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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1989

The Goddard Space Flight Center (GSFC) robotics technology testbed

Much of the technology planned for use in NASA's Flight Telerobotic Servicer (FTS) and the Demonstration Test Flight (DTF) is relatively new and untested. To provide the answers needed to design safe, reliable, and fully functional robotics for flight, NASA/GSFC is developing a robotics technology testbed for research of issues such as zero-g robot control, dual arm teleoperation, simulations, and hierarchical control using a high level programming language. The testbed will be used to investigate these high risk technologies required for the FTS and DTF projects. The robotics technology testbed is centered around the dual arm teleoperation of a pair of 7 degree-of-freedom (DOF) manipulators, each with their own 6-DOF mini-master hand controllers. Several levels of safety are implemented using the control processor, a separate watchdog computer, and other low level features. High speed input/output ports allow the control processor to interface to a simulation workstation: all or part of the testbed hardware can be used in real time dynamic simulation of the testbed operations, allowing a quick and safe means for testing new control strategies. The NASA/National Bureau of Standards Standard Reference Model for Telerobot Control System Architecture (NASREM) hierarchical control scheme, is being used as the reference standard for system design. All software developed for the testbed, excluding some of simulation workstation software, is being developed in Ada. The testbed is being developed in phases. The first phase, which is nearing completion, and highlights future developments is described.

Schnurr, Rick↗

NASA NTRS2016

ISS Robotic Student Programming

The SPHERES facility is a set of three free-flying satellites launched in 2006. In addition to scientists and engineering, middle- and high-school students program the SPHERES during the annual Zero Robotics programming competition. Zero Robotics conducts virtual competitions via simulator and on SPHERES aboard the ISS, with students doing the programming. A web interface allows teams to submit code, receive results, collaborate, and compete in simulator-based initial rounds and semi-final rounds. The final round of each competition is conducted with SPHERES aboard the ISS. At the end of 2017 a new robotic platform called Astrobee will launch, providing new game elements and new ground support for even more student interaction.

competition↗

NASA NTRS2016

ISS Robotic Student Programming

The SPHERES (Synchronized Position Hold Engage and Reorient Experimental Satellite) facility is a set of three free-flying satellites launched in 2006. In addition to scientists and engineers, middle- and high-school students program the SPHERES during the annual Zero Robotics programming competition. Zero Robotics conducts virtual competitions via simulator and on SPHERES aboard the ISS (International Space Station), with students doing the programming. A web interface allows teams to submit code, receive results, collaborate, and compete in simulator-based initial rounds and semi-final rounds. The final round of each competition is conducted with SPHERES aboard the ISS. At the end of 2017 a new robotic platform called Astrobee will launch, providing new game elements and new ground support for even more student interaction.

competition↗

NASA NTRS1990

Workspace visualization and time-delay telerobotic operations

The paper examines the performance of telerobotic tasks where the operator and robot are physically separated, and a comunication time delay of up to several seconds between them exists. This situation is applicable to space robotic servicing-assembly-maintenance operations on low earth or geosynchronous orbits with a ground-based command station. Attention is given to two developments which address advanced time-delay teleoperations for unstructured tasks: (1) the 'phantom robot', a real-time predictive graphics simulator developed to allow teleoperator eye-to-hand coordination or robot free-space kinematics under a time delay of several seconds; and (2) shared compliance control, a modified form of automatic electromechanical impedance control employed in parallel with manual position control to permit soft contact and grasp compliance with workpiece geometry under a time delay of several seconds.

Schenker, P. S.↗

NASA NTRS2005

Return to Flight: Crew Activities Resource Reel 1 of 2

The crew of the STS-114 Discovery Mission is seen in various aspects of training for space flight. The crew activities include: 1) STS-114 Return to Flight Crew Photo Session; 2) Tile Repair Training on Precision Air Bearing Floor; 3) SAFER Tile Inspection Training in Virtual Reality Laboratory; 4) Guidance and Navigation Simulator Tile Survey Training; 5) Crew Inspects Orbital Boom and Sensor System (OBSS); 6) Bailout Training-Crew Compartment; 7) Emergency Egress Training-Crew Compartment Trainer (CCT); 8) Water Survival Training-Neutral Buoyancy Lab (NBL); 9) Ascent Training-Shuttle Motion Simulator; 10) External Tank Photo Training-Full Fuselage Trainer; 11) Rendezvous and Docking Training-Shuttle Engineering Simulator (SES) Dome; 12) Shuttle Robot Arm Training-SES Dome; 13) EVA Training Virtual Reality Lab; 14) EVA Training Neutral Buoyancy Lab; 15) EVA-2 Training-NBL; 16) EVA Tool Training-Partial Gravity Simulator; 17) Cure in Place Ablator Applicator (CIPAA) Training Glove Vacuum Chamber; 16) Crew Visit to Merritt Island Launch Area (MILA); 17) Crew Inspection-Space Shuttle Discovery; and 18) Crew Inspection-External Tank and Orbital Boom and Sensor System (OBSS). The crew are then seen answering questions from the media at the Space Shuttle Landing Facility.

Source record↗

NASA NTRS2000

Modeling and Design of an Electro-Rheological Fluid Based Haptic System for Tele-Operation of Space Robots

For many years, the robotic community sought to develop robots that can eventually operate autonomously and eliminate the need for human operators. However, there is an increasing realization that there are some tasks that human can perform significantly better but, due to associated hazards, distance, physical limitations and other causes, only robot can be employed to perform these tasks. Remotely performing these types of tasks requires operating robots as human surrogates. While current "hand master" haptic systems are able to reproduce the feeling of rigid objects, they present great difficulties in emulating the feeling of remote/virtual stiffness. In addition, they tend to be heavy, cumbersome and usually they only allow limited operator workspace. In this paper a novel haptic interface is presented to enable human-operators to "feel" and intuitively mirror the stiffness/forces at remote/virtual sites enabling control of robots as human-surrogates. This haptic interface is intended to provide human operators intuitive feeling of the stiffness and forces at remote or virtual sites in support of space robots performing dexterous manipulation tasks (such as operating a wrench or a drill). Remote applications are referred to the control of actual robots whereas virtual applications are referred to simulated operations. The developed haptic interface will be applicable to IVA operated robotic EVA tasks to enhance human performance, extend crew capability and assure crew safety. The electrically controlled stiffness is obtained using constrained ElectroRheological Fluids (ERF), which changes its viscosity under electrical stimulation. Forces applied at the robot end-effector due to a compliant environment will be reflected to the user using this ERF device where a change in the system viscosity will occur proportionally to the force to be transmitted. In this paper, we will present the results of our modeling, simulation, and initial testing of such an electrorheological fluid (ERF) based haptic device.

Mavroidis, Constantinos↗

NASA NTRS1997

Virtual Collaborative Simulation Environment for Integrated Product and Process Development

Deneb Robotics is a leader in the development of commercially available, leading edge three- dimensional simulation software tools for virtual prototyping,, simulation-based design, manufacturing process simulation, and factory floor simulation and training applications. Deneb has developed and commercially released a preliminary Virtual Collaborative Engineering (VCE) capability for Integrated Product and Process Development (IPPD). This capability allows distributed, real-time visualization and evaluation of design concepts, manufacturing processes, and total factory and enterprises in one seamless simulation environment.

Gulli, Michael A.↗

NASA NTRS1994

Control of a Serpentine Robot for Inspection Tasks

This paper presents a simple and robust kinematic control scheme for the JPL serpentine robot system. The proposed strategy is developed using the dampened-least-squares/configuration control methodology, and permits the considerable dexterity of the JPL serpentine robot to be effectively utilized for maneuvering in the congested and uncertain workspaces often encountered in inspection tasks. Computer simulation results are given for the 20 degree-of-freedom (DOF) manipulator system obtained by mounting the twelve DOF serpentine robot at the end-effector of an eight DOF Robotics Research arm/lathe-bed system. These simulations demonstrate that the proposed approach provides an effective method of controlling this complex system.

robotics simulations kinematic control serpentine ↗

NASA NTRSDate not supplied

Neo – Mars Adaptive Training Integrative Knowledge System (MATRIKS) to Improve Operational Performance and its Neural Basis for Spaceflight

With prolonged mission durations, spaceflight crews will become increasingly dependent on onboard technologies for knowledge acquisition and maintenance. It is expected that not all skills and knowledge required for these missions can be retained and retrieved based on pre-mission training alone. Limited and delayed communication will significantly constrain support from Mission Control and crews will increasingly rely on autonomous onboard technologies to successfully perform post-landing operations. With the present project we will target NASA’s particular interest in developing and assessing an adaptive, just-in-time countermeasure that will consolidate and improve skills that are most relevant to space flight operations. To achieve this aim, NASA established a Virtual NASA Specialized Center of Research (VNSCOR)referred to as “Mars Adaptive Training Integrative Knowledge System (MATRIKS)”, comprising the following three projects: (1) “Trinity–Multi-Environment Virtual Training for Long Duration Exploration Missions”, PI: A. Anderson (UC Boulder); (2) “Morpheus–A Haptic Sensory Supplement to Optimize In-Flight Adaptive Training for Human Control of Spacecraft Robotic Arms”, PI: S. Robinson, UC Davis); and the present project “Neo–Adaptive Training integrative knowledge System to Improve Operational Performance and its Neural Basis for Spaceflight” (UPenn, PI: A.C. Stahn). Neo leverages a validated workstation called 6DF that simulates a rendezvous and docking maneuver using real spacecraft flight dynamics. It is designed to (1) train and improve sensorimotor skills relevant for inflight and post-landing operational tasks; (2) feature an autonomous and adaptive training approach that does not rely on feedback from flight operations on the ground; (3) maximize the transfer of mission-relevant motor skills; (4) allow the assessment of the neural circuitry underlying the task; and (5) deliver the training in a motivating and meaningful way to astronauts. Neocomprises two overarching aims: First, we will identify the neural circuitry underlying spaceflight relevant tasks by performing a subset of the 6DFtaskduring functional magnetic resonance imaging (MRI)in a total of up to N=30 subjects with varying levels of 6DF training experience. Second, as part of the above-mentioned VNSCOR MATRIKS the proposed 6DF autonomous intelligent tutor system will be integrated in an additive manner with a haptic feedback intervention (Morpheus), and a multi-environment virtual trainer(Trinity).It is expected that Neo, Morpheus and Trinity mutually complement each other to facilitate an effective countermeasure tool to acquire and retain operational skills that are critical for exploration class missions. To assess the efficacy of this combined effort, the VNSCOR MATRIKS will collect data inN=16 crew members in one HERA campaign of 45 days duration with N=16 crew members(four missions with N=4 crew member seach).The primary goal is to identify changes in operational performance as assessed by NASA’s simulator of Canadarm2 operations, i.e., Robotic On-board Trainer (ROBoT-r) in response to MATRIKS. As part of Neo we will also identify if, and to what extent MATRIKS will promote transfer to general cognitive performance (Cognition battery), distinctive visuo-spatial tasks critical for telerobotic tasks (Spatial Cognition battery), and affect brain structural changes and the neural circuitry of key brain networks expected to be relevant for spaceflight-related performance. At the conclusion of the research, we will have defined and demonstrated the use of a neuroscience-based, adaptive training integrative knowledge system to potentially mitigate visuo-spatial and sensorimotor brain changes associated with prolonged isolation and confinement to reduce the likelihood or impact of potential decrements in human performance capabilities during long-duration space missions. The expected significance of this 4-year project relates to its relevance for facilitating effective countermeasure tools to acquire and retain operational skills that are critical for exploration class missions. This will support the development of necessary countermeasures and technologies in support of human space exploration, focusing on mitigating operational performance risks.

A C Stahn↗

NASA NTRSDate not supplied

Robotic Software Architecture for in-Space Outfitting Operations

Space exploration is expanding into longer missions, larger payloads, and more complex operations. To make these larger scale missions a reality, it is necessary to perform assembly, construction, and maintenance tasks via a robotic workforce in addition to crewed operations. While there has been significant research into in-space assembly and manufacturing, it is primarily focused on rigid structural elements, such as ISRU printing or truss construction. Outfitting tasks, such as cable routing, are a critical step to a fully operational in-space facility. This paper seeks to provide a reduced order state model and an optimized combination of state-of-the-art robotics algorithms applied to a cable routing scenario. Simulation results are expected to advance approaches to online autonomous robotic manipulation of non-rigid elements.

Amy M Quartaro↗

NASA NTRSDate not supplied

Robotic Software Architecture for In-Space Outfitting Operations

Amy Quartaro↗

NASA NTRS1999

Versatile Modeling and Simulation Techniques for Earth and Planetary Balloon Systems

Modeling and simulation of balloons and aerobots (robotic balloons) is an essential part of scientific balloon mission development and planning.

Balloon Modeling Simulation Software Design UML Ae↗

NASA NTRS1989

A design strategy for autonomous systems

Some solutions to crucial issues regarding the competent performance of an autonomously operating robot are identified; namely, that of handling multiple and variable data sources containing overlapping information and maintaining coherent operation while responding adequately to changes in the environment. Support for the ideas developed for the construction of such behavior are extracted from speculations in the study of cognitive psychology, an understanding of the behavior of controlled mechanisms, and the development of behavior-based robots in a few robot research laboratories. The validity of these ideas is supported by some simple simulation experiments in the field of mobile robot navigation and guidance.

Forster, Pete↗

NASA NTRSDate not supplied

2024 Nasa Lunabotics University Competition: Site Preparation With Bulk Regolith

Introduction: Lunabotics provides accredited institutions of higher learning students (vocational-technical, college, university) an opportunity to apply the NASA systems engineering process to design and build a prototype robot. This robot would be capable of performing the proposed operations on the Lunar surface in support of future Artemis mission goals. Lunabotics features a systems engineering design challenge to engage students in the next phase of hu-man space exploration supporting the Artemis missions. This two-semester event encourages students to design and build an autonomous or telerobotic robot designed to traverse the simulated Lunar surface and complete the assigned construction tasks. The number of teams accepted into this challenge is not predetermined but is based on the scores and overall quality of the Project Management Plans received and other factors. The culmination of the Lunabotics virtual challenge will be the design, build and operation of a functional prototype Lunar robot. Teams are required to submit the following: (1) Project Management Plan, (2) Systems Engineering Paper, a (3) STEM Engage-ment Report, and a (4) Proof of Life Video. This is an optional item, but to qualify for the grand prize a team must also submit a: (5) Presentation and Demonstration. Background: The NASA Lunabotics University Competition was first held in 2010 as a follow on to the NASA Regolith Excavation Challenge [1]. The high level of interest and participation from over 50 universities each year has led to a sustained annual competi-ion cadence: it has been held every May for the past 14 years [2,3]. Over 6,000 students have participated and been inspired to pursue Science, Technology, En-gineering and Mathematics careers (STEM). 2024 Competition: The necessary lunar surface tasks are evolving to meet the NASA Artemis Mission requirements. In the past Lunabotics challenges we gathered data to support Lunar mining for consuma-bles in the Lunar regolith. Now, in 2024, the task is to gather data on Lunar site preparation and construction by designing and building a robot that will traverse the chaotic Lunar terrain and construct a regolith-based berm. The goal is to build a berm structure which would be useful to the Artemis Mission for blast and ejecta protection during lunar landings and launches, shading cryogenic propellant tank farms, providing radiation protection around a nuclear power plant and other mission critical uses. Lunabotics will consist of three separate events this year. The first event is NASA’s Lunabotics Project Development Challenge, where teams submit various deliverables to be scored by judges. The second event will be the University of Central Florida (UCF) Lunabotics Qualification challenge, in the Exolith laboratory, where teams will put their de-signs to the test. The top ten scoring teams from the Qualification challenge are then invited to the third and final event, NASA’s Lunabotics On-Site Challenge at Kennedy Space Center in Florida. This presentation will summarize the results and lessons learned from the NASA Lunabotics University Competition held in May 2024.

Lunabotics↗

NASA NTRS2023

Designing Learning Experiences With A Low-Cost Robotic Arm

Robots have gained immense popularity in Hollywood and growth globally in both industrial manufacturing and non-manufacturing environments and applications such as healthcare, service sector, and space exploration. To date, there are several examples of simple and low-cost educational robotic platforms and commercially available platforms (e.g., Lego Mindstorms, VEX Robotics) for incorporation into existing curriculum. However, most low-cost examples require access to rapid-prototyping tools, such as 3D printers to manufacture the structure of the robot, while commercially available platforms are relatively expensive (> $1,000). Although the low-cost, open-source examples provide increased access, these examples require design and manufacturing tasks that would be considered outside the learning objectives of an upper-level robotics course and are better suited for other introductory courses. Thus, we asked, how can a robotic platform be incorporated into existing robotics curriculum to enhance students' learning experiences? To explore this research question, we introduce a low-cost (<$200), untethered, and transportable robotic platform that is easy to assemble using off-the-shelf components. This kit can be powered from a laptop computer and does not rely on access to rapid-prototyping tools such as 3D printers or laser cutters, making this a more accessible option in undergraduate engineering courses. Specifically, we aimed to investigate the design of experiential learning experiences for the mathematical modeling of the forward and inverse kinematics of a serial robotic arm that complements existing robotics curriculum. The experiential learning experience focuses on traditional written answer, simulation in MATLAB, and finally implementation on a robotic platform. Few studies examined this accessible option when evaluating experiential learning experiences that complement existing robotics curricula. To assess the impact of this robotic arm kit in an undergraduate course, we implemented an educational intervention that allowed us insight into student perceptions, takeaways on the course and activities involving the robotic arm, and the impact of the course on their career outlook when comparing activities that involved use of the robotic arm and those that did not. Details on the design, development and implementation of the learning activities is provided. Both quantitative and qualitative data were collected and analyzed. The results presented in this paper discuss students finding the learning activities on the robotic arms more helpful than those without, and that students found high value in the hands-on experiences and real-world scenarios offered by the activities using the robotic arm. Challenges to implementation of the robotic arms are discussed, including students’ prior knowledge of using robotic arms.

Eric J. Markvicka↗

NASA NTRSDate not supplied

LUNAR REGOLITH:SMALL SCALE ROBOTIC SITE PREPARATION AND GEOTECHNICAL EXPERIMENTSWITH SCOOPS

NASA’s Moon-To-Mars Planetary Autonomous Construction Technology (MMPACT) project seeks to research, develop, and demonstrate lunar surface construction capabilities. Quantification of lunar regolith’s geotechnical properties allows for effective prediction of forces and displacement during excavation and construction and is critical to facilitating regolith sintering capabilities all of which benefit lunar infrastructure plans. Knowledge of shear strength, Mohr-Coulomb cohesion, angle of internal friction, bearing strength, bulk density, etc. is needed. The use of ground-based testing of various lunar simulants with relevant hardware (e.g., robotic arm tools) enables validation of technology choices, tool paths, and lunar surface construction activities. In addition, the use of Taguchi methods will minimize the number of needed experiments to explore critical input parameters.

R. P. Mueller↗

NASA NTRSDate not supplied

Lunar Regolith: Small Scale Robotic Site Preparation and Geotechnical Experiments with Scoops

- NASA’s Moon-To-Mars Planetary Autonomous Construction Technology (MMPACT) project seeks to research, develop, and demonstrate lunar surface construction capabilities. - Quantification of lunar regolith’s geotechnical properties allows for effective prediction of forces and displacement during excavation and construction and is critical to facilitating regolith sintering capabilities all of which benefit lunar infrastructure plans. - Knowledge of shear strength, Mohr-Coulomb cohesion, angle of internal friction, bearing strength, bulk density, etc. is needed. - The use of ground-based testing of various lunar simulants with relevant hardware (e.g., robotic arm tools) enables validation of technology choices, tool paths, and lunar surface construction activities. - In addition, the use of Taguchi methods [1] will minimize the number of needed experiments to explore critical input parameters. - The Jet Propulsion Lab is preparing to fly the COLDarm payload on a CLPS lunar mission with a geotechnical measurement scoop

Regolith↗

NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗