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At least 91 records · Page 5

Synthetic Data Generation for 3D Mesh Prediction and Spatial Reasoning During Multi-Agent Robotic Missions

In-space assembly operations require accurate reasoning over the pose, location, and structural organization of both the autonomous agents and assembly materials. In a full six-degree-of-freedom space, an accurate understanding of the full three-dimensional structure of the object of interest greatly enriches information for pose estimation and collision planning. Current methods of predicting pose estimation require a priori understanding of the shape of the object. Additionally, visual information in the space environment is impacted by variations in contrast and illumination. Using synthetic data allows us to rapidly generate large datasets with in varying environments and lighting conditions.This work details the generation of synthetic data used to explore the use of a region-based convolutional neural networks to detect objects of interest and predict a voxel-based three-dimensional mesh in order to understand their full three-dimensional shape. This mesh provides useful spatial information during in-space assembly operations without requiring either the complexity of maintaining models over the progress of building an object or observations from multiple angles. The generated meshes are then compared to that of ground truth in order to measure its performance.

synthetic data↗

Synthetic Data Generation for 3D Mesh Prediction and Spatial Reasoning During Multi-Agent Robotic Missions

In-space assembly operations require accurate reasoning over the pose, location, and structural organization of both the autonomous agents and assembly materials. In a full six-degree-of-freedom space, an accurate understanding of the full three-dimensional structure of the object of interest greatly enriches information for pose estimation and collision planning. Current methods of predicting pose estimation require a priori understanding of the shape of the object. Additionally, visual information in the space environment is impacted by variations in contrast and illumination. Using synthetic data allows us to rapidly generate large datasets with in varying environments and lighting conditions. This work details the generation of synthetic data used to explore the use of a region-based convolutional neural networks to detect objects of interest and predict a voxel-based three-dimensional mesh in order to understand their full three-dimensional shape. This mesh provides useful spatial information during in-space assembly operations without requiring either the complexity of maintaining models over the progress of building an object or observations from multiple angles. The generated meshes are then compared to that of ground truth in order to measure its performance.

James Ecker↗

Assessment of Sensor Data Accuracy within Gazebo/ROS for High-Precision Autonomous In-Space Robotic Operations

Modeling high-precision in-space servicing, assembly, and manufacturing operations in a simulated environment is a critical step in the development of robotic systems that will be used to autonomously assemble large-scale structures in space. Limited facility size and high costs for manufacturing prototypes make it challenging to conduct full-scale operational testing under appropriate environmental conditions; therefore, testing in a modular, high-fidelity simulation environment is necessary for verification and validation of technology and architecture designs prior to launch. Several modeling and simulation environments exist both within NASA and industry that can be used to test robotic system design and operations, including the widely used commercial tool Gazebo integrated with Robotic Operating System software. Because the performance of autonomous robotic systems relies heavily on the quality of sensor input data, this paper focuses on assessing the accuracy of pose data from an optical sensor model in the Gazebo environment against the behavior of real hardware. The results of the tests will help developers using Gazebo for large-scale, high-precision simulation to account for modeling inaccuracies within their robotic control system algorithms.

simulation↗

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.↗

SIBatt-3D: In-Space/On-Surface 3D Printing of Sodium Ion Batteries from ISRU Materials

Constructed more than 20 years ago, the International Space Station’s primary power system originally used nickel-hydrogen batteries with a lifetime of 6.5 years, until NASA began the process of replacing them in 2016 with lithium-ion batteries with a lifetime of 10 years. The demanding and costly process was accomplished after four flights of the Japanese H-II Transfer Vehicle cargo spacecraft (with a cost of about $10,000 per pound of payload), and 13 different astronauts conducting 14 spacewalks. Besides utilization in the ISS, rechargeable batteries are present in many space applications: they are installed in exploration robots, life support systems and in portable communication devices, to mention some. In this context, this project is focused on the in-space manufacturing of shape-conformable batteries using in-situ resources, and aims to address the NASA’s gaps related to the development of next generation of energy storage devices (TX03), as well as in-space manufacturing and in-situ resource utilization (TX07). The proposed work also tackles the HEOMD’s objectives targeting the in-space additive manufacturing (AM) from Lunar/Martian materials (regolith as AM feedstock) to reinvigorate America’s Human Space Exploration Program (SPD-1). This project is in direct alignment with the STMD’s objectives to demonstrate in-space autonomous manufacturing and assembly of complete systems by 2030, and to enable humans to live and explore in space and on planetary surfaces by 2040 thanks to in-space habitation, infrastructure development and in-situ resource utilization (ST1 and ST5). Manufacturing of shape conformable batteries directly in-space and using in-situ resources would also contribute to reducing the payload weight and volume (TX12) for future missions, thus reducing risk for long term Mars missions where rapid resupply is logistically infeasible. Nowadays, commercial batteries consist of stacked two-dimensional (2D) sheets, which are only manufactured in restricted geometries (cylindrical and coin cell). Evolving from conventional 2D, complex 3D battery architectures have been proven to increase the electrochemical active surface area and ion diffusion path, leading to improved areal energy density and power performance. This tendency was illustrated in our recent in-depth modeling studies by simulating a classical Ragone plot exhibiting the energy-power relationship. Our team demonstrated through modeling that a complex gyroidal 3D printed battery architecture exhibits significantly improved power performances (>150% at the current density of 6C; full discharge in 10 minutes) in comparison to a traditional 3D printed planar geometry. Motivated by these results and as the fabrication of intricate 3D battery design is only possible experimentally thanks to the geometric freedom offered by additive manufacturing (AM), our team has already initiated leveraging thermoplastic material extrusion at the laboratory scale. While 3D printing of batteries is relatively recent (2013), it has witnessed a growing interest during the last recent years, as next-generation shape-conformable 3D batteries can be co-designed with the system. Consequently, dead-volume and mass brought from Earth are minimized, in addition to improved battery performance, in alignment with the aforementioned NASA’s objectives. Further, while this project is specifically dedicated to batteries, it lends itself towards the maturation of in-space manufacturing via 3D printing using in-situ resources, stated in HEOMD and STMD goals.

In-Space Manufacturing↗

Finite Element Thermal Model for Ultrasonic Welding of Thermoplastic Composites

Ultrasonic welding, UW, is a fast and energy-efficient technique for joining thermoplastic composites. It involves the use of high-frequency mechanical vibrations and a static welding force to melt and join adherends. Ultrasonic welding is an enabling technology to reduce the cost and complexity of in-space construction because lightweight thermoplastic composite components can be packaged compactly for launch and then efficiently assembled using supervised autonomous robotic technologies on site. However, the temperatures in space present challenges to UW, and it is critical that the efficacy of process parameters selected for manufacturing in space is understood prior to launch. To this end, a three-dimensional finite element model is presented in this technical presentation. The model incorporates equations for effects of viscoelastic heating and heat transfer on the welding process. The proposed model is applied to predict the temperature distribution in single lap shear, SLS, samples composed of AS4/PEEK (TC1200) composite that were welded using a terrestrial machine as part of a comprehensive weldability study. Thermocouple and infrared spot sensor data from the SLS samples provide empirical temperature measurements for calibration and validation of the UW thermal model. Calibration and validation of the model is an important step given the significant uncertainties in material properties such as the loss modulus and necessary assumptions in the physics implementations which allow the model to converge in an acceptable amount of time. The validated thermal model can be used to simulate the process for the space environment. Future validation sample testing is planned in a vacuum chamber. The result will be a model capable of guiding process parameter selection to ensure acceptable weld bonds when manufacturing in space.

Josh Fody↗

An Autonomous Vault-Building Robot System for Creating Spanning Structures

Research in autonomous robots for construction has largely focused on ground-based robots whose reach constrains the size of what they can build, or on climbing or aerial robots that build solid or unroofed structures. Autonomous construction of larger, multistory buildings, or bridges spanning unsupported distances, would require robots that build sturdy structures supporting their own weight. In this paper, we present VaultBot, a system of autonomous robots that build a load-bearing spanning vault using identical modular blocks. The custom blocks employ mechanical and other features to facilitate robotic manipulation and locomotion, and can be removed from and replaced in an assembled structure as a way of repairing damage. We characterize the system's performance and failure modes, and demonstrate reliable autonomous assembly for a structure composed of 46 blocks. Blocks can be made collapsible and deployable as a way of reducing mass and volume that must be transported to a construction site. Such a system could be used to help enable construction of protective shelters in challenging environments, such as disaster relief scenarios, arctic settings, or extraterrestrial habitats.

Nathan Melenbrink↗

Laser Range and Bearing Finder for Autonomous Missions

NASA has recently re-confirmed their interest in autonomous systems as an enabling technology for future missions. In order for autonomous missions to be possible, highly-capable relative sensor systems are needed to determine an object's distance, direction, and orientation. This is true whether the mission is autonomous in-space assembly, rendezvous and docking, or rover surface navigation. Advanced Optical Systems, Inc. has developed a wide-angle laser range and bearing finder (RBF) for autonomous space missions. The laser RBF has a number of features that make it well-suited for autonomous missions. It has an operating range of 10 m to 5 km, with a 5 deg field of view. Its wide field of view removes the need for scanning systems such as gimbals, eliminating moving parts and making the sensor simpler and space qualification easier. Its range accuracy is 1% or better. It is designed to operate either as a stand-alone sensor or in tandem with a sensor that returns range, bearing, and orientation at close ranges, such as NASA's Advanced Video Guidance Sensor. We have assembled the initial prototype and are currently testing it. We will discuss the laser RBF's design and specifications. Keywords: laser range and bearing finder, autonomous rendezvous and docking, space sensors, on-orbit sensors, advanced video guidance sensor

Granade, Stephen R.↗

Application of the CIRSSE cooperating robot path planner to the NASA Langley truss assembly problem

A method for autonomously planning collision free paths for two cooperating robots in a static environment was developed at the Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The method utilizes a divide-and-conquer type of heuristic and involves non-exhaustive mapping of configuration space. While there is no guarantee of finding a solution, the planner was successfully applied to a variety of problems including two cooperating 9 degrees of freedom (dof) robots. Although developed primarily for cooperating robots the method is also applicable to single robot path planning problems. A single 6 dof version of the planner was implemented for the truss assembly east, at NASA Langley's Automated Structural Assembly Lab (ASAL). The results indicate that the planner could be very useful in addressing the ASAL path planning problem and that further work along these lines is warranted.

Weaver, Jonathan M.↗

Autonomous Space Shuttle

The continued assembly and operation of the International Space Station (ISS) is the cornerstone within NASA's overall Strategic P an. As indicated in NASA's Integrated Space Transportation Plan (ISTP), the International Space Station requires Shuttle to fly through at least the middle of the next decade to complete assembly of the Station, provide crew transport, and to provide heavy lift up and down mass capability. The ISTP reflects a tight coupling among the Station, Shuttle, and OSP programs to support our Nation's space goal . While the Shuttle is a critical component of this ISTP, there is a new emphasis for the need to achieve greater efficiency and safety in transporting crews to and from the Space Station. This need is being addressed through the Orbital Space Plane (OSP) Program. However, the OSP is being designed to "complement" the Shuttle as the primary means for crew transfer, and will not replace all the Shuttle's capabilities. The unique heavy lift capabilities of the Space Shuttle is essential for both ISS, as well as other potential missions extending beyond low Earth orbit. One concept under discussion to better fulfill this role of a heavy lift carrier, is the transformation of the Shuttle to an "un-piloted" autonomous system. This concept would eliminate the loss of crew risk, while providing a substantial increase in payload to orbit capability. Using the guidelines reflected in the NASA ISTP, the autonomous Shuttle a simplified concept of operations can be described as; "a re-supply of cargo to the ISS through the use of an un-piloted Shuttle vehicle from launch through landing". Although this is the primary mission profile, the other major consideration in developing an autonomous Shuttle is maintaining a crew transportation capability to ISS as an assured human access to space capability.

Siders, Jeffrey A.↗

Automation and robotics

The Autonomous Systems focus on the automation of control systems for the Space Station and mission operations. Telerobotics focuses on automation for in-space servicing, assembly, and repair. The Autonomous Systems and Telerobotics each have a planned sequence of integrated demonstrations showing the evolutionary advance of the state-of-the-art. Progress is briefly described for each area of concern.

Montemerlo, Melvin↗

Autonomous Lunar Infrastructure Outfitting

The Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS) project at NASA Ames Research Center is developing autonomous infrastructure, instrumentation, and spacecraft assembly and manufacturing capabilities for next generation exploration and science missions, with a goal to change the cost scaling of these missions relative to mission size and duration. Using a building-block approach with a 'kit of parts' composed of ultra-light, high-performance mechanical metamaterials, simplified robots leverage the period environment to achieve high levels of autonomy and reliability for in-space and surface assembly of large-scale apertures, solar-arrays, towers, habitats, and other infrastructure. Robots and structure break down into a compact form factor for launch. By leveraging economies of scale and achieving high-packing ratios, ARMADAS technology can revolutionize space missions by breaking the tyranny of the launch shroud, decreasing development times, decreasing mission costs for transformative science capability, and providing a scalable and versatile space infrastructure strategy. An ecosystem of reconfigurable infrastructure modules can be reused, repaired, expanded reconfigured to meet emergency or unforeseen needs, and reduce spare parts.

Christine Gregg↗

Uncertainty in Servicing and Assembly Tasks for Space Robotic Manipulators

This presentation will discuss a subset of the sources of uncertainty that impact autonomous in-space servicing, assembly, and manufacturing missions. These include robotic manipulator modeling uncertainties in both kinematics and dynamics, perception error associated machine learning models for pose estimation, and sensor noise. Mitigation strategies will be discussed including the incorporation of capture envelopes in the design of robotic tools and selection of robot goal poses to minimize end-effector sensitivity in manipulators with redundant degrees of freedom.

robotics↗

Value Proposition, Strategic Framework, and Capability Needs for In-Space Assembly

The Space Science and Technology (S&T) Partnership Forum was established in 2015 to identify synergistic efforts and technologies across the government, with a focus on key pervasive and game-changing technologies across government space agencies in order to more efficiently and effectively manage S&T resources. As principal partners of the interagency S&T Partnership Forum, the U.S. Air Force (USAF), the National Aeronautics and Space Administration (NASA), and the National Reconnaissance Office (NRO) identified and prioritized several S&T collaboration topic areas. Autonomous and semi-autonomous in-space assembly (iSA) is the focus of the topic area that NASA, under the direction of the Office of Chief Technologist, is currently coordinating among the S&T principal partners and affiliate partners, such as the Defense Advanced Research Projects Agency (DARPA) and the U.S. Naval Research Laboratory (NRL). The S&T iSA facilitation and analysis team, led by NASA, collected data from the participating agencies on their current developments, activities, and needs in the area of in-space assembly. This paper provides an overview of the S&T iSA facilitation and analysis team’s efforts in establishing the value proposition and strategic framework for interagency collaboration in iSA within the partnership as a foundation to deliver value and achieve iSA topic objectives across government space agencies. Further, this paper describes the early products of these efforts in the definition of the iSA capabilities, design drivers, and stakeholder goals to facilitate dialogue within the partnership and the larger community.

Phillip A Williams↗

Establishing In-Space Assembly Technical Collaboration Environments Through Functional Capability Analyses

NASA OCT strategically collaborates with other government space agencies to find enterprise synergistic technology solutions to benefit the Nation through leadership of the interagency Science and Technology Partnership Forum. Successful collaborations depend on integrating knowledge across the intersection of industry, academe, and government within pioneering technical areas such as in-space assembly. High-quality data products that are timely, accurate, and trusted are used to communicate with internal and external stakeholders to influence portfolios by focusing investments to maximize impact on NASA missions and the U.S. economy. These data products succinctly describe and convey the breadth and dependencies of multiple capabilities, while incorporating diverse technical perspectives, to articulate and inform interagency collaborative developments of autonomous on-orbit assembly technologies.

Rodgers, Erica↗

Laser Beam Welding Advancements for In-Space Servicing, Assembly, and Manufacturing

NASA is currently working to develop in-space servicing, assembly, and manufacturing (ISAM) capabilities for low Earth orbit and the lunar surface. One crucial technology for this effort is laser beam welding. Laser systems can perform joining, cleaning, cutting, and repair activities, which will enable the construction of large in-space structures that could not fit on a single launch vehicle, such as trusses for solar panels, radiators, or communications infrastructure. Multiple projects studying laser welding for space applications are currently underway at NASA Marshall Space Flight Center. One of these, the DIsk-Shaped Configurable and Modular vAcuum uNit (DISCMAN), is a compact vacuum chamber designed to support parameter development for laser welding in microgravity. It contains a rotating platen with weld samples made from aluminum, steel, and titanium, a high-power infrared laser, and integrated pumps for pulling vacuum inside the sample cartridge. The DISCMAN payload is planned to launch to the International Space Station, where welds will be performed under sustained microgravity inside the Bishop Airlock. Another effort underway at Marshall is the Lunar Assembly and Servicing by Autonomous Robotics (LASAR) initiative. This project uses a space-rated robotic arm equipped with a laser weld head, wire feeder, and multiple cameras to perform welds in a thermal vacuum chamber simulating the lunar surface environment. Some of these welds are done on snowflake joints, which are specially designed to slot together to join segments of trussN structures, allowing for the construction of tall surface infrastructure. DISCMAN, LASAR, and other projects are being carried out to advance the technological maturity of in-space laser beam welding, collect data to inform computational models, and learn reliable processes for creating weld joints in space. This work supports NASA’s greater goals to expand humanity’s presence in low Earth orbit, establish a permanent moon base, and eventually send crewed missions to Mars and beyond.

Manufacturing↗

Laser Beam Welding Advancements for In-Space Servicing, Assembly, and Manufacturing

NASA is currently working to develop in-space servicing, assembly, and manufacturing (ISAM) capabilities for low Earth orbit and the lunar surface. One crucial technology for this effort is laser beam welding. Laser systems can perform joining, cleaning, cutting, and repair activities, which will enable the construction of large in-space structures that could not fit on a single launch vehicle, such as trusses for solar panels, radiators, or communications infrastructure. Multiple projects studying laser welding for space applications are currently underway at NASA Marshall Space Flight Center. One of these, the DIsk-Shaped Configurable and Modular vAcuum uNit (DISCMAN), is a compact vacuum chamber designed to support parameter development for laser welding in microgravity. It contains a rotating platen with weld samples made from aluminum, steel, and titanium, a high-power infrared laser, and integrated pumps for pulling vacuum inside the sample cartridge. The DISCMAN payload is planned to launch to the International Space Station, where welds will be performed under sustained microgravity inside the Bishop Airlock. Another effort underway at Marshall is the Lunar Assembly and Servicing by Autonomous Robotics (LASAR) initiative. This project uses a space-rated robotic arm equipped with a laser weld head, wire feeder, and multiple cameras to perform welds in a thermal vacuum chamber simulating the lunar surface environment. Some of these welds are done on snowflake joints, which are specially designed to slot together to join segments of trussN structures, allowing for the construction of tall surface infrastructure. DISCMAN, LASAR, and other projects are being carried out to advance the technological maturity of in-space laser beam welding, collect data to inform computational models, and learn reliable processes for creating weld joints in space. This work supports NASA’s greater goals to expand humanity’s presence in low Earth orbit, establish a permanent moon base, and eventually send crewed missions to Mars and beyond.

Robotics↗

Scaling Climbing Collaborative Mobile Manipulators (C2M2) for Outfitting a Tall Lunar Tower (TLT) and Truss Structures

In-space and planetary truss structures like the Tall Lunar Tower (TLT) can greatly benefit from truss climbing collaborative mobile manipulators (C-CMMs) for outfitting and other servicing tasks. Mobile robotic systems traversing these structures will allow for improved access to the structure for placing equipment and routing cables after the structure has been assembled. The robotic system described in the proposed paper is designed to provide access to the structure through collaborative mobile robotics. The paper will provide a method to constrain the design of such a robot via the geometry of the truss structure and the controlling joint torques across various gaits. The focus of the design is on a six-degree of freedom (DOF) robot arranged with two-DOF at each end and at the center. The variable features of this system are the actuators and the length of the links connecting the two-DOF modules. The result of the analysis is a link sizing range which the robot can be designed within to ensure functionality on the truss structure. A C-CMM will be designed using the scaling utility and several constructed to demonstrate operating both independently and collaboratively.

in-space assembly↗