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NASA NTRSDate not supplied

Functional Task Tests in Partial Gravity During Parabolic Flight

BACKGROUND Understanding how critical mission tasks are performed in partial gravity such as on the moon or Mars is necessary to define effective and comprehensive countermeasure strategies for preserving crew performance during exploration missions. We studied the performance of tasks such as standing, walking, and jumping during the partial gravity phases of parabolic flight. We hypothesized that the acute effects of partial gravity on vestibular, proprioceptive, and sensorimotor functions would negatively impact performance. METHODS Twelve subjects were tested over three flights of 30 parabolas each, including 10 parabolas at 0.25g, 10 parabolas at 0.5g, and 10 parabolas at 0.75g. Subjects also performed tests in 1g between parabolas. During the sit-to-stand with obstacle walk task, subjects rose from a seated position and walked as quickly as possible straight ahead towards a cone (4 m distance), walked around the cone making a 180° left turn, returned, and sat in the chair. On the way to and from the cone, subjects stepped over a 30 cm high obstacle. For the recovery from fall task, subjects lay prone for the pull-up phase and initial 10 sec of the parabola. Then they were asked to rise as quickly as possible and maintain a quiet stance for 10 sec. The tandem rail balance task involved standing with both feet on a 4.5 cm wide rail. The time ended when subjects either stepped off the rail or grabbed on to support straps. The jump down task started with the subjects standing on a 30 cm high platform, then the subjects were instructed to step off the platform, land with both feet simultaneously, and settle in a quiet stance. The cone of stability task involved subjects leaning about the ankles as far as they could in the anterior, posterior, and lateral directions without unfolding their arms or taking a step. The center of pressure distance between endpoints was calculated. Data were collected using inertial measurement units (Opal V2, APDM, Portland, OR) worn on the head and trunk, heart rate monitors (RS800CX, Polar, Kempele, Finland), and a force plate (Bertec, Columbus, OH). RESULTS Gravity level had a significant effect on performance, with the greatest changes from 1g tending to be at the 0.25g level (Table 1). Lower gravity levels were associated with increased times to complete the sit-to-stand obstacle walk task and the recovery from fall task, decreased change in heart rate during the recovery from fall task, decreased rail balance times, and increased cone of stability distance in the anterior-posterior direction. Table 1. Functional task performance at different gravity levels during parabolic flight. Measure0.25g0.5g0.75g1gp-valueSit-to-stand with obstacle walk time (sec)9.8 ±1.4*7.2 ±0.76.9 ±0.8*7.4 ±0.9<0.001Recovery from fall time to settle (sec)5.3 ± 0.9*4.6 ± 0.84.2 ± 0.64.3 ± 0.70.002Recovery from fall change in heart rate (bpm)6.0 ± 7.3*11.2 ± 6.5*14.9 ± 4.915.9 ± 6.5<0.001Rail balance with eyes open time (sec)2.7 ±0.8*4.8 ±2.16.6 ±4.78.4 ±6.70.031Rail balance with eyes closed time (sec)1.6 ±0.4*2.1 ±0.42.4 ±0.62.6 ±0.8<0.001Jump down time to settle (sec)2.1 ± 0.41.9 ± 0.42.0 ± 0.31.8 ± 0.30.328Cone of stability –anterior-posterior (cm)20.8 ±2.7*18.8 ±2.218.6 ±1.717.9 ±2.00.039Cone of stability –lateral (cm)26.8 ±6.624.4 ±2.123.0 ±2.123.8 ±2.30.215p-value: one-way repeated measures analysis of variance; *Significant pairwise difference from 1g (p<0.05). DISCUSSION These data suggest that there is a dose-response relationship between gravity level and functional task performance. The largest changes in performance were expected at the lowest gravity level (0.25g) because subjects would no longer be able to use the gravitational reference for the perception of upright. Understanding the extent of performance deficits informs the risks and design of countermeasures for exploration spaceflight missions. ACKNOWLEDGEMENT This work is supported by NASA’s Human Research Program Human Health Countermeasures Element.

T R Macaulay↗
NASA NTRS2023

Subsurface Gravimetry Using Rover IMU Navigation Systems Data

Gravimetry is a valuable analytical tool for probing density distributions in the subsurface. Extraterrestrial data is currently limited to orbital collection, restricting spatial resolution to tens to hundreds of kilometers. Therefore, surface-based gravity surveys are necessary to study the gravity field and- lateral density variations at a finer scale. Traditional gravity sensors (gravimeters) are rare on science payloads owing to their relatively high mass, fragility, and cost. Inertial measurement units (IMU); however, are included on every rover platform to perform navigation and attitude determination. This project aims to solve this issue by demonstrating the utility in recalibrating the accelerometers contained within an IMU to measure the static acceleration of gravitational fields and, by extension, gravity anomalies induced by subsurface density variations.

Chandler Lawson↗
NASA NTRSDate not supplied

Hybrid Flush and Synthetic Air Data Filter for Entry Vehicle Atmospheric State Estimation

A hybrid flush/synthetic air data sensing filter utilizing Kalman-Schmidt and Rach-Tung-Striebel smoothers is developed to obtain entry vehicle atmosphere estimates. The filter/smoother blends information from pressure sensors distributed on the heatshield with measurements of the vehicle aerodynamic forces and moments computed from mass properties and inertial measurement unit data, and prior estimates of the atmosphere. The filter produces estimates of the atmospheric conditions along the entry trajectory, and systematic error estimates to reconcile differences between the pressure and aerodynamic data sources. The filter is applied to data acquired during the Mars Science Laboratory and Mars 2020 entry, descent, and landing at Gale crater and at Jezero crater, respectively. The results show that the hybrid filter produces estimates of the freestream flight condition with lower uncertainty than either the flush or synthetic air data algorithms. The filter accomplishes this result by incorporating additional data and computing estimates of systematic error parameters in the pressure data and the aerodynamic model to further reduce the uncertainties.

Christopher D. Karlgaard↗
NASA NTRSDate not supplied

Trajectory Reconstruction of the Low-Earth Orbit Flight Test of an Inflatable Decelerator

The Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) project conducted a flight test of a 6m inflatable aeroshell. The LOFTID test article was a secondary payload on an Atlas V launcher that carried the Joint Polar Satellite System-2 (JPSS-2) as its primary payload. The vehicle launched on November 10th, 2022. After reaching orbit, the LOFTID test article inflated the aeroshell, separated from the upper stage on an entry trajectory, and entered the atmosphere to splash down in the Pacific Ocean under parachutes. The test concept of operations is shown in Figure 1. The test article was instrumented with a variety of sensors to be used for post-flight evaluation of vehicle performance. Data from one of the key sensors for trajectory reconstruction, the Inertial Measurement Unit (IMU), was not captured in the data recorder due to a malfunction. Data from the nose cone mounted Flush Air Data Sensing (FADS) system were successfully acquired. The layout of the FADS sensors and the measured pressures during atmospheric entry are shown in Figure 2. The FADS data were combined with a Newtonian flow pressure model [1, 2] to produce estimates of the atmospheric relative trajectory. A Mach number anchoring technique given in [2] was used to stabilize estimates in high speed flight conditions. Since no IMU data were available, a trajectory simulation was used to provide the Mach number time history. The resulting estimates of the atmospheric-relative trajectory are shown in Figures 3. Given the loss of the IMU data, alternate methods for trajectory reconstruction are being explored. One approach under investigation is the use of the on-board video recorder data to be analyzed to reconstruct attitude motion. This approach is currently under investigation and will be reported on in the final paper. The Newtonian flow pressure model for the FADS analysis will also be updated with a CFD-based pressure model.

Christopher D Karlgaard↗
NASA NTRSDate not supplied

Trajectory Reconstruction of the Low-Earth Orbit Flight Test of an Inflatable Decelerator

The Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) project conducted a flight test of a 6m inflatable aeroshell. The LOFTID test article was a secondary payload on an Atlas V launcher that carried the Joint Polar Satellite System-2 (JPSS-2) as its primary payload. The vehicle launched on November 10th, 2022. After reaching orbit, the LOFTID test article inflated the aeroshell, separated from the upper stage on an entry trajectory, and entered the atmosphere to splash down in the Pacific Ocean under parachutes. The test concept of operations is shown in Figure 1. The test article was instrumented with a variety of sensors to be used for post-flight evaluation of vehicle performance. Data from one of the key sensors for trajectory reconstruction, the Inertial Measurement Unit (IMU), was not captured in the data recorder due to a malfunction. Data from the nose cone mounted Flush Air Data Sensing (FADS) system were successfully acquired. The layout of the FADS sensors and the measured pressures during atmospheric entry are shown in Figure 2. The FADS data were combined with a Newtonian flow pressure model [1, 2] to produce estimates of the atmospheric relative trajectory. A Mach number anchoring technique given in [2] was used to stabilize estimates in high speed flight conditions. Since no IMU data were available, a trajectory simulation was used to provide the Mach number time history. The resulting estimates of the atmospheric-relative trajectory are shown in Figures 3. Given the loss of the IMU data, alternate methods for trajectory reconstruction are being explored. One approach under investigation is the use of the on-board video recorder data to be analyzed to reconstruct attitude motion. This approach is currently under investigation and will be reported on in the final paper. The Newtonian flow pressure model for the FADS analysis will also be updated with a CFD-based pressure model.

Christopher D. Karlgaard↗
NASA NTRSDate not supplied

Hybrid Flush and Synthetic Air Data Filter for Entry Vehicle Atmospheric State Estimation

A hybrid flush/synthetic air data sensing filter for entry vehicle atmosphere estimation is developed. The approach makes use of a Kalman-Schmidt and Rauch-Tung-Streibel smoother. The filter/smoother blends information from pressure sensors distributed on the heatshield with pseudo-measurements of the vehicle aerodynamic forces and moments computed from mass properties and inertial measurement unit data, and prior estimates of the atmosphere. The filter produces estimates of the atmospheric conditions along the entry trajectory, and systematic error estimates to reconcile differences between the pressure and aerodynamic data sources. The filter is applied to data acquired during the Mars 2020 entry, descent, and landing at Jezero crater on February 18th, 2021. The final paper will also include results from the Mars Science Laboratory entry, descent, and landing.

Chris D. Karlgaard↗
NASA NTRS2024

Surface Gravimetry Using Rover Navigation Systems

This prototype seeks to demonstrate the utility of repurposing a Micro-ElectroMechancical (MEMS) Inertial measurement Unit (IMU) to perform surface gravimetry on a rover. Gravimetry is a common analytical tool used for probing density distributions in the subsurface of a planetary body. Historically, extraterrestrial gravimetry has been confined to orbital platforms. While orbital surveys allow for the construction of global gravity models, the spatial resolution of the data is constrained by the platform’s orbital altitude and high inherent speed. Data collected at or near the surface would increase spatial resolution and allow finer-scale crustal structure to be resolved. To date, there have been only two extraterrestrial surface gravity surveys: the Apollo 17 Traverse Gravimeter Experiment and a survey using the MEMS accelerometers contained within the Curiosity rover’s IMUs. The Curiosity survey highlighted the potential of using MEMS technology to perform planetary gravimetry, albeit with lower sensitivities than traditional surface gravimeters. MEMS accelerometers are included on every rover platform as part of the IMU navigation systems. MEMS accelerometers have low mass, cost, and power requirements while being robust across a range of environments, whereas traditional gravimeters are fragile, costly, and relatively massive (≥8kg versus ≈50g for MEMS IMUs). Thus, the emergence of MEMS gravimeters provides a low-risk and cost-effective method for performing planetary surface gravimetry [3,4]. Here, we present a method to recalibrate the MEMS accelerometers in rover IMUs to collect gravimetric measurements. Such measurements could assist current and future rover missions and support wider efforts to mature MEMS gravimeters.

C S Lawson↗
NASA NTRS2024

Kinematic Sensors Evaluation for Spaceflight Exercise Data Collections

INTRODUCTION: On the International Space Station (ISS), exercise feedback from astronauts is very important to diagnose and mitigate any form-related injuries and ensure efficacious exercise prescriptions and systems. Going forward, exploration exercise efforts seek to gain further quantitative data of human and system performance. Currently, methods of collecting in-flight exercise data on the ISS are limited to marker-based motion capture (MoCap) where astronauts must wear reflective markers over their clothes and specialized cameras are used. The main objective of this work was to investigate the following alternative tracking options: markerless video-based MoCap and inertial measurement units (IMUs). These were compared against traditional marker-based MoCap to evaluate kinematic accuracy and inform feasible methods for future exercise data collections on the ISS, especially in support of future Vibration Isolation and Stabilization (VIS) system development. METHODS: Three test subjects performed a variety of flight-like resistance and aerobic exercises using the Miniature Exercise Device (MED-2), Concept-2 rowing ergometer, barbell mockup, bench (e.g., for bench press, hip thruster, and cycling), and a custom structure for dips. These were intended also to represent exercises which could be performed on the multi-modality European Enhanced Exploration Exercise Device (E4D) [1]. The marker-based MoCap data, collected through a 16-camera OptiTrack MoCap system, was regarded as the gold standard to compare the data against. Passive markers were affixed to each subject according to a modified full body Plug-in Gait marker set [2] with 46 total markers. The markerless MoCap data was collected using two GoPro Hero7 cameras and one GoPro Hero11 camera. For the IMU data, a full body set of 17 Xsens DOTs were placed on the subject: 10 upper body and 7 lower body IMUs. Biomechanical modeling and evaluation was conducted through OpenSim [3] (MoCap), OpenSense [4] (IMU), OpenCap [5] (markerless), ENABLE [6] (markerless), and other modeling software. Secondary objectives included comparing the volume of equipment, reducing mass and crew set-up time. RESULTS AND DISCUSSION: While there were issues with initial processing for the IMUs and markerless MoCap, the results aided in the understanding of each sensor, developing end-to-end processes, and identifying future needs. Some observed concerns with the markerless MoCap approaches included being cognizant of a cluttered background, number of people in field of view, camera number and placement. Some challenges with the IMUs included possible sliding, early deactivation possibly due to exercise pose, and large quantity sensor synchronization. Overall, the markerless MoCap option may be the preferred method of data collection and processing as it provides a solution for certain IMU shortcomings and may be least in equipment volume, upmass, and crew setup time. CONCLUSIONS: While this work was mainly focused on ISS data collection, these sensor data along with continued evaluation and development efforts will help to establish best methods for exercise data collection on Gateway, for other Artemis missions, and beyond. Details on the latest end-to-end processing of the data and results will be presented, along with lessons learned and recommended sensor selection and methods.

S Faragalla↗
NASA NTRSDate not supplied

Viper Science Operations: Science Traverse Planning Perspectives, Processes, and Tools.

Introduction: The NASA Volatiles Investigating Polar Exploration Rover (VIPER) launchesin late 2024 towards a landing site on Mons Mouton in the Nobile region of the Lunar South Pole (LSP). As described in other LPSC presentations [1,2,3], the primary objective of the VIPER mission is to study the composition and distribution of hydrogen-bearing and other volatiles by way of a complementary suite of payloads that the rover will carry to the Moon: three “prospecting” instruments which operate continuously while roving - the Neutron Spectrometer System (NSS), the Near InfraRed Volatiles Spectrometer System (NIRVSS), and the Mass Spectrometer observing lunar operations (MSolo). A 1-meter auguring/percussive drill called the The Regolith and Ice Drill for Exploration of New Terrains (TRIDENT) is used to bring subsurface cuttings to the surface in 10-cm increments where they are interrogated by NIRVSS and MSolo. The Visible Imaging System is comprised of eight cameras (the NavCam stereo pair mounted on the mast gimbal, the AftCam stereo pair mounted on the aft panel, and four HazCams mounted in the wheel wells) that capture grayscale visible wavelength images of the lunar environment and the rover’s upper deck. The VIPER mobility system is a four-wheel design that includes the following motorized modules: Suspension, Steering, and Drive/Propulsion. Wheel odometry and applied torque — combined with position data from rover imagery — can be used to compute assessments of ‘slip and sinkage’. Slope estimates can be computed from stereo rover imagery, as well as pitch and roll data from the IMU (Inertial Measurement Unit) and Star Tracker telemetry.

Darlene Sze Shien Lim↗
NASA NTRSDate not supplied

Results from the Helicopter Drop Test of the DAVINCI Descent Sphere

This paper summarizes the October 2023 helicopter drop test of the descent sphere of the upcoming Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging mission to Venus. The drop test met its primary objectives of recording acceleration, attitude rates, and camera data during the 30-second descent at Utah Test and Training Range. The recorded inertial measurement unit and global position sensor receiver data has allowed a six degree-of-freedom reconstruction of the vehicle position, velocity, attitude, and attitude rates, as well as derived aerodynamic coefficients. Initial comparisons show good agreement between the reconstruction and the pre-flight models of the descent sphere being used by the Venus mission. The reconstructed aerodynamic coefficients from the drop test can inform updates to the aerodynamic model to be used for the actual Venus mission.

Soumyo Dutta↗
NASA NTRSDate not supplied

Mars Sample Return Earth Entry System Helicopter Drop Test Reconstruction

The Mars Sample Return campaign conducted four successful helicopter drop tests of the Earth Entry System at the Utah Test and Training Range on October, 2023. The tests acquired data for the 52.5 deg sphere cone geometry that can be used to develop models for the terminal descent aerodynamics and flight dynamics used to model ground impact conditions. The acquired test data included both sensor data outputs from an on-board inertial measurement unit, global positioning system, and video cameras as well as atmospheric measurements from weather balloons. This data was processed using a Kalman filter/smoother to reconstruct the capsule’s trajectory and aerodynamics. An equation-error method was used to reconcile the aerodynamics by solving for a set of dispersions in the aerodynamic database that form a best-fit to the reconstructed aerodynamics. The reconstructed trajectories were compared with flight simulations generated using Program to Optimize Simulated Trajectories II. The results indicate that the simulation underpredicted the vehicle oscillation amplitudes. The reconstruction exhibits a persistent low-amplitude oscillation that does not damp out as predicted.

Chris D Karlgaard↗
NASA NTRS2024

Low-Earth Orbit Flight Test of an Inflatable Decelerator Modeling and Reconstruction

The Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) mission was a flight test performed on November 10, 2022. LOFTID is an 6 meter diameter Hypersonic Inflatable Aerodynamic Decelerator (HIAD) that is stowed for launch as a secondary payload, inflated in space, and separated from launch vehicle before conducting entry, descent, and landing (EDL).The main objective of the flight test was to demonstrate EDL at scale using HIAD technology at flight conditions relevant for future Earth and Mars missions. LOFTID successfully inflated and separated with a spin rate of 18 deg/s, landed within 1 hour on-parachute off the coast of Hawaii, and was successfully recovered. LOFTID re-entered Earth’s atmosphere at 8 km/s, achieved peak deceleration of 9 Gs and peak heat rate of 40 W/cm2, and demonstrated angle-of-attack stability throughout entirety of flight. On-board instrumentation provided flight data, which was saved onto an ejectable data recorder that was ejected at 18 km and successfully recovered. Despite the loss of inertial measurement unit data, techniques were developed to reconstruct the estimated flight performance as described in this paper. This paper presents the trajectory analysis, aerodynamics modeling, and reconstructed flight performance of the LOFTID re-entry vehicle.

Rohan G Deshmukh↗
NASA NTRSDate not supplied

Results from the Helicopter Drop Test of the DAVINCI Descent Sphere

This paper summarizes the October 2023 helicopter drop test of the descent sphere of the upcoming Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging mission to Venus. The drop test met its primary objectives of recording acceleration, attitude rates, and camera data during the 30-second descent at Utah Test and Training Range. The recorded inertial measurement unit and global position sensor receiver data has allowed a six degree-of-freedom reconstruction of the vehicle position, velocity, attitude, and attitude rates, as well as derived aerodynamic coefficients. Initial comparisons show good agreement between the reconstruction and the pre-flight models of the descent sphere being used by the Venus mission. The reconstructed aerodynamic coefficients from the drop test can inform updates to the aerodynamic model to be used for the actual Venus mission.

Soumyo Dutta↗
NASA NTRSDate not supplied

Mars Sample Return Earth Entry System Helicopter Drop Test Reconstruction

The Mars Sample Return campaign conducted four successful helicopter drop tests of the Earth Entry System at the Utah Test and Training Range on October, 2023. The tests acquired data for the 52.5 deg sphere cone geometry that can be used to develop models for the terminal descent aerodynamics and flight dynamics used to model ground impact conditions. The acquired test data included both sensor data outputs from an on-board inertial measurement unit, global positioning system, and video cameras as well as atmospheric measurements from weather balloons. This data was processed using a Kalman filter/smoother to reconstruct the capsule’s trajectory and aerodynamics. An equation-error method was used to reconcile the aerodynamics by solving for a set of dispersions in the aerodynamic database that form a best-fit to the reconstructed aerodynamics. The reconstructed trajectories were compared with flight simulations generated using Program to Optimize Simulated Trajectories II. The results indicate that the simulation underpredicted the vehicle oscillation amplitudes. The reconstruction exhibits a persistent low-amplitude oscillation that does not damp out as predicted.

Chris D Karlgaard↗
NASA NTRS2025

Functional Task Tests in Partial Gravity During Parabolic Flight

BACKGROUND Understanding how critical mission tasks are performed in partial gravity such as on the moon or Mars is necessary to define effective and comprehensive countermeasure strategies for preserving crew performance during exploration missions. We studied the performance of tasks such as standing, balancing, walking, and jumping during the partial gravity phases of parabolic flight. We hypothesized that the acute effects of partial gravity on vestibular, proprioceptive, and sensorimotor functions would negatively impact performance. METHODS Twelve subjects (6F, 6M; 40.2 ± 8.5 years) were tested over three flights of 30 parabolas each, including 10 parabolas at 0.25g, 10 parabolas at 0.5g, and 10 parabolas at 0.75g. Subjects also performed tests in 1g between parabolas. During the seat egress and walk task, subjects rose from a seated position and walked as quickly as possible straight ahead towards a cone (4 m distance), stepped over a 30 cm high obstacle, walked around the cone making a 180° left turn, returned to the chair, and sat down in the chair. Other tasks included a tandem stance on rails, jump down from a 30cm platform, recovery from fall (prone to stand), and limits of stability tasks. Data were collected using inertial measurement units (Opal V2, APDM, Portland, OR) worn on the head and trunk, heart rate monitors (Polar, Finland), and a force plate (Bertec, Columbus, OH). During the jump down and limits of stability tasks, falls were recorded if subjects took extra steps, lifted their heels/toes, or used their arms to recover balance. RESULTS Gravity level had a significant effect on performance, with the greatest changes from 1g tending to be at the 0.25g level (Table 1). Lower gravity levels were associated with increased times to complete the seat egress and walk task and the recovery from fall task, increased head-trunk coordination, decreased tandem stance rail balance times, decreased change in heart rate during the recovery from fall task, and increased cone of stability distance in the anterior-posterior direction. In addition, there were significantly more falls recorded at the lower gravity levels: 31 falls at 0.25g, 14 falls at 0.5g, 6 falls at 0.75g, and 6 falls at 1g. DISCUSSION These data suggest that there is a dose-response relationship between gravity level and functional task performance. The largest changes in performance were expected at the lowest gravity level (0.25g) because subjects would no longer be able to use the gravitational reference for the perception of upright. Understanding the extent of performance deficits informs the risks and design of countermeasures for exploration spaceflight missions.

T R Macaulay↗
NASA NTRS2025

Orion Hardware In The Loop OIMU Stimulation Latency Effect on Navigation State Estimation

Because Hardware In The Loop (HITL) testing involves the integration of flight software and flight hardware on the ground, non-flight-like effects may arise. One of these non-flight-like effects includes Inertial Measurement Unit (IMU) stimulation latency that affects the time in which the measurement is received by the Extended Kalman Filter (EKF). This paper seeks to present the extent to which this stimulation latency affects the navigational state estimate from the Orion navigation system for all phases of flight for Artemis II.

Christopher A Ertl↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

Orion Hardware In The Loop OIMU Stimulation Latency Effect on Navigation State Estimation

Because Hardware In The Loop (HITL) testing involves the integration of flight software and flight hardware on the ground, non-flight-like effects may arise. One of these non-flight-like effects includes Inertial Measurement Unit (IMU) stimulation latency that affects the time in which the measurement is received by the Extended Kalman Filter (EKF). This paper seeks to present the extent to which this stimulation latency affects the navigational state estimate from the Orion navigation system for all phases of flight for Artemis II.

Christopher A Ertl↗