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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
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 NTRS2022

Mars 2020 Lander Vision System Flight Performance 1

The Mars 2020 Entry Descent and Landing (EDL) system delivered the Perseverance rover to the surface of Mars on February 18th, 2021. A large fraction of the Jezero Crater landing site was covered with landing hazards including cliffs, inescapable dune fields and rocks. These hazards were identified or inferred using orbital imagery before launch so that they could be avoided using Terrain Relative Navigation (TRN) which was composed of two parts: the Lander Vision System (LVS) and Safe Target Selection (STS). During EDL, the LVS successfully estimated map relative position by fusing landmarks matched between descent imagery and a map of the landing site with Inertial Measurement Unit (IMU) data. This position estimate was used by STS to identify the safest target for landing that was also reachable given fuel and other constraints. The EDL system then used the powered descent phase to retarget to this location and land safely. The overall error between the targeted location and actual landing location was 5m which was an order of magnitude less than the 60m touchdown error requirement. This paper will describe the final tests of the LVS before launch, the checkout of the LVS during operations and the LVS performance during EDL.

Zheng, Jason↗
NASA NTRS2021

Assessment of M2020 Terrain Relative Landing Accuracy: Flight Performance vs Predicts

Terrain Relative Navigation (TRN) was a critical enabling Entry, Descent, and Landing (EDL) technology that enabled Mars 2020 mission Perseverance rover to land at Jezero crater. TRN pro-vides real-time, autonomous, map-relative position determination and generates a landing target based on a priori knowledge of hazards. The required performance for TRN was to land within 60m of the selected target. The required 60m was sub-allocated to various error sources in three major categories: targeting error, knowledge error, and control error. The targeting error is the error in selecting an appropriate landing target and the knowledge of the target on the surface. It includes the Lander Vision System (LVS) position localization with respect the ground, the synchronization between the Lander Vision System measurement and the main Navigation filter, and errors associated with the LVS Reference Map and Safe Target Selec-tion (STS). The knowledge error is the contribution of knowledge growth from the synchronization with LVS to touchdown. The control error encompasses how accurately the system could stay on the desired reference trajectory. The TRN error budget uses a combination of analysis, simulation, and hardware test-ing results to bound the various error contributions obtained during the verification and validation process. This paper first presents a description the TRN system, focusing on the architecture of LVS and STS. The paper then gives detailed overview of the TRN error budget, with a description of the major error contribu-tions in each of the three categories. Next, the paper gives the results for three versions of the error budget, pre-launch, in-flight pre-landing, and post-landing. The paper compares the pre-flight analysis, the pre-landing analysis using in-flight data during cruise, to the post-landing analysis of the TRN performance. Pre-landing analysis best estimate of the landing performance was 33m, compared to the 60m require-ment. Post-landing analysis estimated a landing accuracy of 8.53m or better, much better than the 33m pre-landing estimate. The actual post-landing imagery calculated the distance of the rover to the targeted location to be 5m. The post-landing analysis closely bounds the image-based assessment of landing accu-racy, indicating the success of the error budget architecture in bounding the landing accuracy, as well as the fidelity of the simulations used to model and predict performance.

Chen, Allen↗
NASA NTRSDate not supplied

Standalone Hazard Evaluation and Refinement From Instrument Findings (S.H.E.R.I.F)

SHERIF is a novel algorithm which defines a unique, non-iterative method for the combination of LiDAR scans into a Digital Elevation Map (DEM) and the simultaneous evaluation of that DEM for Safe Site Selection (SSL) and Hazard Detection (HD). This creates a sensor independent method for a spacecraft conducting Entry Descent and Landing (EDL) operations to synthesize terrain scans and generate a more complete and evolving understanding of the landing site topography as well as the associated hazards. SHERIF aims to increase safety and mission success probability by more effectively using the data from a single sensor to increase situational awareness, knowledge of the landing site and its hazards, as well as informing a more streamlined transition from Terrain Relative Navigation (TRN) to Hazard Relative Navigation (HRN) during descent.

Hazard Detection↗
NASA NTRS2011

Toward Improved Landing Precision on Mars

Mars landers to date have flown ballistic entry trajectories with no trajectory control after the final maneuver before entry. Improvements in landing accuracies (from approx.150 km from the target for Mars Pathfinder to approx.30-40 km for MER and Phoenix) have been driven by approach navigation improvements. MSL will fly the first guided-entry trajectory to Mars, further improving accuracy to approx.10-12 km from the target.

powered descent guidance↗
NASA NTRSDate not supplied

Camera Exposure Time Determination for Artemis I Lunar Flyby

During Artemis I, a flight test was conducted using the Optical Navigation Camera to image Lunar terrain at low altitude prior to the Return Powered Flyby (RPF) burn. The vehicle descended rapidly toward the surface and transitioned over the Lunar Terminator during the time frame in which the images were to be gathered, creating challenging lighting conditions which required the development of a novel technique for exposure time determination to gather imagery of appropriate quality for post flight analysis. The resulting technique leveraged simple photometric models and simulations, as well as the spacecrafts altitude and pointing direction to determine the necessary change in exposure times over the course of the flyby, resulting in a successful flight test.

Terrain Relative Navigation↗
NASA NTRSDate not supplied

Camera Exposure Time Determination for Artemis I Lunar Flyby

During Artemis I, a flight test was conducted using the Optical Navigation Camera to image Lunar terrain at low altitude prior to the Return Powered Flyby (RPF) burn. The vehicle descended rapidly toward the surface and transitioned over the Lunar Terminator during the time frame in which the images were to be gathered, creating challenging lighting conditions which required the development of a novel technique for exposure time determination to gather imagery of appropriate quality for post flight analysis. The resulting technique leveraged simple photometric models and simulations, as well as the spacecrafts altitude and pointing direction to determine the necessary change in exposure times over the course of the flyby, resulting in a successful flight test.

Terrain Relative Navigation↗
NASA NTRSDate not supplied

Camera Exposure Time Determination for Artemis I Lunar Flyby

During Artemis I, a flight test was conducted using the Optical Navigation Camera to image Lunar terrain at low altitude prior to the Return Powered Flyby (RPF) burn. The vehicle descended rapidly toward the surface and transitioned over the Lunar Terminator during the time frame in which the images were to be gathered, creating challenging lighting conditions which required the development of a novel technique for exposure time determination to gather imagery of appropriate quality for post flight analysis. The resulting technique leveraged simple photometric models and simulations, as well as the spacecrafts altitude and pointing direction to determine the necessary change in exposure times over the course of the flyby, resulting in a successful flight test.

Terrain Relative Navigation↗
NASA NTRS2008

Pinpoint Landing Technology Assessment

This slide presentation reviews the technology developments required to achieve pinpoint landing for a Mars landing of a future unmanned vehicle. It addresses some of the challenges to achieving accurate landing (i.e., to 2-3 kilometers) of a designated landing site. The major challenge though is to reduce the possible propellant requirement to achieve this pinpoint landing capability which requires minimizing delivery error at powered descent ignition.

Mars pinpoint landing↗
NASA NTRSDate not supplied

LuNaMaps FY 2024 Annual Program Review

The LuNaMaps project seeks to advance mapping capabilities and understanding in preparation for lunar landing scenarios. In this presentation we outline the advancements made by the team over the last year.

stereophotogrammetry↗
NASA NTRSDate not supplied

Standalone Hazard Evaluation and Refinement From Instrument Findings (S.H.E.R.I.F.)

The Standalone Hazard Evaluation From Instrument Findings (SHERIF) system is a set of novel algorithms and associated framework designed to support the generation of Digital Elevation Maps (DEMs) from multiple LiDAR scans and perform Hazard Detection (HD) and Safe Site Identification (SSI) with no dependencies on other onboard systems. SHERIF can employ several techniques to perform robust 3D keypoint extraction and Point Cloud registration (PCR) on disparate LiDAR scans of a planetary surface to generate a DEM which evolves over the course of a trajectory. The framework also supports a variety of Hazard Detection and Safe Site Identification algorithms which can be applied to the evolving DEM being produced. SHERIF features a robust and modular construction, allowing the user a high degree of flexibility in selecting and implementing whichever keypoint identificaiton, PCR and HD/SSI algorithms they may prefer, while maintaining the data products and sensor independence of the core SHERIF framework. SHERIF was recently evaluated via simulation and hardware-in-the-loop experimental testing at NASA Johnson Space Center.

hazard detection↗
NASA NTRSDate not supplied

Standalone Hazard Evaluation and Refinement From Instrument Findings (S.H.E.R.I.F.)

The Standalone Hazard Evaluation From Instrument Findings (SHERIF) system is a set of novel algorithms and associated framework designed to support the generation of Digital Elevation Maps (DEMs) from multiple LiDAR scans and perform Hazard Detection (HD) and Safe Site Identification (SSI) with no dependencies on other onboard systems. SHERIF can employ several techniques to perform robust 3D keypoint extraction and Point Cloud registration (PCR) on disparate LiDAR scans of a planetary surface to generate a DEM which evolves over the course of a trajectory. The framework also supports a variety of Hazard Detection and Safe Site Identification algorithms which can be applied to the evolving DEM being produced. SHERIF features a robust and modular construction, allowing the user a high degree of flexibility in selecting and implementing whichever keypoint identificaiton, PCR and HD/SSI algorithms they may prefer, while maintaining the data products and sensor independence of the core SHERIF framework. SHERIF was recently evaluated via simulation and hardware-in-the-loop experimental testing at NASA Johnson Space Center.

hazard detection↗
NASA NTRS2020

Subscale Indoor Trajectory Testing via Six DOF Tendon-Actuated Robot

The NASA Johnson Space Center (JSC) Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) project is developing a large-scale six degree of freedom tendon-actuated robot (STAR). STAR is intended to reproduce lunar approach trajectories across subscale terrain in order to rapidly develop and test terrain relative and hazard relative navigation algorithms at low cost. NASA is interested in hosting external partners at the facility to enable them to advance their own algorithm development and testing and intends to activate the facility in Fall 2020. Contact us for more information.

Pedrotty, Samuel M.↗
NASA NTRS2011

Lidar Systems for Precision Navigation and Safe Landing on Planetary Bodies

The ability of lidar technology to provide three-dimensional elevation maps of the terrain, high precision distance to the ground, and approach velocity can enable safe landing of robotic and manned vehicles with a high degree of precision. Currently, NASA is developing novel lidar sensors aimed at needs of future planetary landing missions. These lidar sensors are a 3-Dimensional Imaging Flash Lidar, a Doppler Lidar, and a Laser Altimeter. The Flash Lidar is capable of generating elevation maps of the terrain that indicate hazardous features such as rocks, craters, and steep slopes. The elevation maps collected during the approach phase of a landing vehicle, at about 1 km above the ground, can be used to determine the most suitable safe landing site. The Doppler Lidar provides highly accurate ground relative velocity and distance data allowing for precision navigation to the landing site. Our Doppler lidar utilizes three laser beams pointed to different directions to measure line of sight velocities and ranges to the ground from altitudes of over 2 km. Throughout the landing trajectory starting at altitudes of about 20 km, the Laser Altimeter can provide very accurate ground relative altitude measurements that are used to improve the vehicle position knowledge obtained from the vehicle navigation system. At altitudes from approximately 15 km to 10 km, either the Laser Altimeter or the Flash Lidar can be used to generate contour maps of the terrain, identifying known surface features such as craters, to perform Terrain relative Navigation thus further reducing the vehicle s relative position error. This paper describes the operational capabilities of each lidar sensor and provides a status of their development. Keywords: Laser Remote Sensing, Laser Radar, Doppler Lidar, Flash Lidar, 3-D Imaging, Laser Altimeter, Precession Landing, Hazard Detection

Amzajerdian, Farzin↗
NASA NTRS2003

Light Detection and Ranging-Based Terrain Navigation: A Concept Exploration

This paper discusses the use of Airborne Light Detection And Ranging (LiDAR) equipment for terrain navigation. Airborne LiDAR is a relatively new technology used primarily by the geo-spatial mapping community to produce highly accurate and dense terrain elevation maps. In this paper, the term LiDAR refers to a scanning laser ranger rigidly mounted to an aircraft, as opposed to an integrated sensor system that consists of a scanning laser ranger integrated with Global Positioning System (GPS) and Inertial Measurement Unit (IMU) data. Data from the laser range scanner and IMU will be integrated with a terrain database to estimate the aircraft position and data from the laser range scanner will be integrated with GPS to estimate the aircraft attitude. LiDAR data was collected using NASA Dryden's DC-8 flying laboratory in Reno, NV and was used to test the proposed terrain navigation system. The results of LiDAR-based terrain navigation shown in this paper indicate that airborne LiDAR is a viable technology enabler for fully autonomous aircraft navigation. The navigation performance is highly dependent on the quality of the terrain databases used for positioning and therefore high-resolution (2 m post-spacing) data was used as the terrain reference.

Campbell, Jacob↗