the surface of the Moon will likely rely on Earth-based assets such as the Deep Space Network (DSN) or communication with other spacecraft (e.g., LunaNet, LCRNS, pre-deployed moon beacons, a nearby lander) it may be necessary to navigate in a loss-of-communication scenario. This paper analyzes the methods of surface navigation used on other celestial bodies, such as those used during the Apollo missions and autonomous exploration of Mars, as well as novel methods which have been studied but not yet implemented which may prove useful. It is shown that the navigator has myriad options when processing data from an Inertial Measurement Unit (IMU), a star tracker, (rover) wheel encoders, optical cameras, and LIght Detection and Ranging (LIDAR) sensors. The intention of this paper is to provide a broad overview of what has been done and what could be done, to aid those designing vehicles and/or missions to the lunar surface.

Paul McKee↗

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) Pathfinder for Artemis Gateway

The Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission was developed by NASA in collaboration with Advanced Space, LLC of Westminster, Colorado. This technology demonstration mission serves as a pathfinder for near rectilinear halo orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) is the intended orbit for NASA’s Artemis Gateway, a small, human-tended space station planned for lunar orbit. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and stationkeeping requirements for Gateway’s Power and Propulsion Element. Therefore, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. The CAPSTONE mission consists of a 12-unit (U)+ CubeSat developed, integrated, and tested by the Terran Orbital Corporation that carries a payload communications system capable of crosslink ranging with NASA’s Lunar Reconnaissance Orbiter (LRO). CAPSTONE contains a chip-scale atomic clock (CSAC) for a one-way ranging experiment with NASA’s Deep Space Network, a dedicated payload flight computer for software demonstration, and a camera. The launch, coordinated by NASA’s Launch Services Program, was provided by Rocket Lab on its Electron launch vehicle using their Photon upper stage to deploy the CAPSTONE spacecraft. The mission launched June 28, 2022. The CAPSTONE spacecraft deployed from the Photon stage and traversed an approximately 4-month, highly fuel-efficient transfer phase entering the NRHO November 13, 2022, for a six-month primary mission phase. The mission is currently in a twelve-month technology enhancement operations phase. The CAPSTONE technology demonstration mission is led by Advanced Space, LLC. Spacecraft development and mission operations are conducted by Terran Orbital Corporation of Irvine, California. Noted accomplishments for the CAPSTONE mission include demonstrating the accessibility of NHROs; validating key operational concepts in the NHRO environment; laying the foundation for commercial support of future lunar operations; and accelerating the availability of peer-to-peer navigation capabilities provided by the Cislunar Autonomous Positioning System (CAPS). The CAPSTONE mission is funded through NASA’s Small Spacecraft Technology (SST) program, which is one of several programs within NASA’s Space Technology Mission Directorate. The program is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft. The CAPSTONE mission launch was provided by NASA’s Exploration Systems Development Missions Directorate’s Advanced Exploration Systems Division. Coordination and acquisition of the launch was managed by NASA’s Launch Services Program. The CAPSTONE mission and project status will be presented.

Elwood Agasid↗

NASA Johnson Space Center: Mini AERCam Testing with GSS6560

This slide presentation reviews the testing of the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) with the GPS/SBAS simulation system, GSS6560. There is a listing of several GPS based programs at NASA Johnson, including the testing of Shuttle testing of the GPS system. Including information about Space Integrated GPS/INS (SIGI) testing. There is also information about the standalone ISS SIGI test,and testing of the SIGI for the Crew Return Vehicle. The Mini AERCam is a small, free-flying camera for remote inspections of the ISS, it uses precise relative navigation with differential carrier phase GPS to provide situational awareness to operators. The closed loop orbital testing with and without the use of the GSS6550 system of the Mini AERCam system is reviewed.

Cryant, Scott P.↗

Doppler Lidar Sensor for Precision Landing on the Moon and Mars

Landing mission concepts that are being developed for exploration of planetary bodies are increasingly ambitious in their implementations and objectives. Most of these missions require accurate position and velocity data during their descent phase in order to ensure safe soft landing at the pre-designated sites. To address this need, a Doppler lidar is being developed by NASA under the Autonomous Landing and Hazard Avoidance (ALHAT) project. This lidar sensor is a versatile instrument capable of providing precision velocity vectors, vehicle ground relative altitude, and attitude. The capabilities of this advanced technology have been demonstrated through two helicopter flight test campaigns conducted over a vegetation-free terrain in 2008 and 2010. Presently, a prototype version of this sensor is being assembled for integration into a rocket-powered terrestrial free-flyer vehicle. Operating in a closed loop with vehicle's guidance and navigation system, the viability of this advanced sensor for future landing missions will be demonstrated through a series of flight tests in 2012.

Amzajerdian, Farzin↗

Seeker 1.0: Prototype Robotic Free Flying Inspector Mission Overview

Seeker 1.0 is a prototype free flying robot that will one day be capable of inspecting human-rated spacecraft. Building off previous free flyer experience, this technology will eventually improve safety of human spacecraft by offering a variety of inspection capabilities for both routine and emergency scenarios providing increased capability and safety over current inspection methods. Seeker 1.0 is capable of 6 degree of freedom flight via a cold gas propulsion system and can operate up to 1 hour via a semi-autonomous guidance, navigation, and control system. The prototype spacecraft is capable of capturing still images at a variety of resolutions up to 13 MP. The initial test flight utilizes a command and data relay box called Kenobi. Kenobi is a derivative of the Seeker design and will communicate between Cygnus and Seeker and store data for post-mission downlink. Seeker and Kenobi have launched inside a NanoRacks External CubeSat Deployer (NRCSD-E) attached to the NG-11 Cygnus ISS resupply vehicle and will operate after Cygnus departs ISS and moves to a safe altitude. Operations will last approximately 30 minutes and will consist of basic vehicle maneuvers while capturing high-resolution still images. With any remaining time and propellant, Seeker will demonstrate additional safety capabilities and maneuvers required for operations around a crewed spacecraft. The Seeker project utilized the Class IE process that allows for streamlined flight hardware development and increased mission risk tolerance.

Spacecraft Inspection↗

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 SPLICE Project: Development and Testing of Precision Landing GN&C Technologies

NASA's technology advancement needs for entry, descent and landing call for high-precision, high-rate sensors that can improve navigation accuracy and vehicle control performance. Higher landing accuracy is required for any future human lander missions, and likely, for most robotic missions 1,2. Sensors and algorithms that significantly reduce navigation errors and can image the local terrain will enable landing at locations of high scientific interest that would otherwise pose significant risk to the vehicle. The Safe and Precise Landing-Integrated Capabilities Evolution project, or SPLICE, is developing precision landing and hazard avoidance (PL&HA) technologies for NASA and for potential commercial space flight missions. SPLICE technologies include sensors, algorithms, advanced space flight computing capabilities, and simulation tools used to integrate and study guidance, navigation, and control (GN&C) system performance. SPLICE efforts include hardware-in-the-loop (HWIL) simulation testing, ground testing, and flight testing, including reuse of hardware from the CoOperative Blending of Autonomous Landing Technologies (COBALT) suborbital flight-test payload3,4. Two of the precise navigation sensors that are being developed and matured within SPLICE are LiDARs. Since 2006, NASA Langley has been developing a Navigation Doppler LiDAR (NDL) for precise velocity measurements, and SPLICE is building an NDL engineering test unit (ETU) that will be brought up to TRL 6 following environmental and high-speed1,2 testing. NASA Goddard is developing a Hazard Detection LiDAR (HD LiDAR) engineering development unit (EDU) for SPLICE that has relevance to future human and robotic lander missions. The HD LiDAR will be flight test and matured to TRL 5.

Restrepo, Carolina I.↗