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NASA NTRS2021

LiDAR-Based Map Relative Localization Performance Analysis for Landing on Europa

This paper presents preliminary simulations andanalyses done to assess the feasibility of performing Map RelativeLocalization (MRL) with the Europa Lander LiDAR beingdeveloped for the Europa Lander Pre-Phase A concept. MapRelative Localization is the process of determining the horizontalposition of a lander with respect to an onboard, a-priori map,by comparing the map to sensor observations of the terrain duringdeorbit, descent, and landing (DDL). Although kilometerscaleposition knowledge is commonly available during DDL,landing in hazard-rich environments requires position errors of100 m or less. Prior knowledge in the case of Europa Landerwill be visual and topographic maps collected by the upcomingEuropa Clipper mission. The Mars 2020 Lander Vision System(LVS) uses images from a camera to localize with respect tovisual maps. This technology, as well as a 3D imaging LiDAR indevelopment for hazard detection, is currently baselined for theEuropa Lander Pre-Phase A concept. This paper investigatesthe potential use of the hazard detection LiDAR to performMRL with respect to a 3D digital elevation model (DEM)provided by the Europa Clipper mission, as an alternative orbackup solution to passive optical MRL. Compared to passiveoptical MRL, one advantage of LiDAR-based localization isthat it is insensitive to lighting conditions, potentially relaxingrequirements on synchronizing map acquisition and landingtime of day. To analyze LiDAR based MRL performance,six representative terrains are synthetically up-sampled fromGalileo-derived maps of Europa to a resolution of 0.5 m/pxand covering an area of 4 km by 4 km. These maps are usedas ground-truth to generate simulated noisy a-priori onboardtopographic maps expected from Europa Clipper as well assimulated LiDAR DEMs generated at an altitude of 5 km duringEuropa Lander DDL. The simulated LiDAR DEM is matchedagainst the simulated map via 2D normalized cross-correlation,exploiting the accurately known spacecraft attitude to avoidthe need for more computationally intensive algorithms such asIterative Closest Point (ICP). Two sources of measurement errorare identified for analysis: 1) additive Gaussian noise in therange measurements from the Europa Lander LiDAR and theEuropa Clipper derived maps and 2) errors in the LiDAR DEMinduced by errors in the Europa Lander state estimate which isused to de-warp the LiDAR scan data into a DEM format. Weassess the effect of each of these types of errors independently onmatching performance as well as the overall performance whenall types of error are introduced. Additionally, we present theresult of a sensitivity study to terrain frequency content.

Trawny, Nikolas↗
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 NTRS2017

The Intelligent Landing System for Safe and Precise Landing on Europa

Europa, the smallest of Jupiter’s Galilean moons, is thought to harbor a vast liquid water ocean beneath its icy crust, making it one of the most scientifically intriguing targets for a robotic surface sampling mission in our Solar System. However, autonomously landing a spacecraft safely and precisely on Europa poses unique challenges, such as very little existing high-resolution reconnaissance imagery, a surface expected to be very rough and hazardous over a wide range of scales, an extremely intense ionizing radiation environment, and very limited lander resources for mass and volume. To address these challenges, we propose a novel Intelligent Landing System (ILS) combining four Guidance, Navigation & Control (GN&C) sensing functions – velocimetry, altimetry, map-relative localization, and hazard detection – that would together enable safe and precise landing on Europa’s surface. The ILS is a smart sensor system, combining an inertial measurement unit (IMU), a monocular, passive-optical camera, and a light detection and ranging (Li-DAR) sensor with dedicated computing resources as well as an onboard 3D terrain map. The ILS leverages more than a decade of technology development from programs such as the Lander Vision System, currently baselined on the Mars 2020 mission. This paper provides a detailed description of the proposed ILS architecture and concept of operations, as well as select preliminary simulation results to assess performance and robustness.

Trawny, Nikolas↗
NASA NTRS2021

The Mars 2020 Perseverance Navigation Filter

The Mars 2020 (M2020) Entry Descent and Landing (EDL) system delivered a rover named “Perseverance” at Jezero crater (Mars) on February 18th, 2021. M2020 EDL used a Guidance Navigation and Control (GN&C) system to achieve its landing target objectives. The navigation filter (NavFilter) integrated Descent Inertial Measurement Unit (DIMU) measurements to estimate position and attitude. The NavFilter also used the Terminal Descent Sensor (TDS) to es-timate surface-relative position and velocity corrections. The NavFilter provided all of the dynamic state information to the entry controller, entry guidance, Lander Vision System (LVS) and powered descent guidance and control algo-rithms. The NavFilter for Perseverance is based on Curiosity’s NavFilter with a couple of modifications.

Casoliva, Jordi↗
NASA NTRS2015

Flight Testing of Terrain-Relative Navigation and Large-Divert Guidance on a VTVL Rocket

Since 2011, the Autonomous Descent and Ascent Powered-Flight Testbed (ADAPT) has been used to demonstrate advanced descent and landing technologies onboard the Masten Space Systems (MSS) Xombie vertical-takeoff, vertical-landing suborbital rocket. The current instantiation of ADAPT is a stand-alone payload comprising sensing and avionics for terrain-relative navigation and fuel-optimal onboard planning of large divert trajectories, thus providing complete pin-point landing capabilities needed for planetary landers. To this end, ADAPT combines two technologies developed at JPL, the Lander Vision System (LVS), and the Guidance for Fuel Optimal Large Diverts (G-FOLD) software. This paper describes the integration and testing of LVS and G-FOLD in the ADAPT payload, culminating in two successful free flight demonstrations on the Xombie vehicle conducted in December 2014.

ADAPT↗
NASA NTRS2016

COBALT CoOperative Blending of Autonomous Landing Technology

COBALT is a terrestrial test platform for development and maturation of GN&C (Guidance, Navigation and Control) technologies for PL&HA (Precision Landing and Hazard Avoidance). The project is developing a third generation, Langley Navigation Doppler Lidar (NDL) for ultra-precise velocity and range measurements, which will be integrated and tested with the JPL Lander Vision System (LVS) for Terrain Relative Navigation (TRN) position estimates. These technologies together provide navigation that enables controlled precision landing. The COBALT hardware will be integrated in 2017 into the GN&C subsystem of the Xodiac rocket-propulsive Vertical Test Bed (VTB) developed by Masten Space Systems (MSS), and two terrestrial flight campaigns will be conducted: one open-loop (i.e., passive) and one closed-loop (i.e., active).

Carson, John M. III↗
NASA NTRS2017

COBALT: Development of a Platform to Flight Test Lander GN&C Technologies on Suborbital Rockets

The NASA COBALT Project (CoOperative Blending of Autonomous Landing Technologies) is developing and integrating new precision-landing Guidance, Navigation and Control (GN&C) technologies, along with developing a terrestrial fight-test platform for Technology Readiness Level (TRL) maturation. The current technologies include a third- generation Navigation Doppler Lidar (NDL) sensor for ultra-precise velocity and line- of-site (LOS) range measurements, and the Lander Vision System (LVS) that provides passive-optical Terrain Relative Navigation (TRN) estimates of map-relative position. The COBALT platform is self contained and includes the NDL and LVS sensors, blending filter, a custom compute element, power unit, and communication system. The platform incorporates a structural frame that has been designed to integrate with the payload frame onboard the new Masten Xodiac vertical take-o, vertical landing (VTVL) terrestrial rocket vehicle. Ground integration and testing is underway, and terrestrial fight testing onboard Xodiac is planned for 2017 with two flight campaigns: one open-loop and one closed-loop.

Carson, John M., III↗
NASA NTRS2016

Cobalt: Development and Maturation of GN&C Technologies for Precision Landing

The CoOperative Blending of Autonomous Landing Technologies (COBALT) instrument is a terrestrial test platform for development and maturation of guidance, navigation and control (GN&C) technologies for precision landing. The project is developing a third-generation Langley Research Center (LaRC) navigation doppler lidar (NDL) for ultra-precise velocity and range measurements, which will be integrated and tested with the Jet Propulsion Laboratory (JPL) lander vision system (LVS) for terrain relative navigation (TRN) position estimates. These technologies together provide precise navigation knowledge that is critical for a controlled and precise touchdown. The COBALT hardware will be integrated in 2017 into the GN&C subsystem of the Xodiac rocket-propulsive vertical test bed (VTB) developed by Masten Space Systems, and two terrestrial flight campaigns will be conducted: one open-loop (i.e., passive) and one closed-loop (i.e., active).

Carson, John M.↗
NASA NTRS2021

Mars 2020 Perseverance Edl Gnc Safe Target Selection Reconstruction

On February 18th, 2021, NASA landed Perseverance on the Jezero crater (on Mars) using a new Terrain Relative Navigation (TRN) capability. TRN is com-prised of a new sensor, the Lander Vision System (LVS), and a new GNC algo-rithm, the Safe Target Selection (STS). LVS localized the descent vehicle with respect to a map. STS selected the safe landing target within a reachable region from the on-board Safe Targets Map (STM). The landing target was then handed to the Mars Science Laboratory (MSL) heritage powered descent GNC system to execute the landing. This paper describes the design and the as-flown performance of the STS algorithm.

Dutta, Soumyo↗
NASA NTRS2009

Synthetic and Enhanced Vision System for Altair Lunar Lander

Past research has demonstrated the substantial potential of synthetic and enhanced vision (SV, EV) for aviation (e.g., Prinzel & Wickens, 2009). These augmented visual-based technologies have been shown to significantly enhance situation awareness, reduce workload, enhance aviation safety (e.g., reduced propensity for controlled flight -into-terrain accidents/incidents), and promote flight path control precision. The issues that drove the design and development of synthetic and enhanced vision have commonalities to other application domains; most notably, during entry, descent, and landing on the moon and other planetary surfaces. NASA has extended SV/EV technology for use in planetary exploration vehicles, such as the Altair Lunar Lander. This paper describes an Altair Lunar Lander SV/EV concept and associated research demonstrating the safety benefits of these technologies.

Prinzell, Lawrence J., III↗
NASA NTRS2008

Synthetic Vision Displays for Planetary and Lunar Lander Vehicles

Aviation research has demonstrated that Synthetic Vision (SV) technology can substantially enhance situation awareness, reduce pilot workload, improve aviation safety, and promote flight path control precision. SV, and related flight deck technologies are currently being extended for application in planetary exploration vehicles. SV, in particular, holds significant potential for many planetary missions since the SV presentation provides a computer-generated view for the flight crew of the terrain and other significant environmental characteristics independent of the outside visibility conditions, window locations, or vehicle attributes. SV allows unconstrained control of the computer-generated scene lighting, terrain coloring, and virtual camera angles which may provide invaluable visual cues to pilots/astronauts, not available from other vision technologies. In addition, important vehicle state information may be conformally displayed on the view such as forward and down velocities, altitude, and fuel remaining to enhance trajectory control and vehicle system status. The paper accompanies a conference demonstration that introduced a prototype NASA Synthetic Vision system for lunar lander spacecraft. The paper will describe technical challenges and potential solutions to SV applications for the lunar landing mission, including the requirements for high-resolution lunar terrain maps, accurate positioning and orientation, and lunar cockpit display concepts to support projected mission challenges.

Arthur, Jarvis J., III↗
NASA NTRS2004

Autonomous Navigation Results from the Mars Exploration Rover (MER) Mission

In January, 2004, the Mars Exploration Rover (MER) mission landed two rovers, Spirit and Opportunity, on the surface of Mars. Several autonomous navigation capabilities were employed in space for the first time in this mission. ]n the Entry, Descent, and Landing (EDL) phase, both landers used a vision system called the, Descent Image Motion Estimation System (DIMES) to estimate horizontal velocity during the last 2000 meters (m) of descent, by tracking features on the ground with a downlooking camera, in order to control retro-rocket firing to reduce horizontal velocity before impact. During surface operations, the rovers navigate autonomously using stereo vision for local terrain mapping and a local, reactive planning algorithm called Grid-based Estimation of Surface Traversability Applied to Local Terrain (GESTALT) for obstacle avoidance. ]n areas of high slip, stereo vision-based visual odometry has been used to estimate rover motion, As of mid-June, Spirit had traversed 3405 m, of which 1253 m were done autonomously; Opportunity had traversed 1264 m, of which 224 m were autonomous. These results have contributed substantially to the success of the mission and paved the way for increased levels of autonomy in future missions.

autonomous↗
NASA NTRS2021

LiDAR-Inertial Based Navigation and Mapping for Precision Landing

Future lander missions will travel to ambitious, scientifically interesting locations near rough and dangerous terrain. They will need to operate with limited prior information about the terrain, and under varying lighting conditions. Landing safely and precisely in the face of these challenges is difficult for existing vision-based landing systems, which require detailed orbital reconnaissance, a priori hazard maps, and impose time-of-day restrictions on landing to ensure similar lighting conditions in orbital and descent imagery. Advanced 3D imaging LiDAR systems currently under development, and originally intended for single-scan hazard detection, have the potential to be operated continuously from altitudes of up to 5 km. Used together with existing inertial measurement units (IMUs), these sensors open a path-to-flight for a full navigation and mapping system, which could replace or augment a traditional landing sensor suite. A landing system based around these sensors can perform accurate altimetry, map-relative localization (MRL), LiDAR-inertial odometry, and map refinement in an illumination-insensitive manner, over unknown or partially known terrain. This paper outlines preliminary work on a LiDAR-inertial landing system that: estimates the spacecraft trajectory during entry, descent, and landing (EDL); and maps the topography of the terrain below, for future use in hazard detection and avoidance. An incremental, factor graph based, smoothing approach is used to solve for the maximum a posteriori trajectory of spacecraft states. Integrated IMU measurements and features tracked in adjacent range and intensity images are used to estimate motion (LiDAR-inertial odometry). LiDAR scans are binned into motion-corrected digital elevation models (DEMs), which are matched to an existing orbital topographic map to provide absolute position information (MRL). The estimated trajectory is then used to project the LiDAR scans into the map frame, creating a variable-resolution quadtree topographic map suitable for hazard detection and avoidance. Existing topographic maps from throughout the solar system (i.e., Earth, the Moon, Mars, Ceres, Vesta, Europa, Enceladus, and Eros) are upsampled for use in EDL simulations. The Mars 2020 Lander Vision System Simulator (LVSS) is extended to simulate LiDAR-inertial data for realistic EDL trajectories. Results of the algorithm operating on the simulated data are presented. Estimated spacecraft trajectory and refined map are compared to ground truth to assess estimation accuracy.

Katake, Anup↗
NASA NTRS1989

Hybrid vision for automated spacecraft landing

A hyrbid real-time vision system concept is proposed for Mars lander guidance and control for the Mars Rover/Sample Return mission. The system includes digital and optical processing methods with high speed digital image warping to preprocess a video image for optical correlation. The system also includes position estimation by synthetic estimation filtering, image stabilization by joint transform optical correlation, and hazard identification from measurements of optical flow by sequential image subtraction.

Juday, Richard D.↗
NASA NTRS2020

Artificial Gravity in Mars Orbit for Crew Acclimation

NASA’s current baseline plan for a crewed Mars mission anticipates a transit time of up to three hundred days in microgravity and 3-14 days on the Martian surface for gravity acclimation before the crew can safely perform their first Extra-Vehicular Activity (EVA). While there are multiple options for how initial surface operations will be performed, all current designs involve acclimation on the surface, and the impacts on the mission schedule, required supplies, and crew lander systems are significant. This paper proposes an alternative option utilizing artificial gravity, which offers benefits in terms of mission scope, mass savings, crew health, and long-term strategic vision. By moving the acclimation requirement to the orbiting habitat’s existing systems, rather than adding redundant systems to the lander, the Mars Descent Vehicle (MDV) can be a much smaller, simpler, and lighter design. Rather than the lander being designed to support crew for days, it would be mere hours. While ambitious, the concept of pre-acclimation in orbit can be not only safe and feasible, but done with fairly minimal changes to the planned architecture and overall mass requirements. The data used draws on decades of established research and demonstrates how this capability can be not only used for pre-acclimation, but also to support crew during early orbital-only missions, surface abort contingency scenarios, return-to-orbit abort scenarios, and as an early proof of capability into larger and more ambitious artificial gravity designs needed for extended exploration missions in the future.

Rowe, Justin↗
NASA NTRS2022

IRIS: High-fidelity Perception Sensor Modeling for Closed-Loop Planetary Simulations

Perception plays a key role in autonomous and semi-autonomous planetary exploration vehicles. For instance, landers can use computer vision techniques for identifying safe landing locations, aerial vehicles use cameras as navigation sensors, and planetary rovers use them for localization and hazard detection. Engineering simulations of such systems requires the accurate modeling of perception and vision sensors for simulating autonomy scenarios. In addition, the modeling of sensors for landers, aerial and ground vehicles requires the ability to handle large and high-resolution terrains, the accurate modeling of illumination, hi-fidelity rendering via ray/path tracing and the inclusion of sensor characteristics. Vision sensor models strive to simulate sensor reality by using physics principles to model the interaction of light and objects. Furthermore, high frame rate performance is highly desirable for in-the-loop simulations involving vehicle dynamics and control software. In this paper we describe a new sensor modeling capability called Inter-planetary Rendering for Imaging and Sensors (IRIS) that meets these requirements for the real-time and high-fidelity simulation of vision sensors for planetary aerospace and robotics applications.

Elmquist, Asher↗
NASA NTRS2009

Human Systems Integration (HSI) Case Studies from the NASA Constellation Program

The National Aeronautics and Space Administration (NASA) Constellation Program is responsible for planning and implementing those programs necessary to send human explorers back to the moon, onward to Mars and other destinations in the solar system, and to support missions to the International Space Station. The Constellation Program has the technical management responsibility for all Constellation Projects, including both human rated and non-human rated vehicles such as the Crew Exploration Vehicle, EVA Systems, the Lunar Lander, Lunar Surface Systems, and the Ares I and Ares V rockets. With NASA s new Vision for Space Exploration to send humans beyond Earth orbit, it is critical to consider the human as a system that demands early and continuous user involvement, inclusion in trade offs and analyses, and an iterative "prototype/test/ redesign" process. Personnel at the NASA Johnson Space Center are involved in the Constellation Program at both the Program and Project levels as human system integrators. They ensure that the human is considered as a system, equal to hardware and software vehicle systems. Systems to deliver and support extended human habitation on the moon are extremely complex and unique, presenting new opportunities to employ Human Systems Integration, or HSI practices in the Constellation Program. The purpose of the paper is to show examples of where human systems integration work is successfully employed in the Constellation Program and related Projects, such as in the areas of habitation and early requirements and design concepts.

Baggerman, Susan↗