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Modeling and Simulation of the Angel Upper Limb Offload Device: Branching Into New Methods

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch of the Software, Robotics, and Simulation Division. Previously we have shared preliminary modeling of that device and kinematics based on motion capture data. Here we present an alternative approach to determine device kinematics by calculating ANGEL component angles with an OpenSim plugin. We compare calculated angles to inverse kinematics (IK) derived ones with the goal of validating the model. This new method can be further informative for device design and analytically testing different configurations to achieve desired reduced gravity conditions (e.g., lunar gravity (Lg) or Martian gravity (Mg)). We have compared calculated angles with IK-derived angles in tests with a shirt-sleeve subject positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup and arm weights to emulate the weight of the suit sleeve as well as a suited subject in ARGOS with a Mark-III suit. A variety of upper body tasks were completed in the former and full-body tasks in the latter. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. There are four ANGEL components with a total of 5 degrees of freedom (DOFs), each component has a single DOF except for the cuff which is modeled as 2 DOFs. The sickle/yaw bracket and cuff rotation angles are determined statically based on the assumptions that the sickle will track the attachment point of the cuff and that the cuff will rotate such that the attachment point is at its highest point. The cuff tilt, linker and V-bracket angles are then determined by optimizing their positions to approach a mechanical equilibrium. The calculated linker angle is compared to three different methods of determining the linker line-of-force kinematically (from V-bracket to center-cuff, cuff highest point or marker-derived position). Given the joint angles of the device, the spring force and resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data. The average difference in angles is the smallest for the V-bracket and linker, around 1 to 5 degrees for most trials. The resulting offload and shoulder torque are comparable between calculated and IK-derived angles. In summary, we have developed a method to calculate the joint angles of an exoskeleton-like upper limb offloading device currently in development. We have also developed a custom plugin which will be a valuable tool to optimize device configurations for a desired gravitational environment, probe the offload achieved for motions recorded outside of our test suite, and inform future design improvements.

L B Nilsson

Modeling and Simulation of The Angel Upper Limb Offload Device: Branching into New Methods

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch of the Software, Robotics, and Simulation Division. Previously we have shared preliminary modeling of that device and kinematics based on motion capture data. Here we present an alternative approach to determine device kinematics by calculating ANGEL component angles with an OpenSim plugin. We compare calculated angles to inverse kinematics (IK) derived ones with the goal of validating the model. This new method can be further informative for device design and analytically testing different configurations to achieve desired reduced gravity conditions (e.g., lunar gravity (Lg) or Martian gravity (Mg)). We have compared calculated angles with IK-derived angles in tests with a shirt-sleeve subject positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup and arm weights to emulate the weight of the suit sleeve as well as a suited subject in ARGOS with a Mark-III suit. A variety of upper body tasks were completed in the former and full-body tasks in the latter. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. There are four ANGEL components with a total of 5 degrees of freedom (DOFs), each component has a single DOF except for the cuff which is modeled as 2 DOFs. The sickle/yaw bracket and cuff rotation angles are determined statically based on the assumptions that the sickle will track the attachment point of the cuff and that the cuff will rotate such that the attachment point is at its highest point. The cuff tilt, linker and V-bracket angles are then determined by optimizing their positions to approach a mechanical equilibrium. The calculated linker angle is compared to three different methods of determining the linker line-of-force kinematically (from V-bracket to center-cuff, cuff highest point or marker-derived position). Given the joint angles of the device, the spring force and resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data. The average difference in angles is the smallest for the V-bracket and linker, around 1 to 5 degrees for most trials. The resulting offload and shoulder torque are comparable between calculated and IK-derived angles. In summary, we have developed a method to calculate the joint angles of an exoskeleton-like upper limb offloading device currently in development. We have also developed a custom plugin which will be a valuable tool to optimize device configurations for a desired gravitational environment, probe the offload achieved for motions recorded outside of our test suite, and inform future design improvements.

L B Nilsson

Development of ARGOS Offloading Assessments and Methodology for Lunar EVA Simulations

The Active Response Gravity Offload System (ARGOS) at NASA Johnson Space Center (JSC) is an analog environment that can offload pressurized suited subjects at various gravity levels. The suit is suspended from a robotic overhead crane by a cable connected to the suit via a gimbal with an adjustable pivot point. There has been increased interest in providing lunar pressurized suited training at ARGOS in preparation for lunar missions. Determination of the appropriate gimbal pivot point location for a given subject is vital for a high-fidelity and functional lunar simulation. Interactions between the pivot point location and center of gravity (CG) can result in righting moments that may lead to artificially stable or unrealistically challenging configurations. Changing the pivot point location is time consuming and repeated adjustment can result in significant loss of valuable pressurized suited time. This paper aims to share the knowledge obtained from the offloading characterization efforts during pressurized suited testing at ARGOS and document the ongoing process to define an appropriate pivot point location through iterative quantitative and qualitative assessments. The human-spacesuit CG locations for the ARGOS lunar simulation were estimated using a 3D body scan and density model combined with spacesuit hardware CAD and specifications. Early pilot testing of the gimbal revealed that setting the pivot point coincident with the modeled CG location was not always possible due to the current gimbal design, and small shifts forward and aft had noticeable effects on subject stability. Fifteen subjects performed a series of CG-related tasks in the xEMU spacesuit to assess simulation acceptability. Through iterative testing, this task list evolved to streamline the process needed to efficiently identify a suitable pivot point for a given subject. The developed methodology will be critical to determine pivot point selection for astronaut training in the xEMU ARGOS environment.

Sarah L. Jarvis

Human Thermal Assessment of Traverse and Geology Task Iterations During Simulated Lunar Extravehicular Activity

Spacewalks or extravehicular activities (EVA) in microgravity are mentally and physically demanding. Current microgravity EVAs are predominantly focused on upper body tasks on engineered surfaces; however, the introduction of gravity means that crew members during future lunar EVAs will be required to perform tasks that generate full body workloads such as navigating natural lunar terrain while conducting geological sampling. To date, only 12 people have walked on the surface of the Moon resulting in limited knowledge of suited thermal regulation under lunar-relevant physical workloads. To address this gap, a study is underway to focus on spacesuit operations with simulated lunar EVA workloads. This study presents methodology for collecting standard thermal measures during suit testing. In this pilot study, two suited subjects underwent simulated lunar EVAs using the NASA Active Response Gravity Offload System (ARGOS) to simulate the effects of partial gravity. Each lunar EVA, lasting three to five hours, included various metabolically demanding EVA tasks. Subjects donned the NASA Mark III (MK III) space suit and were offloaded to 1/6th G (lunar gravity). A subset task circuit from one of these simulations replicated an EVA traverse to a lunar crater, taking a geological sample, and returning to base. The suited subject walked one 1500 m (0% grade) and three 500 m traverses at three different grades (10, 20, 30%). Between each traverse, subjects performed geology sampling tasks (0 and 10% grade). Thermal measurements included core and skin temperature, liquid cooling garment (LCG) inlet and outlet temperature, and spacesuit gas inlet and outlet temperature and humidity. Compared to baseline core temperature (S1 = 37.07±0.32 °C, S2 = 37.27±0.01 °C) and mean skin temperature (S1 = 32.38±0.34 °C, S2 = 33.62±0.03 °C), after a 1500 m traverse, each suited subject showed an increased core temperature (S1 = 37.23±0.12 °C, S2 = 37.41±0.11°C) and decreased mean skin temperature (S1 = 32.16±0.17 °C, S2 = 31.53±1.15 °C) at a delta LCG temperature (S1 = 1.86±0.24 °C, S2 = 2.20±0.76 °C) and delta suit humidity (S1 = 9.66±1.49 %, S2 = 11.50±1.58 %). Core temperature continued to increase from compounding traverse and geology tasks (S1 = 38.04±0.03 °C, S2 = 38.1±0.02 °C) accompanied by an increase in delta LCG temperature (S1 = 2.24±0.13 °C, S2 = 2.67±0.12 °C) and delta suit humidity (S1 = 28±2.42 %, S2 = 31±2.13 %). Conversely, as the circuit progressed, mean skin temperature continued to decrease due to sustained LCG heat rejection (S1 = 30.08±0.15 °C, S2 = 30.28±0.07 °C). During the simulated EVA circuit core temperature increased to elevated values and remained elevated as heat was retained while mean skin temperature decreased due to peripheral heat offloaded to the LCG. The thermal measures collected during this study provided critical heat loading dynamics during lunar EVA tasks. Including core and skin temperatures along with suited thermal measures provides a standard data collection scheme for human thermal metrics during EVA task management. Data collected in this configuration can be used to build future lunar EVA task circuits and human thermal predictions.

Bradley Hoffmann

A Preliminary Assessment of Cognition and Fatigue During Simulated Lunar Surface Extravehicular Activities

Introduction: Artemis astronauts will be required to complete more rigorous Extravehicular Activity (EVA) schedules than during ever before. While new spacesuits are designed to sustain high physical workloads during exploration EVAs (xEVA), crewmembers must also sustain cognitive performance throughout xEVA timelines. It is therefore necessary to characterize the effects of surface xEVA tasks and timelines on cognition and fatigue. Methods: This study utilized NASA Johnson Space Center’s Active Response Gravity Offload System (ARGOS) to simulate lunar gravity and assess xEVA tasks and cognitive performance. Two subjects completed two ~5-hour EVAs in a pressurized Mark III spacesuit, completing simulated lander operations, cable routing, crew rescue, geology, payload relocation, and traverses. Subjects completed two cognitive assessments (Digit-Symbol Substitution Task (DSST) and Psychomotor Vigilance Task (PVT)) before the first and after the second simulated EVA to assess effects of xEVA tasks on processing speed and vigilant attention. Additionally, sleep (e.g., quality, duration, and efficiency) was monitored (Oura Ring) for ≥7 days prior to the simulated EVAs, as well as between each EVA, to account for possible effects of sleep decrements on cognitive metrics. Results: Cognitive performance changed minimally from pre to post EVA for both DSST (response time (RT): S1 Δ129.1ms, S2 Δ40.7ms; Accuracy: S1 preEVA = 1.0, S1 postEVA = 0.98, S2 preEVA = 1.0, S2 postEVA = 1.0) and PVT (S1 PVT RT Δ17.7 ms, S2 PVT RT Δ-2.7 ms). Subjects’ sleep duration immediately prior to EVA showed minimal deviation from baseline (Δhrs; S1 preEVA1= + 0.67, S1 preEVA2 = -.03, S2 preEVA1 = - 1.1, S2 preEVA2 = -1.39) and efficiency (Δ%; S1 preEVA1 = 0.09, S1 preEVA2 = 9.54, S2 preEVA1 = 0, S2 preEVA2= 12). Notably, sleep waketime shifted earlier for one subject by ~1 hr which may have impacted performance. Conclusion: Understanding the impacts of xEVA workloads on cognitive performance will be instrumental to future exploration mission planning and success. Future work will expand the subject pool and test new spacesuit designs to better characterize cognitive performance and impacts of sleep during simulated xEVA and inform modeling and prediction capabilities for future Artemis xEVA planning.

Taylor E. Schlotman

Finite Element Analysis and Test Correlation of a 10-Meter Inflation-Deployed Solar Sail

Under the direction of the NASA In-Space Propulsion Technology Office, the team of L Garde, NASA Jet Propulsion Laboratory, Ball Aerospace, and NASA Langley Research Center has been developing a scalable solar sail configuration to address NASA's future space propulsion needs. Prior to a flight experiment of a full-scale solar sail, a comprehensive phased test plan is currently being implemented to advance the technology readiness level of the solar sail design. These tests consist of solar sail component, subsystem, and sub-scale system ground tests that simulate the vacuum and thermal conditions of the space environment. Recently, two solar sail test articles, a 7.4-m beam assembly subsystem test article and a 10-m four-quadrant solar sail system test article, were tested in vacuum conditions with a gravity-offload system to mitigate the effects of gravity. This paper presents the structural analyses simulating the ground tests and the correlation of the analyses with the test results. For programmatic risk reduction, a two-prong analysis approach was undertaken in which two separate teams independently developed computational models of the solar sail test articles using the finite element analysis software packages: NEiNastran and ABAQUS. This paper compares the pre-test and post-test analysis predictions from both software packages with the test data including load-deflection curves from static load tests, and vibration frequencies and mode shapes from vibration tests. The analysis predictions were in reasonable agreement with the test data. Factors that precluded better correlation of the analyses and the tests were uncertainties in the material properties, test conditions, and modeling assumptions used in the analyses.

Sleight, David W.

Structural Analysis of an Inflation-Deployed Solar Sail With Experimental Validation

Under the direction of the NASA In-Space Propulsion Technology Office, the team of L Garde, NASA Jet Propulsion Laboratory, Ball Aerospace, and NASA Langley Research Center has been developing a scalable solar sail configuration to address NASA s future space propulsion needs. Prior to a flight experiment of a full-scale solar sail, a comprehensive phased test plan is currently being implemented to advance the technology readiness level of the solar sail design. These tests consist of solar sail component, subsystem, and sub-scale system ground tests that simulate the vacuum and thermal conditions of the space environment. Recently, two solar sail test articles, a 7.4-m beam assembly subsystem test article and a 10-m four-quadrant solar sail system test article, were tested in vacuum conditions with a gravity-offload system to mitigate the effects of gravity. This paper presents the structural analyses simulating the ground tests and the correlation of the analyses with the test results. For programmatic risk reduction, a two-prong analysis approach was undertaken in which two separate teams independently developed computational models of the solar sail test articles using the finite element analysis software packages: NEiNastran and ABAQUS. This paper compares the pre-test and post-test analysis predictions from both software packages with the test data including load-deflection curves from static load tests, and vibration frequencies and mode shapes from structural dynamics tests. The analysis predictions were in reasonable agreement with the test data. Factors that precluded better correlation of the analyses and the tests were uncertainties in the material properties, test conditions, and modeling assumptions used in the analyses.

Sleight, David W.

Human Performance in Simulated Reduced Gravity Environments

NASA is currently designing a new space suit capable of working in deep space and on Mars. Designing a suit is very difficult and often requires trade‐offs between performance, cost, mass, and system complexity. Our current understanding of human performance in reduced gravity in a planetary environment (the moon or Mars) is limited to lunar observations, studies from the Apollo program, and recent suit tests conducted at JSC using reduced gravity simulators. This study will look at our most recent reduced gravity simulations performed on the new Active Response Gravity Offload System (ARGOS) compared to the C‐9 reduced gravity plane. Methods: Subjects ambulated in reduced gravity analogs to obtain a baseline for human performance. Subjects were tested in lunar gravity (1.6 m/sq s) and Earth gravity (9.8 m/sq s) in shirt‐sleeves. Subjects ambulated over ground at prescribed speeds on the ARGOS, but ambulated at a self‐selected speed on the C‐9 due to time limitations. Subjects on the ARGOS were given over 3 minutes to acclimate to the different conditions before data was collected. Nine healthy subjects were tested in the ARGOS (6 males, 3 females, 79.5 +/- 15.7 kg), while six subjects were tested on the C‐9 (6 males, 78.8 +/- 11.2 kg). Data was collected with an optical motion capture system (Vicon, Oxford, UK) and was analyzed using customized analysis scripts in BodyBuilder (Vicon, Oxford, UK) and MATLAB (MathWorks, Natick, MA, USA). Results: In all offloaded conditions, variation between subjects increased compared to 1‐g. Kinematics in the ARGOS at lunar gravity resembled earth gravity ambulation more closely than the C‐9 ambulation. Toe‐off occurred 10% earlier in both reduced gravity environments compared to earth gravity, shortening the stance phase. Likewise, ankle, knee, and hip angles remained consistently flexed and had reduced peaks compared to earth gravity. Ground reaction forces in lunar gravity (normalized to Earth body weight) were 0.4 +/- 0.2 on the ARGOS, but only 0.2 +/- 0.1 on the C‐9. Discussion: Gait analysis showed differences in joint kinematics and temporal‐spatial parameters between the reduced gravity simulators and with respect to earth gravity. Although most of the subjects chose a somewhat unique ambulation style as a result of learning to ambulate in a new environment, all but two were consistent with keeping an Earth‐like gait. Learning how reduced gravity affects ambulation will help NASA to determine optimal suit designs, influence mission planning, help train crew, and may shed light on the underlying methods the body uses to optimize gait for energetic efficiency. Conclusion: Kinematic and kinetic analysis demonstrated noteworthy differences between an offloaded environment and 1‐g, as would be expected. The analysis showed a trend to change the ambulation style in an offloaded environment to a rolling‐loping walk (resembling crosscountry skiing) with increased swing time. This ambulation modification, particularly in the ARGOS, indicated that the relative kinetic energy of the subject was increased, on average, per the static body weight compared to the 1‐g condition. How much of this was influenced by the active offloading of the ARGOS system is unknown.

Cowley, Matthew

Generating a Reduced Gravity Environment on Earth

The Active Response Gravity Offload System (ARGOS) is designed to simulate reduced gravity environments, such as Lunar, Martian, or microgravity using a vertical lifting hoist and horizontal motion system. Three directions of motion are provided over a 41 ft x 24 ft x 25 ft tall area. ARGOS supplies a continuous offload of a portion of a person's weight during dynamic motions such as walking, running, and jumping. The ARGOS system tracks the person's motion in the horizontal directions to maintain a vertical offload force directly above the person or payload by measuring the deflection of the cable and adjusting accordingly.

Dungan, L. K.

Modeling and Simulation Efforts to Support Improved Comfort in ARGOS

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch, and here we present preliminary modeling of that device using the open-source biomechanical tool OpenSim [1,2] with an in-house developed plugin. We analyze a series of motions performed by a single shirt-sleeved subject with goals of characterizing the device, validating the model, and predicting whether reduced gravity conditions (i.e., lunar gravity (Lg) or Martian gravity (Mg)) can be accurately simulated with the device, as well as providing comfort to the ARGOS user. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are either obtained from (1) inverse kinematics (IK) using motion capture markers on the various components of the device or (2) calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. Given the joint angles of the device, the resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) in order to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data and the forces from manual measurements of the spring both independently and integrated within the device. We found that calculated joint angles generally represent the angles measured and computed with IK, supporting a possible analysis workflow inputting human motion data and observing system behavior under varied design parameters. In two different device configurations in which the maximum applied force was 131 N, our current model accurately captured force with a difference of 2-3 N from measured loads. Though our initial test was performed with a shirt-sleeve subject, arm weights were added to emulate the weight of the suit sleeve and the subject was positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup. Arm range of motion tasks were performed outside of the HUT, inside the HUT, and inside the HUT while using the device. A variety of other upper body tasks were completed as well. In summary, we have developed a model to investigate and verify an upper limb offload device currently in development. We believe this model will be a valuable tool not only for device characterization but also to predict proper configurations to simulate Lg or Mg conditions, investigate range of motion concerns, predict limitations such as internal collisions and contacts, and inform future design improvements.

L B Nilsson

Comparison of Physical Workload Across Eva-Simulation Analog Environments: Hybrid Space Suit Simulator and Pressurized Suit Testing

NASA conducts research, testing, and training across a variety of analog environments to support characterization of human performance during Extravehicular Activities (EVAs). Time utilizing pressurized suits in an offloaded environment is both limited and expensive, making it challenging to carry out extensive research with these suits. The Human Physiology, Performance, Protection, and Operations (H-3PO) Laboratory at NASA Johnson Space Center designed a Hybrid Space Suit Simulator (HS3) as a low-cost, workload approximator and easy access research tool to provide relevant physical and cognitive workloads during simulated EVAs. A pilot study was conducted in a 1g analog environment where six healthy subjects (3 male, 3 female) underwent simulated 5-hour EVAs in the HS3. This study used a COSMED K5 portable metabolic analyzer and a Polar H10 heart rate monitor to evaluate physical workload during the EVAs. For direct comparison, EVA tasks and timelines were modeled after a similar study conducted in pressurized suits (Mark-III spacesuit, n=3 male; small xPGS spacesuit, n=3 female) at NASA’s Active Response Gravity Offload System (ARGOS) offloaded to Lunar gravity (1/6 g). The 1g HS3 data demonstrated increased metabolic rate when compared to pressurized, Lunar-offloaded suited simulated EVAs for certain tasks including the kneeling scoop (HS3: 1194±199 BTU/hr, ARGOS: 860±170 BTU/hr, p < 0.05) and 20 lb object relocation (HS3: 1651±136 BTU/hr, ARGOS: 1048±252.8 BTU/hr, p < 0.05), but it did not demonstrate any significant differences in heart rate (p > 0.05). Other simulated EVA tasks, such as a 500 m traverse (HS3: 1431±177 BTU/hr, ARGOS: 1212±294 BTU/hr, p > 0.05), showed similar workload profiles with no significant workload differences between HS3 and ARGOS. The HS3 is a useful research tool for increasing workloads in EVA research without pressurized suits, though it may overestimate workload during certain EVA tasks when used in 1g environments.

Zachary Wusk

Determination of the mass properties of a manipulator

Space applications for telerobotics requires a manipulator that is robust to the large payload variations that occur in a zero-g environment. One approach to provide the required performance for this large payload variation is to provide inertial decoupling to the controller. The equations to generate the required joint torques can be obtained in several manners but the independent parameters required to perform the calculations are difficult to obtain. This presentation consists of an overview of the inertial decoupling control system and discusses how to reduce the inertial parameter set to a minimum and obtain the required parameter set to a minimum and obtain the required parameter vector using sensed joint positions and torques. In addition, as telerobotic technology becomes more prevalent in the space environments the ability to emulate the effect of zero-g in a one-g environment is critical in learning how to perform tasks in space. To emulate the zero-g environment it is necessary to remove the effect of gravity on the manipulator by determining the feedforward joint torques. A subset of the algorithm developed to obtain the decoupling parameters is used to obtain the gravity offload parameters. These parameters are used to eliminate the effect of gravity. The algorithm is validated on Martin Marietta/NASA Langley's, 7 Degrees-Of-Freedom (DOF) Flight Telerobotic Servicer Hydraulic Manipulator Test Bed. A video portraying actual results of the algorithm is provided.

Goldenberg, Stewart

Development of an Inertial Sensor-based Methodology for Spacesuited Geology Task Assessments during Simulated Lunar Extravehicular Activities

Lunar surface exploration during Artemis missions will require the specific skill set of geology sampling. Apollo astronauts had extensive training and used specialized tools to collect lunar rocks, core samples, pebbles, sand, and dust. The inflexibility of the pressurized Apollo spacesuits forced sampling to be taken at a standstill posture. However, new exploration spacesuits are expected to incorporate advanced materials and joint bearings, allowing for greater mobility and a wider range of functional postures. Thus, science and exploration during Artemis missions will likely involve a variety of standing, squatting, and kneeling postures. In preparation for future lunar exploration missions, NASA provides geologic training to astronauts and other mission personnel. This professional training with a spacesuit in simulated lunar environments will enhance performance and reduce risk of injury to astronauts on the lunar surface. However, anecdotally, untrained or newly trained people wearing prototype planetary spacesuits have been observed to performing motions differently than a trained geologist would when conducting the same geology sampling tasks. Therefore, a tool for evaluating geology postures at extravehicular activity (EVA) training facilities becomes required. In this paper, we introduce a novel inertial measurement unit (IMU)-based method of geology task assessments in spacesuited conditions during simulated lunar EVAs. As a case study, two subjects (one geologist and one non-geologist) participated and donned the Mark III prototype planetary spacesuit during offloading with the spreader bar gimbal in NASA’s Active Response Gravity Offload System (ARGOS). For automated geology task assessments, the spacesuit was instrumented with three wireless IMUs (APDM Opal, OR, USA): one on the chest and one each on the left and right ankle bearings. Then subjects performed geology tasks using various tools (rake, trench, hammer chisel, scoop, and drive tube) for 45 minutes each. The chest IMU measured the torso tilt angle in the sagittal plane. We used an ensemble learning method with the ankle IMUs to discriminate between standing and kneeling activities. IMU data were processed using custom MATLAB (Mathworks, MA, USA) software. In our case study, the developed method was able to discriminate differences in standing and kneeling activity levels between subjects who were all highly experienced with spacesuited testing. Our preliminary data showed one subject maintained the constant and lower range of the upper body tilt angle while both standing and kneeling, while the other subject showed more variation of the upper body tilt angle and preferred bending the upper body rather than changing from standing to kneeling posture and vice versa. While geology experience may be a factor, these results need further investigation as suit sizing and ARGOS offloading configurations have been proven to have a significant influence on suited ARGOS tasks. Also, more subjects will be needed to complete these tasks for validation. IMU-based geology task assessments can provide useful information for geology training programs. Additionally, our IMU-based posture analysis can provide new insights into how to evaluate spacesuited geology task characteristics of astronauts during simulated lunar EVAs.

Kyoung Jae Kim

Plugin for Integrated Exoskeleton Simulations (PIES)

Upper extremity offload is a new capability to be developed for the Active Response Gravity Offload System (ARGOS) at the Johnson Space Center. To address the need, the Actuated Real-time Control for ARGOS Negation of Gravitational Effects on the Limbs (ARC-ANGEL) system is being designed and developed by the HumanWorks team in the Flight Systems Branch (ER3). The Plugin for Integrated Exoskeleton Simulations (PIES) is a multibody modeling and analysis capability developed by the Digital Astronaut Simulation (DAS) team in the Simulation and Graphics Branch (ER7). The C++ plugin is used in the open source biomechanics software, OpenSim (Stanford University), and integrates human multibody modeling with system dynamic modeling. The latest ‘flavor’ is the ANGEL with Passive and Powered Line of force Evaluation (APPLE) PIES.

Kaitlin Lostroscio

Safe Exploration: Sensorimotor Assessments for Early Extravehicular Activities

BACKGROUND: Artemis missions will require a new level of crew autonomy around periods of gravitational transition, where sensorimotor disturbances are at their highest. There is a need to define performance thresholds for key sensorimotor assessments that indicate when performance in early extravehicular activities (EVAs) might be impacted or unsafe. This panel presentation will discuss the development of sensorimotor assessments for determining crew preparedness of early EVAs by utilizing a novel portable sensorimotor disorientation analog and other spaceflight analogs. OVERVIEW: To define performance thresholds, a proposed set of sensorimotor assessment tasks must be validated under various spaceflight analogs. A Sensorimotor Disorientation Analog (SDA) was developed that could induce varying levels of disorientation through combined vestibular (galvanic vestibular stimulation (GVS)) and proprioceptive (weighted chest, ankles, and wrists) disruptions. The SDA was first pilot tested using subjective feedback from previously flown astronauts to determine the levels of disorientation that mimic motor performance immediately (R+0) and +24 hours (R+1) postflight. A second study was performed using healthy non-astronaut ground subjects to validate the SDA levels by comparing to astronaut postflight data. The validated SDA was utilized in a third study to map performance in the proposed set of sensorimotor assessment tasks to operational tasks. The assessment tasks were defined based on lessons learned from Apollo and subject matter experts (e.g., flight surgeons) to include the following: 1) aid in progressive adaptation to the novel gravitational environment; 2) provide opportunities to develop strategies to recover from off-nominal body positions; and 3) mimic operational tasks such that crew can self-assess their potential ability to complete their missions. This presentation will conclude with a discussion on future validation studies of the proposed assessment tasks using other spaceflight analogs such as centrifugation and gravity offload systems. DISCUSSION: Exploration class missions will require crew to be able to self-assess and treat their sensorimotor dysfunction after gravity transitions, and in off-nominal situations they may be required to perform provocative, challenging tasks soon after landing. This panel presentation will discuss current and ongoing research strategies to address the sensorimotor risk on safe exploration during Artemis missions.

Sarah Moudy

The Instrumented Walking and Turning Test to Evaluate Suited Gait Dynamics and Performance in Extravehicular Activity Training Environments

Background and aims: Walking will be required for many exploration tasks on the Moon during the Artemis program. Walking in a straight line on the confined floorspace of a testing area, and repetitive treadmill walking that requires no change in direction may not adequately reflect the balance and coordination required during ambulation. Also, performance of turning maneuvers may be affected differently in different extravehicular activity (EVA) training facilities that simulate partial gravity. For example, the Neutral Buoyancy Lab (NBL) simulates lunar gravity by adding weight to underwater subjects to alter buoyancy and achieve the equivalent ground reaction force of 1/6 of Earth’s gravity (1/6G), whereas the Active Response Gravity Offload System (ARGOS) uses a computer controlled overhead suspension system programmed to continuously offload a percentage of a subject’s weight to simulate 1/6G. The degree to which dynamic movements such as turning are comparable across these EVA training facilities has not yet been evaluated. The instrumented gait test helps NASA scientists and engineers evaluate gait dynamics and performance in suited conditions, and this test demonstrates the unique characteristics and limitations of EVA training facilities. We developed an instrumented walking and turning test using inertial measurement units (IMUs) and conducted the test at NASA’s EVA training facilities. Results were used to compare suited walking and turning characteristics in the ARGOS and the NBL. Methods: Subjects donned the Mark III space suit during offloading with the ARGOS spreader bar gimbal and donned the Z2.5 space suit while underwater in the NBL with weights and floatation added to achieve realistic suit center of gravity. The test team securely attached three Opal (APDM, OR, USA) wireless IMUs on the space suit for each test run: one on the middle of the hard upper torso, and one on the left and on the right ankle bearings. During the NBL tests, the IMUs were encased in a waterproof housing (GoPro) with foam added to create a tighter fit. At both testing facilities, 6.3 m x 1.0 m (LxW) walking lines were marked, and a cone for turning or walking around was located at the end of the walking path with another line on the other side of the cone to indicate the stopping point after walking around the cone. Under simulated 1/6G, subjects began by standing at the marked line with their arms folded across the chest, they then walked at a preferred speed along the straight walking path until they reached the end, turned 180 degrees around the cone, and finally stopped at the marked stopping point. All IMU data recorded during testing were automatically saved to the internal memory. Then, raw IMU signals were processed using custom MATLAB (Mathworks, MA, USA) code to compare gait parameters during both the walking and the turning components of the task. These parameters included time (s), speed (m/s for walking and rad/s for turning), step number (n) and walk:turn time ratio (% time spent straight walking versus turning). Results: Less time, faster gait, fewer steps, and higher walk:turn ratio during both walking and turning components were exhibited during tests performed at the ARGOS versus those performed at the NBL. During the NBL tests, the slower walking speed continued at the same rate throughout a U-shape turn. During the ARGOS tests, the subjects performed shorter and tighter turns at 4 times the speed of the NBL turns because they walked 30% faster and the vertical offloading system gave them more support. Conclusion: Our data show that the differences in walking and turning parameters during the NBL tests may be due to the high viscosity in the water environment where the motion of the lower limbs was slow and did not reach full flexion and extension. These tests improve the current knowledge of testing environments in preparation for EVAs on the lunar surface.

Kyoung Jae Kim

Selecting Tasks for Evaluating Human Performance as a Function of Gravity

A challenge in understanding human performance as a function of gravity is determining which tasks to research. Initial studies began with treadmill walking, which was easy to quantify and control. However, with the development of pressurized rovers, it is less important to optimize human performance for ambulation as rovers will likely perform gross translation for them. Future crews are likely to spend much of their extravehicular activity (EVA) performing geology, construction and maintenance type tasks, for which it is difficult to measure steady-state-workloads. To evaluate human performance in reduced gravity, we have collected metabolic, biomechanical and subjective data for different tasks at varied gravity levels. Methods: Ten subjects completed 5 different tasks including weight transfer, shoveling, treadmill walking, treadmill running and treadmill incline walking. All tasks were performed shirt-sleeved at 1-g, 3/8-g and 1/6-g. Off-loaded conditions were achieved via the Active Response Gravity Offload System. Treadmill tasks were performed for 3 minutes with reported oxygen consumption (VO2) averaged over the last 2 minutes. Shoveling was performed for 3 minutes with metabolic cost reported as ml O2 consumed per kg material shoveled. Weight transfer reports metabolic cost as liters O2 consumed to complete the task. Statistical analysis was performed via repeated measures ANOVA. Results: Statistically significant metabolic differences were noted between all 3 gravity levels for treadmill running and incline walking. For the other 3 tasks, there were significant differences between 1-g and each reduced gravity, but not between 1/6-g and 3/8-g. For weight transfer, significant differences were seen between gravities in both trial-average VO2 and time-to-completion with noted differences in strategy for task completion. Conclusion: To determine if gravity has a metabolic effect on human performance, this research may indicate that tasks should be selected that require the subject to work vertically against the force of gravity.

Norcross, J. R.