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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 flight telerobotic servicer: NASA's first operational space robot

Alternatives to the exploration of Mars by direct human presence are under consideration by both the United States and the Soviet Union. In these concepts, autonomous surface vehicles would navigate the planet performing a variety of detailed exploratory functions such as mapping, seismic measurements, sample collection and analysis. Both of these approaches to the exploration of Mars depend to a high degree on the ability of robotic machinery to perform complex functions without real time human direction. Closer to home and in time, robotics will begin to play a role in space operations in the construction and maintenance of Space Station Freedom. The Flight Telerobotic Servicer Project is introduced as an element of the Space Station Freedom, and its objectives and some special challenges it faces are discussed.

Fuechsel, Charles F.↗

NASA NTRS1992

Characteristics and requirements of robotic manipulators for space operations

A robotic manipulator, DTF-1, developed as part of the Flight Telerobotic Servicer (FTS) project at Goddard Space Flight Center is discussed focusing on the technical, operational, and safety requirements. The DTF-1 system design, which is based on the manipulator, gripper, cameras, computer, and an operator control station incorporates the fundamental building blocks of the original FTS, the end product of which was to have been a light-weight, dexterous telerobotic device. For the first time in the history of NASA, space technology and robotics were combined to find new and unique solutions to the demanding requirements of flying a sophisticated robotic manipulator in space. DTF-1 is considered to be the prototype for all future development in space robotics.

Andary, James F.↗

DOE OSTI2025

Robotic Assembly of SRF Cavity Pair

Superconducting Radio Frequency (SRF) cavities for particle accelerators require tight tolerances, ultrahigh vacuum, and strict cleanliness during assembly. As in the semiconductor industry, defects such as particles and residues are deleterious to performance, possibly rendering a cavity unfit for use. This problem is addressed primarily through cleanroom assembly during sensitive steps and rigorous chemical processing to prevent and remove such defects. Human workers are often the largest source of contamination, even with proper gowning and practices. The semiconductor industry has long integrated robots in cleanroom operation, but this has not occurred for SRF cavity production; SRF cavities, unlike wafers, are complex shapes, require more hands-on mechanical assembly, and are low-volume production items. At Jefferson Laboratory, a co-operative robot (cobot) has been setup to overcome these problems. Cobots are safe for use alongside human workers and can integrate new tools such as a 3D camera part detection and gripper for item manipulation. Therefore, cobots represent a promising avenue for reducing particulate generated during a variety of assembly tasks. A mockup of a cavity pair and coupler was setup and the cobot programmed to automatically pick up the coupler and place on the mating cavity flange. Particle counting methods were setup to measure human vs cobot assembly particulate generation inside a cavity mockup. Other potential uses will be discussed for further improving SRF cavity assembly steps, where a cobot can replace or assist a human operator, and what potential gains are expected.

Duzik, Adam [Thomas Jefferson National Accelerator↗

NASA NTRS2008

Reactive, Safe Navigation for Lunar and Planetary Robots

When humans return to the moon, Astronauts will be accompanied by robotic helpers. Enabling robots to safely operate near astronauts on the lunar surface has the potential to significantly improve the efficiency of crew surface operations. Safely operating robots in close proximity to astronauts on the lunar surface requires reactive obstacle avoidance capabilities not available on existing planetary robots. In this paper we present work on safe, reactive navigation using a stereo based high-speed terrain analysis and obstacle avoidance system. Advances in the design of the algorithms allow it to run terrain analysis and obstacle avoidance algorithms at full frame rate (30Hz) on off the shelf hardware. The results of this analysis are fed into a fast, reactive path selection module, enforcing the safety of the chosen actions. The key components of the system are discussed and test results are presented.

Utz, Hans↗

NASA NTRSDate not supplied

Powering the Moon: From Artemis Technology Demonstrations to a Lunar Economy

The National Aeronautics and Space Administration (NASA) is working towards developing and demonstrating new technologies, capabilities, and business approaches that are needed for future human deep space exploration missions. This includes collaborating with commercial and international partners to establish the first long-term presence on the Moon under the Artemis mission. Artemis lunar surface operations begin with robotically exploring the lunar south polar region for locations suitable for harvesting lunar surface resources. Over time, activities will expand beyond robotic operations, increasing the need for highly reliable and available electrical power. Beyond Artemis, there are interests in full commercial lunar surface activities. A lunar microgrid is being proposed to deliver highly reliable and available electrical power on the lunar surface and meet the power needs. Microgrids are of interest in terrestrial applications due to their ability to integrate a variety of renewable power sources. A similar approach can be taken for the lunar surface. A lunar microgrid would offer the ability to integrate various power sources to maximize power availability, including nuclear, solar arrays, batteries, and regenerative fuel cells. Microgrids are flexible and can be designed to allow for islanded operation, where power is utilized near the loads to minimize power distribution losses, or in a power sharing mode where power is transmitted longer distances. This capability is crucial during failures where overall power availability is reduced. Microgrids will also allow for the power system to grow and evolve over time, meeting the need to expand beyond initial lunar surface activities.

Jeffrey Csank↗

NASA NTRS2005

Mars Exploration Rover mobility and robotic arm operational performance

The purpose of this paper is to describe an actual instance of a practical human-robot system used on a NASA Mars rover mission that has been underway since January 2004 involving daily intercation between humans on Earth and mobile robots on Mars.

performance assessment↗

NASA NTRS2021

Mass Inferencing Model Creation And Deployment To Lunar Excavation Robot, RASSOR

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. This research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. Radio wave propagation time to the Moon and back is ~2.56 seconds. Though teleoperation is possible with this delay, autonomous capability that enables RASSOR to plan and execute excavation missions intelligently and efficiently is preferred. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation (e.g. knowledge of whether drums are full informs the task of highest priority, whether it be continuing to dig, or returning to a processing plant to offload regolith). A configurable data reduction and analysis pipeline was created to allow for straightforward incorporation of new data, such as that from lunar excavation, to improve model performance in new environments. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All four models take in system states and output a mass prediction for each set of the robot’s bucket drums. Initial results from deployment to RASSOR and testing in a simulated lunar environment show that the models have <10% mean error during robot operation. Future work includes refinement of a model that estimates regolith mass in real-time during excavation as well as further testing of the developed models on the hardware.

ROS↗

NASA NTRS1994

Development and demonstration of a telerobotic excavation system

Oak Ridge National Laboratory is developing remote excavation technologies for the Department of Energy's Office (DOE) of Technology Development, Robotics Technology Development Program, and also for the Department of Defense (DOD) Project Manager for Ammunition Logistics. This work is being done to meet the need for remote excavation and removal of radioactive and contaminated buried waste at several DOE sites and unexploded ordnance at DOD sites. System requirements are based on the need to uncover and remove waste from burial sites in a way that does not cause unnecessary personnel exposure or additional environmental contamination. Goals for the current project are to demonstrate dexterous control of a backhoe with force feedback and to implement robotic operations that will improve productivity. The Telerobotic Small Emplacement Excavator is a prototype system that incorporates the needed robotic and telerobotic capabilities on a commercially available platform. The ability to add remote dexterous teleoperation and robotic operating modes is intended to be adaptable to other commercially available excavator systems.

Burks, Barry L.↗

NASA NTRS2011

Development of Methodologies, Metrics, and Tools for Investigating Human-Robot Interaction in Space Robotics

Human-robot systems are expected to have a central role in future space exploration missions that extend beyond low-earth orbit [1]. As part of a directed research project funded by NASA s Human Research Program (HRP), researchers at the Johnson Space Center have started to use a variety of techniques, including literature reviews, case studies, knowledge capture, field studies, and experiments to understand critical human-robot interaction (HRI) variables for current and future systems. Activities accomplished to date include observations of the International Space Station s Special Purpose Dexterous Manipulator (SPDM), Robonaut, and Space Exploration Vehicle (SEV), as well as interviews with robotics trainers, robot operators, and developers of gesture interfaces. A survey of methods and metrics used in HRI was completed to identify those most applicable to space robotics. These methods and metrics included techniques and tools associated with task performance, the quantification of human-robot interactions and communication, usability, human workload, and situation awareness. The need for more research in areas such as natural interfaces, compensations for loss of signal and poor video quality, psycho-physiological feedback, and common HRI testbeds were identified. The initial findings from these activities and planned future research are discussed. Human-robot systems are expected to have a central role in future space exploration missions that extend beyond low-earth orbit [1]. As part of a directed research project funded by NASA s Human Research Program (HRP), researchers at the Johnson Space Center have started to use a variety of techniques, including literature reviews, case studies, knowledge capture, field studies, and experiments to understand critical human-robot interaction (HRI) variables for current and future systems. Activities accomplished to date include observations of the International Space Station s Special Purpose Dexterous Manipulator (SPDM), Robonaut, and Space Exploration Vehicle (SEV), as well as interviews with robotics trainers, robot operators, and developers of gesture interfaces. A survey of methods and metrics used in HRI was completed to identify those most applicable to space robotics. These methods and metrics included techniques and tools associated with task performance, the quantification of human-robot interactions and communication, usability, human workload, and situation awareness. The need for more research in areas such as natural interfaces, compensations for loss of signal and poor video quality, psycho-physiological feedback, and common HRI testbeds were identified. The initial findings from these activities and planned future research are discussed.

Ezer, Neta↗

NASA NTRS2018

Human-Automation Allocations for Current Robotic Space Operations: Space Station Remote Manipulator System

NASA’s Human Research Program’s Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) delineates the uncertainty surrounding crew work with automation and robotics in spaceflight. HARI is concerned with detrimental effects of ineffective user interfaces, system designs and/or functional task allocation on crew performance, potentially compromising mission success and safety. This risk arises because of limited experience with complex automation and robotics in spaceflight. One key knowledge gap within the HARI risk is related to function allocation.

Chang, Mai Lee↗

NASA NTRS2013

Robotics On-Board Trainer (ROBoT)

ROBoT is an on-orbit version of the ground-based Dynamics Skills Trainer (DST) that astronauts use for training on a frequent basis. This software consists of two primary software groups. The first series of components is responsible for displaying the graphical scenes. The remaining components are responsible for simulating the Mobile Servicing System (MSS), the Japanese Experiment Module Remote Manipulator System (JEMRMS), and the H-II Transfer Vehicle (HTV) Free Flyer Robotics Operations. The MSS simulation software includes: Robotic Workstation (RWS) simulation, a simulation of the Space Station Remote Manipulator System (SSRMS), a simulation of the ISS Command and Control System (CCS), and a portion of the Portable Computer System (PCS) software necessary for MSS operations. These components all run under the CentOS4.5 Linux operating system. The JEMRMS simulation software includes real-time, HIL, dynamics, manipulator multi-body dynamics, and a moving object contact model with Tricks discrete time scheduling. The JEMRMS DST will be used as a functional proficiency and skills trainer for flight crews. The HTV Free Flyer Robotics Operations simulation software adds a functional simulation of HTV vehicle controllers, sensors, and data to the MSS simulation software. These components are intended to support HTV ISS visiting vehicle analysis and training. The scene generation software will use DOUG (Dynamic On-orbit Ubiquitous Graphics) to render the graphical scenes. DOUG runs on a laptop running the CentOS4.5 Linux operating system. DOUG is an Open GL-based 3D computer graphics rendering package. It uses pre-built three-dimensional models of on-orbit ISS and space shuttle systems elements, and provides realtime views of various station and shuttle configurations.

Johnson, Genevieve↗

NASA NTRS2013

NASA Tech Briefs, January 2013

Topics include: Single-Photon-Sensitive HgCdTe Avalanche Photodiode Detector; Surface-Enhanced Raman Scattering Using Silica Whispering-Gallery Mode Resonators; 3D Hail Size Distribution Interpolation/Extrapolation Algorithm; Color-Changing Sensors for Detecting the Presence of Hypergolic Fuels; Artificial Intelligence Software for Assessing Postural Stability; Transformers: Shape-Changing Space Systems Built with Robotic Textiles; Fibrillar Adhesive for Climbing Robots; Using Pre-Melted Phase Change Material to Keep Payloads in Space Warm for Hours without Power; Development of a Centrifugal Technique for the Microbial Bioburden Analysis of Freon (CFC-11); Microwave Sinterator Freeform Additive Construction System (MS-FACS); DSP/FPGA Design for a High-Speed Programmable S-Band Space Transceiver; On-Chip Power-Combining for High-Power Schottky Diode-Based Frequency Multipliers; FPGA Vision Data Architecture; Memory Circuit Fault Simulator; Ultra-Compact Transputer-Based Controller for High-Level, Multi-Axis Coordination; Regolith Advanced Surface Systems Operations Robot Excavator; Magnetically Actuated Seal; Hybrid Electrostatic/Flextensional Mirror for Lightweight, Large-Aperture, and Cryogenic Space Telescopes; System for Contributing and Discovering Derived Mission and Science Data; Remote Viewer for Maritime Robotics Software; Stackfile Database; Reachability Maps for In Situ Operations; JPL Space Telecommunications Radio System Operating Environment; RFI-SIM: RFI Simulation Package; ION Configuration Editor; Dtest Testing Software; IMPaCT - Integration of Missions, Programs, and Core Technologies; Integrated Systems Health Management (ISHM) Toolkit; Wind-Driven Wireless Networked System of Mobile Sensors for Mars Exploration; In Situ Solid Particle Generator; Analysis of the Effects of Streamwise Lift Distribution on Sonic Boom Signature; Rad-Tolerant, Thermally Stable, High-Speed Fiber-Optic Network for Harsh Environments; Towed Subsurface Optical Communications Buoy; High-Collection-Efficiency Fluorescence Detection Cell; Ultra-Compact, Superconducting Spectrometer-on-a-Chip at Submillimeter Wavelengths; UV Resonant Raman Spectrometer with Multi-Line Laser Excitation; Medicine Delivery Device with Integrated Sterilization and Detection; Ionospheric Simulation System for Satellite Observations and Global Assimilative Model Experiments - ISOGAME; Airborne Tomographic Swath Ice Sounding Processing System; flexplan: Mission Planning System for the Lunar Reconnaissance Orbiter; Estimating Torque Imparted on Spacecraft Using Telemetry; PowderSim: Lagrangian Discrete and Mesh-Free Continuum Simulation Code for Cohesive Soils; Multiple-Frame Detection of Subpixel Targets in Thermal Image Sequences; Metric Learning to Enhance Hyperspectral Image Segmentation; Basic Operational Robotics Instructional System; Sheet Membrane Spacesuit Water Membrane Evaporator; Advanced Materials and Manufacturing for Low-Cost, High-Performance Liquid Rocket Combustion Chambers; Motor Qualification for Long-Duration Mars Missions.

Source record↗

NASA NTRSDate not supplied

Lessons for Future In-Space Telerobotic Servicing from Robotic Refueling Mission

The Robotic Refueling Mission (RRM) was a multi-phased technology development effort by the National Aeronautics & Space Administration (NASA) and the Canadian Space Agency (CSA). The program leveraged the existing robotic systems and expertise of the International Space Station (ISS) program and the tool design and satellite servicing expertise of NASA’s Exploration & In-space Services (NExIS) Projects Division at Goddard Space Flight Center (GSFC) to evaluate new hardware and techniques for on-orbit telerobotic servicing. Between 2011 and 2021, two external ISS payloads housed over a dozen robotic tools and adapters designed to service a variety of existing and novel satellite interfaces. Robot operators at NASA’s Johnson Space Center (JSC) and CSA used the Special Purpose Dexterous Manipulator (SPDM) to retrieve and operate these tools for tasks such as cutting wires or multi-layer insulation blanketing, removing valve caps, mating electrical connectors, transferring fluids, and performing visual inspections inside a vehicle. Each phase of RRM involved years of preparation. Tool and interface designs were prototyped and evaluated using both NASA and Canadian ground robotic systems. Procedures were developed by GSFC engineers and vetted in partnership with JSC and CSA robot operators. GSFC engineers were trained to provide real-time support during on-orbit operations. These preparatory efforts and the successful on-orbit evaluations yielded an array of lessons for future in-space telerobotic missions. Designing robotic tools for the space environment requires special consideration of materials, indicators, and differences between ground and flight use cases and environments. When there is a limited window for on-orbit operations, devoting time and high-fidelity hardware to ground testing can be critical. Needs during potential troubleshooting are more essential to camera view quality, frame rate, and position requirements more than nominal operations. Detailed hardware manuals, nominal and contingency procedures, along with clearly defined operations team roles and protocols are vital for efficiency. RRM also demonstrated how the ISS can be utilized to increase the technology readiness levels required for future missions and led to additional technology partnerships between NExIS and the ISS program. The lessons from RRM are currently being applied to designs, operations concepts, and ground test methodology for missions such as On-orbit Servicing, Assembly, and Manufacturing1(OSAM-1)and Mars Sample Return.

Zakiya Tomlinson↗

NASA NTRS1985

Space teleoperation research. American Nuclear Society Executive conference: Remote operations and robotics in the nuclear industry; remote maintenance in other hostile environments

This presentation consists of four sections. The first section is a brief introduction to the NASA Space Program. The second portion summarized the results of a congressionally mandated study of automation and robotics for space station. The third portion presents a number of concepts for space teleoperator systems. The remainder of the presentation describes Langley Research Center's teleoperator/robotic research to support remote space operations.

Meintel, A. J., Jr.↗

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 NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of how much mass is in the drums, this type of high-level planning is not possible. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All take in system states, such as arm/drum positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums.1) A neural network model that takes a vector of normalized system states; 2) A model that uses the integrated power consumption of an arm-raise (normalized by velocity); 3) A model that uses average drum current over a variable length interval of the drum disengaged from the surface; and 4) A real-time estimation model that aggregates excavation drum current. The developed models run in real time, outputting predictions for the front and rear drums, timestamp of the last prediction, and total mass in RASSOR’s drums. Further testing is required to validate the arm-raise model (2), though initial tests indicate reasonable performance (<10% mean error) on the hardware. The linear fit of average drum-current model (3) had a front value of r^2=0.99 and a rear value of r^2=0.98 on the validation dataset. This model currently has the best performance on unseen data. The real time model (4) is still in development, though initial results on a small subset of the training data show that it has high accuracy in predicting the increase in mass during excavation. Though work remains to be done with deploying a high-fidelity model to the physical system that makes predictions with error below the desired threshold, the modular architecture for model development allows quick adjustment of parameters to increase model fidelity. This architecture can also be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results are promising as it has been shown that models can be developed that accurately estimate excavated regolith mass.

rassor↗

NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a mobile robotic bucket-drum excavator platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for estimating the quantity of regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete In-Situ Resource Utilization (ISRU) missions. To teleoperate or run autonomously, it is crucial for the amount of regolith mass ingested to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of the total mass in the drums, this type of high-level planning is not possible. Three distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR, none of which require modification to the hardware. All take in system states, such as arm/drum motor positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums. The developed models run in real-time, outputting predictions for the front drum mass, rear drum mass, timestamp of the last prediction, and total drum mass (sum of front and rear) in RASSOR’s drums. Models deployed to the hardware have low error (<7.5% mean error over the mass range, and <2.6% mean error when drums are more than half full) when making predictions in real-time. Our modeling approach can be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results of this work are promising and show that models can be developed to accurately estimate excavated regolith mass.

Bucket Drum Excavators↗

NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

bucket drum excavators↗