Results for “Motion Capture” — Page 6

NASA NTRS2019

Using Virtual Reality for Worksite Analysis

NASA Marshall Space Flight Center (MSFC) Human Factors Engineering (HFE) Team is implementing virtual reality (VR) and motion capture (MoCap) into HFE analyses of various projects through its Virtual Environments Lab (VEL). This complements the long history of analyses completed using mockups. These techniques are being implemented for; (1) Concept of development of Deep Space Habitats (DSH), (2) Design and analyses for NASA’s Space Launch System (SLS). VR utilization in the VEL will push the design to be better formulated before mockups are constructed, saving budget and time.

Andrews, Tanya↗

NASA NTRS2020

Urban Air Mobility System Testbed Using CAVE Virtual Reality Environment

Urban Air Mobility (UAM) refers to a system of air passenger and small cargo transportation within an urban area. The UAM framework also includes other urban Unmanned Aerial Systems (UAS) services that will be supported by a mix of onboard, ground, piloted, and autonomous operations. Over the past few years UAM research has gained wide interest from companies and federal agencies as an on-demand innovative transportation option that can help reduce traffic congestion and pollution as well as increase mobility in metropolitan areas. The concepts of UAM/UAS operation in the National Airspace System (NAS) remains an active area of research to ensure safe and efficient operations. With new developments in smart vehicle design and infrastructure for air traffic management, there is a need for methods to integrate and test various components of the UAM framework. In this work, we report on the development of a virtual reality (VR) testbed using the Cave Automatic Virtual Environment (CAVE) technology for human-automation teaming and airspace operation research of UAM. Using a four-wall projection system with motion capture, the CAVE provides an immersive virtual environment with real-time full body tracking capability. We created a virtual environment consisting of San Francisco city and a vertical take-off-and-landing passenger aircraft that can fly between a downtown location and the San Francisco International Airport. The aircraft can be operated autonomously or manually by a single pilot who maneuvers the aircraft using a flight control joystick. The interior of the aircraft includes a virtual cockpit display with vehicle heading, location, and speed information. The system can record simulation events and flight data for post-processing. The system parameters are customizable for different flight scenarios; hence, the CAVE VR testbed provides a flexible method for development and evaluation of UAM framework.

Marayong, Panadda↗

NASA NTRS2021

Lunar Surface Operations Modeling Using Digital Astronaut Simulation

During Apollo, crew members experienced a number of falls while engaging in extravehicular activity. The Digital Astronaut Simulation (DAS) expanded human biomechanics modeling tools to begin investigating this prospective mission safety and success challenge for the Artemis program. A core capability was developed to detect if a motion is dynamically feasible in a given gravitational environment. Fed by motion capture and mass properties data, this technology enables observation of whether tasks performed in 1G can be performed the same way in lunar gravity or if they require modifications.

Long Duration Health↗

NASA NTRS2022

Human Stability While Exercising on a VIS Device in Zero Gravity

BACKGROUND: A Vibration Isolation and Stabilization (VIS) system is being designed for use with the European Enhanced Exploration Exercise Device (E4D) [1]. The exercise bar is attached to cables that extend and retract through openings in the E4D platform, which the subject stands on while exercising. Since the E4D is mounted on a moving VIS device, the whole system moves under the subject’s feet. While tension in the cables does help stabilize a crew member in 0g by bracing him or her against the moving platform, flexible cables do not offer full support against falling. This raises the question of whether various exercises that are successfully performed in 1g on a stationary device can be performed without losing balance in 0g on a moving device. Quantifying stability conditions and establishing stability requirements for exercise countermeasure systems is a long-standing challenge and this work helped to inform this specific need for integrated E4D/VIS flight project development. METHODS AND RESULTS: A simplified stability analysis can be attempted based on platform accelerations generated by the VIS device simulation. In this type of analysis, the subject is conceived as standing on the platform in 0g while being held down to it by the tension in the cables. If the sideways acceleration of the platform is such that the cables cannot generate a sufficient moment relative to, e.g., the heels or the toes of the subject to overcome the tipping moment from the inertial forces on the accelerated subject’s body, the subject becomes unstable. This approach, which we refer to as the ‘static’ approximation, indicated failure of all the exercises that were considered in the comprehensive VIS analysis of the E4D. It was realized, however, that platform accelerations are not externally imposed but are themselves induced by the motion of the subject’s body during exercise, and a model calculation confirmed that this drastically altered the tipping moment on the subject, with the potential to even switch the direction in which the body would tip over. This made it imperative to consider in a coupled manner both the motion of the exercising subject’s body and the induced VIS platform motion while considering stability. The coupled dynamics requirement was met by the VIS simulation incorporating time-dependent human mass properties atop the platform and driven by the inertial forces from the prescribed subject motion relative to the platform based on motion-capture recorded human trajectories in 1g on a stationary E4D [2]. To analyze simulation results, a stability criterion was also needed. We do not know how to account for the human ‘control system’ that would take visual and vestibular cues as inputs as the platform moves in 0g. We thus chose to follow an approach we had previously used to analyze the dynamic feasibility of performing a task in lunar gravity along the human body trajectory recorded in 1g [3]. In this approach, one analyzes the center of pressure (COP) between the shoes and the ground (or platform) and checks if the COP remains within the convex hull of the footprints on the ground (or platform), commonly referred to as base of support (BOS). Since pressure is vertical and, in the absence of foot restraints, positive, the COP going outside the BOS indicates that the trajectory recorded in 1g is not dynamically feasible in microgravity and/or on the moving platform of the device. The outcome of the COP-based analysis was that some of the key exercises, especially the deadlift and the back squat exercises, were found to be dynamically feasible for at least some number of the exercise cycles, this number increasing with the cable tension. While this type of stability analysis does not account for the likely alteration of the exercise trajectory from its 1g form in space, it does show that there exist at least some realistic trajectories that pass the dynamic feasibility criterion. This adds confidence that, with further adjustment by the subject of the exercise form in 0g on a moving device, a number of exercises can be performed without losing balance.

D Frenkel↗

NASA NTRSDate not supplied

Lunar Surface Mixed Reality and ARGOS Trainer

This Artemis focused Mixed Reality (MR) and ARGOS project extends the current VR/ARGOS CIF project to enhance and add VR/MR capabilities to support analysis, training and risk reduction for lunar surface EVA operations in the extreme South Pole lunar environment. This third year focused on establishing a functional trainer for crew that supports the ingress/egress of a lander as well as surface tasks such as sample collection and tool deployment and operation. Completed enhancements include improving hand tracking, the addition of supporting mixed reality surface operations, and the implementation of a higher fidelity body tracking capability through a motion capture system.

Lunar↗

NASA NTRS2023

Modeling and Simulation for Exercise Vibration Isolation and Stabilization System Design

The microgravity environment that crew members experience on orbit presents a well-known health challenge, particularly when it comes to loss of muscle and bone mass. To counteract these negative effects, exercise countermeasures play a critical role in the daily routine of the crew on the International Space Station (ISS). To help inform requirements for upcoming exploration missions such as the Gateway Program, a new device, called the European Enhanced Exploration Exercise Device (E4D), is being built by the European Space Agency through their contractor, the Danish Aerospace Company. The E4D is being demonstrated on the ISS and is unique from other current exercise devices in that it provides four separate modalities in a single device: resistive, cycle ergometry, seated aerobic rowing, and rope pulling. To support the integration of E4D on ISS, a passive Vibration Isolation and Stabilization (VIS) system was required by NASA, and this responsibility was given to the Johnson Space Center. This paper describes the end-to-end process of modeling, simulation, and analysis used to inform the mechanical design of the VIS system. The process begins with the collection of representative exerciser motion capture (MoCap) through ground-based testing with the developmental E4D in both the Prototype Immersive Technology (PIT) Laboratory and the Active Response Gravity Offload System (ARGOS) facility at the Johnson Space Center. These collected MoCap data are processed through human biomechanics modeling to create forcing functions as input to a multibody dynamics simulation of the combined E4D/VIS system, with numerous resulting outputs. These outputs include microgravity accelerations, overall system displacements, internal and transmitted loads, as well as collisions. Microgravity accelerations are compared for compliance against ISS requirements while displacements are used for sway space determinations on the design and volumetric constraints within the targeted module. Internal loads are supplied to the supporting stress analysis teams and external loads for structural loads and dynamics teams, both at NASA and ESA. Finally, contact and clearance analysis is performed using the simulation to eliminate potential design issues. To ensure that the elements of the multibody simulation were verified and validated, correlation against multiple VIS related ground hardware testbeds was performed and characterized. In addition to the isolation part of the VIS problem, stabilization is also key to the integrated performance and evaluation. Due to the difficulty in defining ISS requirements in this area, the stability of the exerciser was inspected via analysis. Loss of balance was defined analytically as occurring when the resultant force vector acting on the exerciser lies outside the base of support of the feet. Both the VIS and E4D teams have recently gone through their Critical Design Reviews (CDRs) and the iterative model-based approach has been integral to inform mechanical design, particularly in the case of the VIS. This same end-to-end approach is now being applied for the Gateway Program, where an Exploration Exercise Device (EED) derived from the E4D and notional VIS for the device are under concept development.

Countermeasures↗

NASA NTRS2023

Developing a Hybrid Spacesuit Simulator as a Research Tool for Assessing Extravehicular Activity Relevant Workload

Conducting human tests in a pressurized spacesuit is limited by availability, cost, and manpower; however, pressurized spacesuits are not always needed depending on the objectives of testing, including the development and testing of new informatics capabilities. The Human Physiology, Performance, Protection & Operations Laboratory (H-3PO) at NASA is developing a Hybrid Spacesuit Simulator (HS3) to support testing and characterization of human performance during analog planetary exploration extravehicular activities (EVAs). The goal of HS3 is to create a low-cost, modular, and unpressurized spacesuit simulator as a research tool that provides relevant physical and cognitive workload approximations with EVA-like immersion. HS3 consists of a soft outer suit, thermal control, gloves, boots, helmet, and integrated bioinformatics and communications. Baseline HS3 assessments were performed during 3-hour EVA simulations in two different subjects (DEMO1 and DEMO2) that included traverses at variable resistances and geological sampling activities. Liquid cooling garment (LCG) temperature, mean skin temperature, heart rate, motion capture, and metabolic rate were collected during each 3-hour simulated EVA. During DEMO1 and DEMO2, baseline metabolic rates at rest were 836 ± 327 BTU/hr and 869 ± 207 BTU/hr and increased to 2124 ± 548 BTU/hr and 2269 ± 559 BTU/hr, respectively, during 500m traverse. Average inlet LCG temperatures were 29.57 ± 6.62 °C and 25.63 ± 6.48 °C for DEMO1 and DEMO2 with increased outlet LCG temperatures of 33.53 ± 6.62 °C and 29.21 ± 4.79 °C, respectively. Overall, HS3 will enable future studies to characterize EVA tasks, human performance, and test future EVA capabilities in analog test environments without the need for pressurized suited environments.

Monica Hew↗

NASA NTRSDate not supplied

Coding Structures for Seated Row Simulation of an Active Controlled Vibration Isolation and Stabilization System for Astronaut’s Exercise Platform

Simulation for seated aerobic row exercise was a continued task to assist NASA in analyzing a one-dimensional vibration isolation and stabilization system for astronaut’s exercise platform. Feedback delay and signal noise were added to the simulation model. Simulation runs for this study were conducted in two software simulation tools, Trick and MBDyn, software simulation environments developed at the NASA Johnson Space Center. The exciter force in the simulation was calculated from motion capture of an exerciser during a seated aerobic row exercise. The simulation runs include passive control, active control using a Proportional, Integral, Derivative (PID) controller, and active control using a Piecewise Linear Integral Derivative (PWLID) controller. Output parameters include displacements of the exercise platform, the exerciser, and the counterweight; transmitted force to the wall of spacecraft; and actuator force to the platform. The simulation results showed excellent force reduction in the active controlled system compared to the passive controlled system, which resulted in less force reduction.

Simulation↗

NASA NTRSDate not supplied

Developing A Hybrid Spacesuit Simulator as A Research Tool for Assessing Extravehicular Activity Relevant Workload

Conducting human tests in a pressurized spacesuit is limited by availability, cost, and manpower; however, pressurized spacesuits are not always needed depending on the objectives of testing, including the development and testing of new informatics capabilities. The Human Physiology, Performance, Protection & Operations Laboratory (H-3PO) at NASA is developing a Hybrid Spacesuit Simulator (HS3) to support testing and characterization of human performance during analog planetary exploration extravehicular activities (EVAs). The goal of HS3 is to create a low-cost, modular, and unpressurized spacesuit simulator as a research tool that provides relevant physical and cognitive workload approximations with EVA-like immersion. HS3 consists of a soft outer suit, thermal control, gloves, boots, helmet, and integrated bioinformatics and communications. Baseline HS3 assessments were performed during 3-hour EVA simulations in two different subjects (DEMO1 and DEMO2) that included traverses at variable resistances and geological sampling activities. Liquid cooling garment (LCG) temperature, mean skin temperature, heart rate, motion capture, and metabolic rate were collected during each 3-hour simulated EVA. During DEMO1 and DEMO2, baseline metabolic rates at rest were 836 ± 327 BTU/hr and 869 ± 207 BTU/hr and increased to 2124 ± 548 BTU/hr and 2269 ± 559 BTU/hr, respectively, during 500m traverse. Average inlet LCG temperatures were 29.57 ± 6.62 °C and 25.63 ± 6.48 °C for DEMO1 and DEMO2 with increased outlet LCG temperatures of 33.53 ± 6.62 °C and 29.21 ± 4.79 °C, respectively. Overall, HS3 will enable future studies to characterize EVA tasks, human performance, and test future EVA capabilities in analog test environments without the need for pressurized suited environments.

Suit simulator↗

NASA NTRSDate not supplied

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

ISRU Pilot Excavator Wheel Testing in Lunar Regolith Simulant

The ISRU Pilot Excavator, or IPEx, is a robotic excavator funded by NASA’s Space Technology Mission Directorate (STMD). The Concept of Operations for IPEx involves the robot driving on the lunar surface up to 70 km at a speed of up to 30 cm/s. As such, it is critical to the mission’s success to optimize the design of the wheels for performance in lunar conditions, specifically in lunar regolith. To achieve this, an array of tests was completed to observe the effects of various wheel design choices on the driving performance of the wheels in lunar regolith simulant. In order to facilitate testing, we designed a 12” dia. configurable wheel to allow for interchangeability between various wheel formations. Two types of wheel parts were designed to be swapped: cleats, which form the tread of the wheel; and grousers, which protrude from the treads. The test variables that we considered were as follows: square vs. round wheel shape, solid vs. perforated cleats, cleat spacing, grouser height, and grouser spacing. By combining different settings of each of these test variables, ten discrete wheel designs were created and tested. The configurable test wheels were mounted on the Regolith Advanced Surface Systems Operations Robot (RASSOR) developed at NASA’s Kennedy Space Center. In our experiments, the robot was driven at a controlled speed across a prepared surface of BP-1 lunar regolith simulant. Four types of tests were conducted: circle driving, straight driving, slope driving, and drawbar pull. The driving tests were chosen to mimic a variety of conditions in which IPEx may be expected to operate, and the drawbar pull test was chosen to provide a standard of comparison with existing wheel design literature. The circle and straight driving tests were each performed at different levels: for the circle driving test, the robot was driven at a constant linear speed and three different angular speeds, while for the straight driving test, the robot was driven at three different linear speeds. The data collected from these tests included the power usage from each of the wheels, measurements of the tread patterns left in the regolith surface, and the amount of slip the wheels experienced, which was calculated using data from an OptiTrack motion capture system. From the results of these experiments, we found that certain test variables were more significant than others in determining performance for each type of test, and no single wheel design clearly outperformed the others in all areas. The details of our findings will be discussed further in this paper. This data will be utilized to inform the design of the wheels for IPEx and can provide a basis for the design of wheels for future lunar terrain vehicles.

RASSOR↗

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 NTRS1986

Satellite attitude motion models for capture and retrieval investigations

The primary purpose of this research is to provide mathematical models which may be used in the investigation of various aspects of the remote capture and retrieval of uncontrolled satellites. Emphasis has been placed on analytical models; however, to verify analytical solutions, numerical integration must be used. Also, for satellites of certain types, numerical integration may be the only practical or perhaps the only possible method of solution. First, to provide a basis for analytical and numerical work, uncontrolled satellites were categorized using criteria based on: (1) orbital motions, (2) external angular momenta, (3) internal angular momenta, (4) physical characteristics, and (5) the stability of their equilibrium states. Several analytical solutions for the attitude motions of satellite models were compiled, checked, corrected in some minor respects and their short-term prediction capabilities were investigated. Single-rigid-body, dual-spin and multi-rotor configurations are treated. To verify the analytical models and to see how the true motion of a satellite which is acted upon by environmental torques differs from its corresponding torque-free motion, a numerical simulation code was developed. This code contains a relatively general satellite model and models for gravity-gradient and aerodynamic torques. The spacecraft physical model for the code and the equations of motion are given. The two environmental torque models are described.

Cochran, John E., Jr.↗

NASA NTRS1992

Reference equations of motion for automatic rendezvous and capture

The analysis presented in this paper defines the reference coordinate frames, equations of motion, and control parameters necessary to model the relative motion and attitude of spacecraft in close proximity with another space system during the Automatic Rendezvous and Capture phase of an on-orbit operation. The relative docking port target position vector and the attitude control matrix are defined based upon an arbitrary spacecraft design. These translation and rotation control parameters could be used to drive the error signal input to the vehicle flight control system. Measurements for these control parameters would become the bases for an autopilot or feedback control system (FCS) design for a specific spacecraft.

Henderson, David M.↗

NASA NTRS1972

Computation of supersonic flow fields about bodies in coning motion using a shock-capturing finite-difference technique.

A numerical method for computing the nonlinear inviscid flow field surrounding a body performing coning motion is described. The method permits accurate computation of the aerodynamic moment due to one of the four motions characterizing an arbitrary nonplanar motion. Results of computations for a slender circular cone in coning motion are presented, and show good agreement with experiment for angles of attack up to twice the cone half angle. The computational results display significant departure of the side moment from the linear theory value with increasing angle of attack, but agree well with experimental measurements. This indicates that the initial nonlinear behavior of the aerodynamic moment is determined primarily by the inviscid flow.

Schiff, L. B.↗

NASA NTRS2005

Optimal Configuration of Human Motion Tracking Systems: A Systems Engineering Approach

Human motion tracking systems represent a crucial technology in the area of modeling and simulation. These systems, which allow engineers to capture human motion for study or replication in virtual environments, have broad applications in several research disciplines including human engineering, robotics, and psychology. These systems are based on several sensing paradigms, including electro-magnetic, infrared, and visual recognition. Each of these paradigms requires specialized environments and hardware configurations to optimize performance of the human motion tracking system. Ideally, these systems are used in a laboratory or other facility that was designed to accommodate the particular sensing technology. For example, electromagnetic systems are highly vulnerable to interference from metallic objects, and should be used in a specialized lab free of metal components.

Henderson, Steve↗

NASA NTRS1992

Model based estimation of image depth and displacement

Passive depth and displacement map determinations have become an important part of computer vision processing. Applications that make use of this type of information include autonomous navigation, robotic assembly, image sequence compression, structure identification, and 3-D motion estimation. With the reliance of such systems on visual image characteristics, a need to overcome image degradations, such as random image-capture noise, motion, and quantization effects, is clearly necessary. Many depth and displacement estimation algorithms also introduce additional distortions due to the gradient operations performed on the noisy intensity images. These degradations can limit the accuracy and reliability of the displacement or depth information extracted from such sequences. Recognizing the previously stated conditions, a new method to model and estimate a restored depth or displacement field is presented. Once a model has been established, the field can be filtered using currently established multidimensional algorithms. In particular, the reduced order model Kalman filter (ROMKF), which has been shown to be an effective tool in the reduction of image intensity distortions, was applied to the computed displacement fields. Results of the application of this model show significant improvements on the restored field. Previous attempts at restoring the depth or displacement fields assumed homogeneous characteristics which resulted in the smoothing of discontinuities. In these situations, edges were lost. An adaptive model parameter selection method is provided that maintains sharp edge boundaries in the restored field. This has been successfully applied to images representative of robotic scenarios. In order to accommodate image sequences, the standard 2-D ROMKF model is extended into 3-D by the incorporation of a deterministic component based on previously restored fields. The inclusion of past depth and displacement fields allows a means of incorporating the temporal information into the restoration process. A summary on the conditions that indicate which type of filtering should be applied to a field is provided.

Damour, Kevin T.↗

NASA NTRS1973

Certain characteristics and capture regions of nonlinear vibrating systems

Free vibrations of a system and vibrations which are multiples of them in frequency are discussed. The corresponding periodic forced vibrations of the type n/m (n is the number of periods of disturbance between periods of movement and m is the number of periods of movement in one period of disturbance), generated by a harmonic or close to harmonic disturbance, are propagated close to the corresponding curves of the free vibrations and their frequency multiples. It has been proposed that investigation of transitional modes of motion and capture regions be carried out by precise methods in phase space, with the least number of coordinates. Thus, for example, for nonautonomous second order equations (for example, the Duffing equations), in place of three variables (coordinates, velocity, phases), it is proposed to use two: velocity during transition of the coordinate through zero and phase.

Ragulskene, V. L.↗