Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) Descent and Landing Computer (DLC)
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Precision Landing and Hazard Avoidance↗
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Precision Lunar Landing System ACO (L2S ACO)
Blue Origin is partnering with NASA to evaluate and mature a navigation and guidance system for lunar missions to enable safe and precise landing.
Guidance↗
An Overview of NASA Lidar Technologies for Precision Safe Landing on Planetary Bodies
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Landing Lidar↗
FY23 Astrobotic TRN Annual Program Review
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Terrain Relative Navigation↗
Optimizing Air Traffic - Integrating Artificial Intelligence and Machine Learning in Flight Path Planning and 3D Airspace Visualization for Air Traffic Control
Air Traffic Control (ATC) systems are vital components of the National Airspace System (NAS). ATC, Airport Traffic Control Towers (ATCT), and Terminal Radar Approach Control (TRACON) are responsible for directing all flights departing from and arriving at airports, managing our nation’s airspace, preventing potential accidents, and ensuring that every flight is accounted for. However, these systems often face challenges in effectively monitoring the skies. Issues such as poor communication between operators, difficulty in performing operations, and the constant need for vigilance frequently burden ATC operators. Additionally, the projected increase in air traffic in the coming years will only exacerbate the stress associated with this role. To address these issues, we propose a system that assists ATC operators in situations such as handovers, emergencies, and routing aircraft to avoid weather hazards. Our solution includes an Artificial Intelligence (AI) and Machine Learning (ML)-based Flight Pathways Planning System (FPPS) designed to find the fastest and most optimal routes for aircraft, taking into account weather conditions, restricted terrain, and Extended-Range Twin-Engine Operational Performance Standards (ETOPS) ratings. The proposed Predictive Weather Planning Model, included in FPPS, adjusts routes based on real-time and forecasted weather conditions. Additionally, our NVIDIA Omniverse 3D Visualization System offers a highly interactive environment for better visualization and a clear view of the airspace. By incorporating these systems, the roles of ATC, ATCT, and TRACON operators will become more manageable and less stressful, equipping them to efficiently handle the growing density of airspace.
Regina Ayoubi↗
Hardware in the Loop Performance of Terrestrial Powered Descent Dual Quaternion Guidance with a Custom First-Order Solver
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Convex Optimization↗
Hazard Boresight Relative Navigation for Safe Lunar Landing
Hazard Boresight Relative Navigation greatly simplifies Hazard Detection and Avoidance methodologies by providing a common interface between the Hazard DEM, the Safe Site Selection Algorithm, the size of the landing ellipse, the divert distance and the Guidance targeting algorithm. After the Safe Site is selected from the DEM, Hazard Boresight Relative Navigation will replace the original planet target with the boresight target. The location of the safe site relative to the boresight is sent back to GNC for the divert maneuver.
Stephen R. Steffes↗
Achieving safe autonomous landings on Mars using vision-based approaches
Autonomous landing capabilities will be critical to the success of planetary exploration missions, and in particular to the exploration of Mars. Past studies have indicated that the probability of failure associated with open-loop landings is unacceptably high. Two approaches to achieving autonomous landings with higher probabilities of success are currently under analysis. If a landing site has been certified as hazard free, then navigational aids can be used to facilitate a precision landing. When only limited surface knowledge is available and landing areas cannot be certified as hazard free, then a hazard detection and avoidance approach can be used, in which the vehicle selects hazard free landing sites in real-time during its descent. Issues pertinent to both approaches, including sensors and algorithms, are presented. Preliminary results indicate that one promising approach to achieving high accuracy precision landing is to correlate optical images of the terrain acquired during the terminal descent phase with a reference image. For hazard detection scenarios, a sensor suite comprised of a passive intensity sensor and a laser ranging sensor appears promising as a means of achieving robust landings.
Pien, Homer↗
Aerobot Autonomy Architecture
An architecture for autonomous operation of an aerobot (i.e., a robotic blimp) to be used in scientific exploration of planets and moons in the Solar system with an atmosphere (such as Titan and Venus) is undergoing development. This architecture is also applicable to autonomous airships that could be flown in the terrestrial atmosphere for scientific exploration, military reconnaissance and surveillance, and as radio-communication relay stations in disaster areas. The architecture was conceived to satisfy requirements to perform the following functions: a) Vehicle safing, that is, ensuring the integrity of the aerobot during its entire mission, including during extended communication blackouts. b) Accurate and robust autonomous flight control during operation in diverse modes, including launch, deployment of scientific instruments, long traverses, hovering or station-keeping, and maneuvers for touch-and-go surface sampling. c) Mapping and self-localization in the absence of a global positioning system. d) Advanced recognition of hazards and targets in conjunction with tracking of, and visual servoing toward, targets, all to enable the aerobot to detect and avoid atmospheric and topographic hazards and to identify, home in on, and hover over predefined terrain features or other targets of scientific interest. The architecture is an integrated combination of systems for accurate and robust vehicle and flight trajectory control; estimation of the state of the aerobot; perception-based detection and avoidance of hazards; monitoring of the integrity and functionality ("health") of the aerobot; reflexive safing actions; multi-modal localization and mapping; autonomous planning and execution of scientific observations; and long-range planning and monitoring of the mission of the aerobot. The prototype JPL aerobot (see figure) has been tested extensively in various areas in the California Mojave desert.
Elfes, Alberto↗
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↗
Autonomous landing on Mars
Long communication times between earth and Mars demand autonomous landing capabilities. If high-resolution imagery acquired from an orbiter is available to select and certify a specific safe landing site or sites, navigational updates relative to the surface can be used to achieve the necessary accuracy to land within these certified sites. Autonomous registrations of the orbiter's imagery with photographs of the landing area taken by the lander during descent can provide the necessary accuracy and robustness. If orbital imagery is not available, autonomous hazard recognition and avoidance will be required to guide the lander to a hazard-free site. Feature extraction and matching algorithms, applied to visible light imagery and optimized to the terrain discovered by the Viking landers, can provide both an accurate surface-relative navigational update capability and a hazard recognition capability.
Stevenson, John↗
Flash Lidar Performance Testing: Configuration and Results
Lidar-based hazard detection and avoidance will enable safe landing in scientifically interesting terrain with higher hazard abundance. ASC GoldenEye flash lidar was tested at JPL as part of EDL technology development for Mars 2018
Lidar noise parameters↗
Rocket sled testing of a prototype terrain-relative navigation system
The next generation of Martian landers (2007 and beyond) will employ a precision soft-landing capability that will make it possible to explore previously inaccessible regions on the surface of Mars. This capability will be enabled by onboard systems that automatically identify and avoid terrain containing steep slopes or rocks exceeding a particular terrain height. JPL is currently developing such a hazard detection and avoidance system; this system will map the landing zone with a scanning laser radar, identify hazards, select a safe landing zone, and then guide the vehicle to the selected landing area. This paper describes how one component of this system-hazard detection-is being tested using a rocket sled and simulated Martian terrain.
lidar↗
Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles
This software implements a motion-planning module for a maritime autonomous surface vehicle (ASV). The module trails a given target while also avoiding static and dynamic surface hazards. When surface hazards are other moving boats, the motion planner must apply International Regulations for Avoiding Collisions at Sea (COLREGS). A key subset of these rules has been implemented in the software. In case contact with the target is lost, the software can receive and follow a "reacquisition route," provided by a complementary system, until the target is reacquired. The programmatic intention is that the trailed target is a submarine, although any mobile naval platform could serve as the target. The algorithmic approach to combining motion with a (possibly moving) goal location, while avoiding local hazards, may be applicable to robotic rovers, automated landing systems, and autonomous airships. The software operates in JPL s CARACaS (Control Architecture for Robotic Agent Command and Sensing) software architecture and relies on other modules for environmental perception data and information on the predicted detectability of the target, as well as the low-level interface to the boat controls.
Wolf, Michael↗
Hazard Boresight Relative Navigation for Safe Lunar Landing
In the area of planetary landing, hazard detection and avoidance is the act of driving a vehicle to a safe landing area using onboard resources. A hazard detection sensor is used to scan the terrain and these measurements are evaluated to determine where the safe landing sites are located. The selected site is generally not the same as the nominal target, so the vehicle must divert to the new site. This activity involves the interaction between several components, including a suite of onboard GNC algorithms that work together to efficiently choose and divert to a new site. This paper presents the Hazard Boresight Relative Navigation concept, which is a method that provides a common interface between the hazard scan, safe-site selection algorithm, size of the target-relative landing ellipse, divert offset distance and guidance targeting algorithm. After the safe-site is selected from the hazard scan, the original inertial target is replaced with a vehicle-relative target, which is initialized by a measurement from the hazard scan. The new target-relative position state is estimated over time in the navigation filter, and is fed to the guidance algorithm to perform the divert maneuver. In addition to detailing the Hazard Boresight Relative Navigation concept, this paper also presents some general landing terms that can be used in the greater discussion, as well as analysis on how to estimate and predict the vehicle footprint dispersion ellipse during flight, which is used in the safe-site selection algorithm.
Stephen R. Steffes↗
Hazard Boresight Relative Navigation for Safe Lunar Landing
In the area of planetary landing, hazard detection and avoidance is the act of driving a vehicle to a safe landing area using onboard resources. A hazard detection sensor is used to scan the terrain and these measurements are evaluated to determine where the safe landing sites are located. The selected site is generally not the same as the nominal target, so the vehicle must divert to the new site. This activity involves the interaction between several components, including a suite of onboard GNC algorithms that work together to efficiently choose and divert to a new site. This paper presents the Hazard Boresight Relative Navigation concept, which is a method that provides a common interface between the hazard scan, safe-site selection algorithm, size of the target-relative landing ellipse, divert offset distance and guidance targeting algorithm. After the safe-site is selected from the hazard scan, the original inertial target is replaced with a vehicle-relative target, which is initialized by a measurement from the hazard scan. The new target-relative position state is estimated over time in the navigation filter, and is fed to the guidance algorithm to perform the divert maneuver. In addition to detailing the Hazard Boresight Relative Navigation concept, this paper also presents some general landing terms that can be used in the greater discussion, as well as analysis on how to estimate and predict the vehicle footprint dispersion ellipse during flight, which is used in the safe-site selection algorithm.
Stephen Steffes↗
Analysis of Alerting System Failures in Commercial Aviation Accidents
The role of an alerting system is to make the system operator (e.g., pilot) aware of an impending hazard or unsafe state so the hazard can be avoided or managed successfully. A review of 46 commercial aviation accidents (between 1998 and 2014) revealed that, in the vast majority of events, either the hazard was not alerted or relevant hazard alerting occurred but failed to aid the flight crew sufficiently. For this set of events, alerting system failures were placed in one of five phases: Detection, Understanding, Action Selection, Prioritization, and Execution. This study also reviewed the evolution of alerting system schemes in commercial aviation, which revealed naive assumptions about pilot reliability in monitoring flight path parameters; specifically, pilot monitoring was assumed to be more effective than it actually is. Examples are provided of the types of alerting system failures that have occurred, and recommendations are provided for alerting system improvements.
aviation accidents↗
Lunar Excavator Mission Operations using Dynamic Movement Primitives
To support sustainable infrastructure on the Moon, NASA must leverage robots to extract lunar resources for in-situ processing and construction. As part of this effort, NASA is launching the in-situ resource utilization (ISRU) Pilot Excavator later this decade to validate a robotic regolith excavator based on the Regolith Advanced Surface Systems Operations Robot (RASSOR). RASSOR is designed to extract and transport regolith to meet the needs of ISRU architectures. During its mission, Pilot Excavator will be tasked with driving in test patterns to demonstrate the operational concept. One of these tests is a circular trajectory around the lander while avoiding miscellaneous surface hazards such as lunar rocks. To this end, we utilize dynamic movement primitives to represent navigation sequences as primitive trajectories. Here, we introduce a novel obstacle avoidance parameter, which is configured to avoid rocks throughout testing exercises. We demonstrate the effectiveness our method in a newly developed simulation tool called the Simulated Excavation Environment for Lunar Operations (SEELO) using models based on the NASA RASSOR 2.0 excavator. After making key changes to the obstacle avoidance formulation, our results show that the robot is able to safety and robustly navigate the lunar surface with densely populated rock obstacles while retaining the desired circle pattern behavior.
Space Robotics and Automation↗