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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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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Tactile Robotic Topographical Mapping Without Force or Contact Sensors

A method of topographical mapping of a local solid surface within the range of motion of a robot arm is based on detection of contact between the surface and the end effector (the fixture or tool at the tip of the robot arm). The method was conceived to enable mapping of local terrain by an exploratory robot on a remote planet, without need to incorporate delicate contact switches, force sensors, a vision system, or other additional, costly hardware. The method could also be used on Earth for determining the size and shape of an unknown surface in the vicinity of a robot, perhaps in an unanticipated situation in which other means of mapping (e.g., stereoscopic imaging or laser scanning with triangulation) are not available. The method uses control software modified to utilize the inherent capability of the robotic control system to measure the joint positions, the rates of change of the joint positions, and the electrical current demanded by the robotic arm joint actuators. The system utilizes these coordinate data and the known robot-arm kinematics to compute the position and velocity of the end effector, move the end effector along a specified trajectory, place the end effector at a specified location, and measure the electrical currents in the joint actuators. Since the joint actuator current is approximately proportional to the actuator forces and torques, a sudden rise in joint current, combined with a slowing of the joint, is a possible indication of actuator stall and surface contact. Hence, even though the robotic arm is not equipped with contact sensors, it is possible to sense contact (albeit with reduced sensitivity) as the end effector becomes stalled against a surface that one seeks to measure.

Burke, Kevin↗
NASA NTRSDate not supplied

Astrobee On-Orbit Commissioning Manuscript and Presentation

The Astrobee free flying robots operate autonomously inside the International Space Station (ISS) with oversight from a ground operator or ISS crew. They replace the Synchronized Position Hold Engage and Reorient Experimental Satellites (SPHERES) as research platforms for zero-g free-flying robotics. Astrobee can also serve as a mobile camera/sensor platform for flight and payload controllers to improve ISS operations. Development began in late 2014, and flight hardware deployed to the ISS on several launches starting from November 2018 to October 2019. Shortly after the first two robots arrived in April 2019, we began a series of commissioning activities to validate the Astrobee robots. This paper reviews the Astrobee system and describes the on-orbit commissioning activities and results.

ISS↗
NASA NTRSDate not supplied

Astrobee On-Orbit Commissioning

The Astrobee free flying robots operate autonomously inside the International Space Station (ISS) with oversight from a ground operator or ISS crew. They replace the Synchronized Position Hold Engage and Reorient Experimental Satellites (SPHERES) as research platforms for zero-g free-flying robotics. Astrobee can also serve as a mobile camera/sensor platform for flight and payload controllers to improve ISS operations. Development began in late 2014, and flight hardware deployed to the ISS on several launches starting from November 2018 to October 2019. Shortly after the first two robots arrived in April 2019, we began a series of commissioning activities to validate the Astrobee robots. This paper reviews the Astrobee system and describes the on-orbit commissioning activities and results.

ISS↗
NASA NTRSDate not supplied

Lunar In-situ Resource Utilization Concept to Reality

ISRU is a capability involving multiple elements to achieve final products (mobility, product storage and delivery, power, crew and/or robotic maintenance, etc.) ‘ISRU’ does not exist on its own. By definition, it must connect and tie to users/customers of ISRU products and services Living Off the Land: ISRU involves any hardware or operation that harnesses and utilizes ‘in-situ’ (local) resources to create products and services for robotic and human exploration. Resource Examples •Water •Oxygen •Hydrogen •Carbon •Metals •Silicon •Nitrogen •Regolith/Rock •Discarded materials Product Examples •Propellant •Life Support Consumables •Feed stock for •Additive manufacturing •Construction •Agriculture substrate and/or fertilizer

lunar↗
DOE OSTI2026

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗
NASA NTRS2016

State Estimation for Tensegrity Robots

Tensegrity robots are a class of compliant robots that have many desirable traits when designing mass efficient systems that must interact with uncertain environments. Various promising control approaches have been proposed for tensegrity systems in simulation. Unfortunately, state estimation methods for tensegrity robots have not yet been thoroughly studied. In this paper, we present the design and evaluation of a state estimator for tensegrity robots. This state estimator will enable existing and future control algorithms to transfer from simulation to hardware. Our approach is based on the unscented Kalman filter (UKF) and combines inertial measurements, ultra wideband time-of-flight ranging measurements, and actuator state information. We evaluate the effectiveness of our method on the SUPERball, a tensegrity based planetary exploration robotic prototype. In particular, we conduct tests for evaluating both the robot's success in estimating global position in relation to fixed ranging base stations during rolling maneuvers as well as local behavior due to small-amplitude deformations induced by cable actuation.

robot↗
NASA NTRSDate not supplied

Entry, Descent, and Landing GN&C System Evaluation via Cable-Driven Emulation Robotics

An innovative cable-driven parallel robot named the Six Degree-of-Freedom Tendon Actu- ated Robot (STAR), recently developed by researchers at NASA Johnson Space Center, was built to enable entry, descent, and landing (EDL) emulation experiments. Upon functional testing and system verification, STAR employed several simulated EDL trajectories to validate velocimeter LIDAR-based sensor models for cooperative terrain relative navigation applica- tions for its first testing campaign. The STAR lab also hosted researchers from Astrobotic to evaluate the real-time performance of a newly developed sensor payload, UltraNav, through hardware in-the-loop-testing (HWIL). This work introduces the STAR system along with its accompanying testing utilities and capabilities, and deliver the experimental methodology and results of test campaigns performed with the STAR facility to date.

navigation↗
NASA NTRS2016

Geocam Space: Enhancing Handheld Digital Camera Imagery from the International Space Station for Research and Applications

Handheld astronaut photography of the Earth has been collected from the International Space Station (ISS) since 2000, making it the most temporally extensive remotely sensed dataset from this unique Low Earth orbital platform. Exclusive use of digital handheld cameras to perform Earth observations from the ISS began in 2004. Nadir viewing imagery is constrained by the inclined equatorial orbit of the ISS to between 51.6 degrees North and South latitude, however numerous oblique images of land surfaces above these latitudes are included in the dataset. While unmodified commercial off-the-shelf digital cameras provide only visible wavelength, three-band spectral information of limited quality current cameras used with long (400+ mm) lenses can obtain high quality spatial information approaching 2 meters/ground pixel resolution. The dataset is freely available online at the Gateway to Astronaut Photography of Earth site (http://eol.jsc.nasa.gov), and now comprises over 2 million images. Despite this extensive image catalog, use of the data for scientific research, disaster response, commercial applications and visualizations is minimal in comparison to other data collected from free-flying satellite platforms such as Landsat, Worldview, etc. This is due primarily to the lack of fully-georeferenced data products - while current digital cameras typically have integrated GPS, this does not function in the Low Earth Orbit environment. The Earth Science and Remote Sensing (ESRS) Unit at NASA Johnson Space Center provides training in Earth Science topics to ISS crews, performs daily operations and Earth observation target delivery to crews through the Crew Earth Observations (CEO) Facility on board ISS, and also catalogs digital handheld imagery acquired from orbit by manually adding descriptive metadata and determining an image geographic centerpoint using visual feature matching with other georeferenced data, e.g. Landsat, Google Earth, etc. The lack of full geolocation information native to the data makes it difficult to integrate astronaut photographs with other georeferenced data to facilitate quantitative analysis such as urban land cover/land use classification, change detection, or geologic mapping. The manual determination of image centerpoints is both time and labor-intensive, leading to delays in releasing geolocated and cataloged data to the public, such as the timely use of data for disaster response. The GeoCam Space project was funded by the ISS Program in 2015 to develop an on-orbit hardware and ground-based software system for increasing the efficiency of geolocating astronaut photographs from the ISS (Fig. 1). The Intelligent Robotics Group at NASA Ames Research Center leads the development of both the ground and on-orbit systems in collaboration with the ESRS Unit. The hardware component consists of modified smartphone elements including cameras, central processing unit, wireless Ethernet, and an inertial measurement unit (gyroscopes/accelerometers/magnetometers) reconfigured into a compact unit that attaches to the base of the current Nikon D4 camera - and its replacement, the Nikon D5 - and connects using the standard Nikon peripheral connector or USB port. This provides secondary, side and downward facing cameras perpendicular to the primary camera pointing direction. The secondary cameras observe calibration targets with known internal X, Y, and Z position affixed to the interior of the ISS to determine the camera pose corresponding to each image frame. This information is recorded by the GeoCam Space unit and indexed for correlation to the camera time recorded for each image frame. Data - image, EXIF header, and camera pose information - is transmitted to the ground software system (GeoRef) using the established Ku-band USOS downlink system. Following integration on the ground, the camera pose information provides an initial geolocation estimate for the individual film frame. This new capability represents a significant advance in geolocation from the manual feature-matching approach for both nadir and off-nadir viewing imagery. With the initial geolocation estimate, full georeferencing of an image is completed using the rapid tie-pointing interface in GeoRef, and the resulting data is added to the Gateway to Astronaut Photography of Earth online database in both Geotiff and Keyhole Markup Language (kml) formats. The integration of the GeoRef software component of Geocam Space into the CEO image cataloging workflow is complete, and disaster response imagery acquired by the ISS crew is now fully georeferenced as a standard data product. The on-orbit hardware component (GeoSens) is in final prototyping phase, and is on-schedule for launch to the ISS in late 2016. Installation and routine use of the Geocam Space system for handheld digital camera photography from the ISS is expected to significantly improve the usefulness of this unique dataset for a variety of public- and private-sector applications.

Stefanov, William L.↗
NASA NTRS1980

Process development for automated solar cell and module production. Task 4: Automated array assembly

A process sequence which can be used in conjunction with automated equipment for the mass production of solar cell modules for terrestrial use was developed. The process sequence was then critically analyzed from a technical and economic standpoint to determine the technological readiness of certain process steps for implementation. The steps receiving analysis were: back contact metallization, automated cell array layup/interconnect, and module edge sealing. For automated layup/interconnect, both hard automation and programmable automation (using an industrial robot) were studied. The programmable automation system was then selected for actual hardware development.

Source record↗
NASA NTRS1987

Trajectory control of robot manipulators with closed-kinematic chain mechanism

The problem of Cartesian trajectory control of a closed-kinematic chain mechanism robot manipulator, recently built at CAIR to study the assembly of NASA hardware for the future Space Station, is considered. The study is performed by both computer simulation and experimentation for tracking of three different paths: a straight line, a sinusoid, and a circle. Linearization and pole placement methods are employed to design controller gains. Results show that the controllers are robust and there are good agreements between simulation and experimentation. The results also show excellent tracking quality and small overshoots.

Nguyen, Charles C.↗
NASA NTRS2011

Use of Hawaii Analog Sites for Lunar Science and In-Situ Resource Utilization

In-Situ Resource Utilization (ISRU) and lunar science share similar objectives with respect to analyzing and characterizing the physical, mineral, and volatile materials and resources at sites of robotic and human exploration. To help mature and stress instruments, technologies, and hardware and to evaluate operations and procedures, space agencies have utilized demonstrations at analog sites on Earth before use in future missions. The US National Aeronautics and Space Administration (NASA), the Canadian Space Agency (CSA), and the German Space Agency (DLR) have utilized an analog site on the slope of Mauna Kea on the Big Island of Hawaii to test ISRU and lunar science hardware and operations in two previously held analog field tests. NASA and CSA are currently planning on a 3rd analog field test to be held in June, 2012 in Hawaii that will expand upon the successes from the previous two field tests.

Sanders, G. B.↗
NASA NTRS2011

Lessons Learned for Geologic Data Collection and Sampling: Insights from the Desert RATS 2010 Geologist Crewmembers

Since 1997, Desert Research and Technology Studies (D-RATS) has conducted hardware and operations tests in the Arizona desert that advance human and robotic planetary exploration capabilities. D-RATS 2010 (8/31-9/13) simulated geologic traverses through a terrain of cinder cones, lava flows, and underlying sedimentary units using a pair of crewed rovers and extravehicular activities (EVAs) for geologic fieldwork. There were two sets of crews, each consisting of an engineer/commander and an experienced field geologist drawn from the academic community. A major objective of D-RATS was to examine the functions of a science support team, the roles of geologist crewmembers, and protocols, tools, and technologies needed for effective data collection and sample documentation. Solutions to these problems must consider how terrestrial field geology must be adapted to geologic fieldwork during EVAs

Hurtado, J. M., Jr.↗
NASA NTRS2014

Software Engineering for Human Spaceflight

The Spacecraft Software Engineering Branch of NASA Johnson Space Center (JSC) provides world‐class products, leadership, and technical expertise in software engineering, processes, technology, and systems management for human spaceflight. The branch contributes to major NASA programs (e.g. ISS, MPCV/Orion) with in‐house software development and prime contractor oversight, and maintains the JSC Engineering Directorate CMMI rating for flight software development. Software engineering teams work with hardware developers, mission planners, and system operators to integrate flight vehicles, habitats, robotics, and other spacecraft elements. They seek to infuse automation and autonomy into missions, and apply new technologies to flight processor and computational architectures. This presentation will provide an overview of key software‐related projects, software methodologies and tools, and technology pursuits of interest to the JSC Spacecraft Software Engineering Branch.

Fredrickson, Steven E.↗
NASA NTRS2015

Software Innovation in a Mission Critical Environment

Operating in mission-critical environments requires trusted solutions, and the preference for "tried and true" approaches presents a potential barrier to infusing innovation into mission-critical systems. This presentation explores opportunities to overcome this barrier in the software domain. It outlines specific areas of innovation in software development achieved by the Johnson Space Center (JSC) Engineering Directorate in support of NASA's major human spaceflight programs, including International Space Station, Multi-Purpose Crew Vehicle (Orion), and Commercial Crew Programs. Software engineering teams at JSC work with hardware developers, mission planners, and system operators to integrate flight vehicles, habitats, robotics, and other spacecraft elements for genuinely mission critical applications. The innovations described, including the use of NASA Core Flight Software and its associated software tool chain, can lead to software that is more affordable, more reliable, better modelled, more flexible, more easily maintained, better tested, and enabling of automation.

Fredrickson, Steven↗
NASA NTRS1993

Integrating Software Modules For Robot Control

Reconfigurable, sensor-based control system uses state variables in systematic integration of reusable control modules. Designed for open-architecture hardware including many general-purpose microprocessors, each having own local memory plus access to global shared memory. Implemented in software as extension of Chimera II real-time operating system. Provides transparent computing mechanism for intertask communication between control modules and generic process-module architecture for multiprocessor realtime computation. Used to control robot arm. Proves useful in variety of other control and robotic applications.

Volpe, Richard A.↗
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 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

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↗