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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Robotic Technology Efforts at the NASA/Johnson Space Center

The NASA/Johnson Space Center has been developing robotic systems in support of space exploration for more than two decades. The goal of the Center's Robotic Systems Technology Branch is to design and build hardware and software to assist astronauts in performing their mission. These systems include: rovers, humanoid robots, inspection devices and wearable robotics. Inspection systems provide external views of space vehicles to search for surface damage and also maneuver inside restricted areas to verify proper connections. New concepts in human and robotic rovers offer solutions for navigating difficult terrain expected in future planetary missions. An important objective for humanoid robots is to relieve the crew of "dull, dirty or dangerous" tasks allowing them more time to perform their important science and exploration missions. Wearable robotics one of the Center's newest development areas can provide crew with low mass exercise capability and also augment an astronaut's strength while wearing a space suit. This presentation will describe the robotic technology and prototypes developed at the Johnson Space Center that are the basis for future flight systems. An overview of inspection robots will show their operation on the ground and in-orbit. Rovers with independent wheel modules, crab steering, and active suspension are able to climb over large obstacles, and nimbly maneuver around others. Humanoid robots, including the First Humanoid Robot in Space: Robonaut 2, demonstrate capabilities that will lead to robotic caretakers for human habitats in space, and on Mars. The Center's Wearable Robotics Lab supports work in assistive and sensing devices, including exoskeletons, force measuring shoes, and grasp assist gloves.

Diftler, Ron↗
NASA NTRS2017

Robotic Technology Efforts at the NASA/Johnson Space Center

The NASA/Johnson Space Center has been developing robotic systems in support of space exploration for more than two decades. The goal of the Center’s Robotic Systems Technology Branch is to design and build hardware and software to assist astronauts in performing their mission. These systems include: rovers, humanoid robots, inspection devices and wearable robotics. Inspection systems provide external views of space vehicles to search for surface damage and also maneuver inside restricted areas to verify proper connections. New concepts in human and robotic rovers offer solutions for navigating difficult terrain expected in future planetary missions. An important objective for humanoid robots is to relieve the crew of “dull, dirty or dangerous” tasks allowing them more time to perform their important science and exploration missions. Wearable robotics one of the Center’s newest development areas can provide crew with low mass exercise capability and also augment an astronaut’s strength while wearing a space suit.This presentation will describe the robotic technology and prototypes developed at the Johnson Space Center that are the basis for future flight systems. An overview of inspection robots will show their operation on the ground and in-orbit. Rovers with independent wheel modules, crab steering, and active suspension are able to climb over large obstacles, and nimbly maneuver around others. Humanoid robots, including the First Humanoid Robot in Space: Robonaut 2, demonstrate capabilities that will lead to robotic caretakers for human habitats in space, and on Mars. The Center’s Wearable Robotics Lab supports work in assistive and sensing devices, including exoskeletons, force measuring shoes, and grasp assist gloves.

Diftler, Ron↗
NASA NTRS1986

Active control of robot manipulator compliance

Work performed at Catholic University on the research grant entitled Active Control of Robot Manipulator Compliance, supported by NASA/Goddard space Flight Center during the period of May 15th, 1986 to November 15th, 1986 is described. The modelling of the two-degree-of-freedom robot is first presented. Then the complete system including the robot and the hybrid controller is simulated on an IBM-XT Personal Computer. Simulation results showed that proper adjustments of controller gains enable the robot to perform successful operations. Further research should focus on developing a guideline for the controller gain design to achieve system stability.

Nguyen, C. C.↗
NASA NTRS1988

Applications of concurrent neuromorphic algorithms for autonomous robots

This article provides an overview of studies at the Oak Ridge National Laboratory (ORNL) of neural networks running on parallel machines applied to the problems of autonomous robotics. The first section provides the motivation for our work in autonomous robotics and introduces the computational hardware in use. Section 2 presents two theorems concerning the storage capacity and stability of neural networks. Section 3 presents a novel load-balancing algorithm implemented with a neural network. Section 4 introduces the robotics test bed now in place. Section 5 concerns navigation issues in the test-bed system. Finally, Section 6 presents a frequency-coded network model and shows how Darwinian techniques are applied to issues of parameter optimization and on-line design.

Barhen, J.↗
NASA NTRS1993

Robotics handbook. Version 1: For the interested party and professional

This publication covers several categories of information about robotics. The first section provides a brief overview of the field of Robotics. The next section provides a reasonably detailed look at the NASA Robotics program. The third section features a listing of companies and organization engaging in robotics or robotic-related activities; followed by a listing of associations involved in the field; followed by a listing of publications and periodicals which cover elements of robotics or related fields. The final section is an abbreviated abstract of referred journal material and other reference material relevant to the technology and science of robotics, including such allied fields as vision perception; three-space axis orientation and measurement systems and associated inertial reference technology and algorithms; and physical and mechanical science and technology related to robotics.

Source record↗
DOE OSTI2022

Review on robot-assisted polishing: Status and future trends

Nowadays, precision components have been extensively used in various industries such as biomedicine, photonics, and optics. To achieve nanometric surface roughness, high-precision polishing is mandatory. Compared with the conventional polishing techniques, the robot-assisted polishing has the advantages of flexible working ranges and low cost. Therefore, it has been more widely deployed in demanding polishing tasks. However, few review articles were found on this topic to provide a general progress on the development of the robot-assisted polishing technology. Here in this paper reviews the recent advancement of the robot-assisted polishing. Firstly, the integration of robots with various polishing techniques is overviewed, followed by the introduction of the research status of constant force control in robot-assisted polishing. Then, the errors in typical robot-assisted polishing systems are analyzed, together with the corresponding compensation methods. At last, the future trends in the development of robot-assisted polishing are discussed. This review is intended as a roadmap for researchers or engineers who are interested in robot-assisted polishing or machining.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Advanced mechanisms for robotics

An overview of applied research and development at NASA-Goddard (GSFC) on mechanisms and the collision avoidance skin for robots is presented. First the work on robot end effectors is outlined, followed by a brief discussion on robot-friendly payload latching mechanisms and compliant joints. This, in turn, is followed by the collision avoidance/management skin and the GSFC research on magnetostrictive direct drive motors. Finally, a new project, the artificial muscle, is introduced. Each of the devices is described in sufficient detail to permit a basic understanding of its purpose, fundamental principles of operation, and capabilities. In addition, the development status of each is reported along with descriptions of breadboards and prototypes and their test results. In each case, the implications of the research for commercialization is discussed. The chronology of the presentation will give a clear idea of both the evolution of the R&D in recent years and its likely direction in the future.

Vranish, John M.↗
NASA NTRS1994

Perception for mobile robot navigation: A survey of the state of the art

In order for mobile robots to navigate safely in unmapped and dynamic environments they must perceive their environment and decide on actions based on those perceptions. There are many different sensing modalities that can be used for mobile robot perception; the two most popular are ultrasonic sonar sensors and vision sensors. This paper examines the state-of-the-art in sensory-based mobile robot navigation. The first issue in mobile robot navigation is safety. This paper summarizes several competing sonar-based obstacle avoidance techniques and compares them. Another issue in mobile robot navigation is determining the robot's position and orientation (sometimes called the robot's pose) in the environment. This paper examines several different classes of vision-based approaches to pose determination. One class of approaches uses detailed, a prior models of the robot's environment. Another class of approaches triangulates using fixed, artificial landmarks. A third class of approaches builds maps using natural landmarks. Example implementations from each of these three classes are described and compared. Finally, the paper presents a completely implemented mobile robot system that integrates sonar-based obstacle avoidance with vision-based pose determination to perform a simple task.

Kortenkamp, David↗
DOE OSTI2023

Spot Robot Staffing Augmentation in Process Modeling and Analysis (E-2) [Slides]

In September 2021 E-2 obtained its first Spot robot from Boston Dynamics to evaluate their suitability for work in and around laboratory facilities. Spot is a highly mobile quadruped robot capable of up to 90 minutes of operation. They can be outfitted with payloads up to 30 pounds and support Boston Dynamics-developed equipment, third party payloads, or custom-developed payloads. The platform showed immediate promise resulting in the procurement of a total of four units by the end of FY22 (Trinity, Gadget, Crossroads, and Sandstone).

42 ENGINEERING↗
DOE OSTI2016

Characteristics and performance of the first commercial multileaf collimator for a robotic radiosurgery system

Purpose: The “InCise™ multileaf-collimator (MLC)” is the first commercial MLC to be mounted on a robotic SRS/SBRT platform (CyberKnife). The authors assessed characteristics and performance of this novel device in a preclinical five months test period. Methods: Commissioning beam data were acquired with unshielded diodes. EBT3 radiochromic films were employed for measurement of transmission, leaf/bank position accuracy (garden fence) before and after exercising the MLC, for end-to-end testing and further characterization of the beam. The robot workspace with MLC was assessed analytically by transformation to an Euler geometry (“plane,” “gantry,” and “collimator” angles) and by measuring pointing accuracy at each node. Stability over time was evaluated in picket fence and adapted Winston–Lutz tests (AQA). Results: Beam penumbrae (80%–20%, with 100% = 2 × dose at inflection point for field sizes ≥ 50 × 50 mm{sup 2}) were 2.2–3.7 mm for square fields in reference condition (source-axis-distance 800 mm, depth 15 mm) and depended on field size and off-axis position. Transmission and leakage did not exceed 0.5%. Accessible clinical workspace with MLC covered non-coplanar gantry angles of [−113°; +112°] and collimator angles of [−100°; +107°], with an average robot pointing accuracy of 0.12 ± 0.09 mm. For vertical beams, garden fence tests exhibited an average leaf positioning error of ≤0.2 mm, which increased by 0.25 and 0.30 mm (banks X1 and X2) with leaves traveling parallel to gravity. After execution of a leaf motion stress routine, garden fence tests showed slightly increased jaggedness and allowed to identify one malfunctioning leaf motor. Total system accuracy with MLC was 0.38 ± 0.05 mm in nine end-to-end tests. Picket fence and AQA tests displayed stable results over the test period. Conclusions: The InCise™ MLC for CyberKnife showed high accuracy and adequate characteristics for SRS/SBRT applications. MLC performance after exercise demands specific quality assurance measures.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Sensory Motor Coordination in Robonaut

As a participant of the year 2000 NASA Summer Faculty Fellowship Program, I worked with the engineers of the Dexterous Robotics Laboratory at NASA Johnson Space Center on the Robonaut project. The Robonaut is an articulated torso with two dexterous arms, left and right five-fingered hands, and a head with cameras mounted on an articulated neck. This advanced space robot, now driven only teleoperatively using VR gloves, sensors and helmets, is to be upgraded to a thinking system that can find, interact with and assist humans autonomously, allowing the Crew to work with Robonaut as a (junior) member of their team. Thus, the work performed this summer was toward the goal of enabling Robonaut to operate autonomously as an intelligent assistant to astronauts. Our underlying hypothesis is that a robot can develop intelligence if it learns a set of basic behaviors (i.e., reflexes - actions tightly coupled to sensing) and through experience learns how to sequence these to solve problems or to accomplish higher-level tasks. We describe our approach to the automatic acquisition of basic behaviors as learning sensory-motor coordination (SMC). Although research in the ontogenesis of animals development from the time of conception) supports the approach of learning SMC as the foundation for intelligent, autonomous behavior, we do not know whether it will prove viable for the development of autonomy in robots. The first step in testing the hypothesis is to determine if SMC can be learned by the robot. To do this, we have taken advantage of Robonaut's teleoperated control system. When a person teleoperates Robonaut, the person's own SMC causes the robot to act purposefully. If the sensory signals that the robot detects during teleoperation are recorded over several repetitions of the same task, it should be possible through signal analysis to identify the sensory-motor couplings that accompany purposeful motion. In this report, reasons for suspecting SMC as the basis for intelligent behavior will be reviewed. A robot control system for autonomous behavior that uses learned SMC will be proposed. Techniques for the extraction of salient parameters from sensory and motor data will be discussed. Experiments with Robonaut will be discussed and preliminary data presented.

Peters, Richard Alan, II↗
NASA NTRS2011

Towards Autonomous Operation of Robonaut 2

The Robonaut 2 (R2) platform, as shown in Figure 1, was designed through a collaboration between NASA and General Motors to be a capable robotic assistant with the dexterity similar to a suited astronaut [1]. An R2 robot was sent to the International Space Station (ISS) in February 2011 and, in doing so, became the first humanoid robot in space. Its capabilities are presently being tested and expanded to increase its usefulness to the crew. Current work on R2 includes the addition of a mobility platform to allow the robot to complete tasks (such as cleaning, maintenance, or simple construction activities) both inside and outside of the ISS. To support these new activities, R2's software architecture is being developed to provide efficient ways of programming robust and autonomous behavior. In particular, a multi-tiered software architecture is proposed that combines principles of low-level feedback control with higher-level planners that accomplish behavioral goals at the task level given the run-time context, user constraints, the health of the system, and so on. The proposed architecture is shown in Figure 2. At the lowest-level, the resource level, there exists the various sensory and motor signals available to the system. The sensory signals for a robot such as R2 include multiple channels of force/torque data, joint or Cartesian positions calculated through the robot's proprioception, and signals derived from objects observable by its cameras.

Badger, Julia M.↗
DOE OSTI2023

Robotic surgical devices, systems and related methods

Various medical devices and related systems, including robotic and/or in vivo medical devices, and various robotic surgical devices for in vivo medical procedures. Included herein, for example, is a robotic surgical system having a support beam positionable through an incision, and a robotic device having a device body, first and second rotating shoulder components coupled to the device body, and first and second robotic arms coupled to the first and second shoulder components, respectively.

Farritor, Shane↗
NASA NTRS2006

Intelligent Vision Systems Independent Research and Development (IR&D) 2006

This report summarizes results in conduct of research sponsored by the 2006 Independent Research and Development (IR&D) program at Marshall Space Flight Center (MSFC) at Redstone Arsenal, Alabama. The focus of this IR&D is neural network (NN) technology provided by Imagination Engines, Incorporated (IEI) of St. Louis, Missouri. The technology already has many commercial, military, and governmental applications, and a rapidly growing list of other potential spin-offs. The goal for this IR&D is implementation and demonstration of the technology for autonomous robotic operations, first in software and ultimately in one or more hardware realizations. Testing is targeted specifically to the MSFC Flat Floor, but may also include other robotic platforms at MSFC, as time and funds permit. For the purpose of this report, the NN technology will be referred to by IEI's designation for a subset configuration of its patented technology suite: Self-Training Autonomous Neural Network Object (STANNO).

Patrick, Clinton↗
NASA NTRSDate not supplied

Astrobee On-Orbit Commissioning

The Astrobee free flying robots operate in the interior of the International Space Station (ISS) under supervisory control of 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 also provides a tool for improving the efficiency of ISS operations as a mobile camera/sensor platform available to flight and payload controllers. The Astrobee system consists of three robots with perching arms, a docking station, and a ground data system. Development began in late-2014, and flight hardware has been deployed to ISS on several launches starting in November 2018 and concluding in October 2019. Shortly after the first two robots arrived on ISS in April, we began a series of "commissioning" activities to validate both space and ground segments. We plan to complete commissioning and become an operational facility available to guest scientists by the end of 2019. This paper provides an overview of the Astrobee system, a description of the on-orbit activities, and commissioning results.

ISS↗
NASA NTRSDate not supplied

Astrobee On-Orbit Commissioning

The Astrobee free flying robots operate in the interior of the International Space Station (ISS) under supervisory control of 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 also provides a tool for improving the efficiency of ISS operations as a mobile camera/sensor platform available to flight and payload controllers. The Astrobee system consists of three robots with perching arms, a docking station, and a ground data system. Development began in late-2014, and flight hardware has been deployed to ISS on several launches starting in November 2018 and concluding in October 2019. Shortly after the first two robots arrived on ISS in April, we began a series of “commissioning” activities to validate both space and ground segments. This paper provides an overview of the Astrobee system, a description of the on-orbit activities, and commissioning results.

Astrobee↗
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↗