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At least 253 records · Page 14

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NASA NTRS1991

Summary report: A preliminary investigation into the use of fuzzy logic for the control of redundant manipulators

The Rice University Department of Mechanical Engineering and Materials Sciences' Robotics Group designed and built an eight degree of freedom redundant manipulator. Fuzzy logic was proposed as a control scheme for tasks not directly controlled by a human operator. In preliminary work, fuzzy logic control was implemented for a camera tracking system and a six degree of freedom manipulator. Both preliminary systems use real time vision data as input to fuzzy controllers. Related projects include integration of tactile sensing and fuzzy control of a redundant snake-like arm that is under construction.

Cheatham, John B., Jr.↗

NASA NTRS1988

Mobile transporter path planning using a genetic algorithm approach

The use of an optimization technique known as a genetic algorithm for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the Space Station which must be able to reach any point of the structure autonomously. Specific elements of the genetic algorithm are explored in both a theoretical and experimental sense. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research. However, trajectory planning problems are common in space systems and the genetic algorithm provides an attractive alternative to the classical techniques used to solve these problems.

Baffes, Paul↗

NASA NTRS1993

Control of nonlinear systems with applications to constrained robots and spacecraft attitude stabilization

This thesis is organized in two parts. In Part 1, control systems described by a class of nonlinear differential and algebraic equations are introduced. A procedure for local stabilization based on a local state realization is developed. An alternative approach to local stabilization is developed based on a classical linearization of the nonlinear differential-algebraic equations. A theoretical framework is established for solving a tracking problem associated with the differential-algebraic system. First, a simple procedure is developed for the design of a feedback control law which ensures, at least locally, that the tracking error in the closed loop system lies within any given bound if the reference inputs are sufficiently slowly varying. Next, by imposing additional assumptions, a procedure is developed for the design of a feedback control law which ensures that the tracking error in the closed loop system approaches zero exponentially for reference inputs which are not necessarily slowly varying. The control design methodologies are used for simultaneous force and position control in constrained robot systems. The differential-algebraic equations are shown to characterize the slow dynamics of a certain nonlinear control system in nonstandard singularly perturbed form. In Part 2, the attitude stabilization (reorientation) of a rigid spacecraft using only two control torques is considered. First, the case of momentum wheel actuators is considered. The complete spacecraft dynamics are not controllable. However, the spacecraft dynamics are small time locally controllable in a reduced sense. The reduced spacecraft dynamics cannot be asymptotically stabilized using continuous feedback, but a discontinuous feedback control strategy is constructed. Next, the case of gas jet actuators is considered. If the uncontrolled principal axis is not an axis of symmetry, the complete spacecraft dynamics are small time locally controllable. However, the spacecraft attitude cannot be asymptotically stabilized using continuous feedback, but a discontinuous stabilizing feedback control strategy is constructed. If the uncontrolled principal axis is an axis of symmetry, the complete spacecraft dynamics cannot be stabilized. However, the spacecraft dynamics are small time locally controllable in a reduced sense. The reduced spacecraft dynamics cannot be asymptotically stabilized using continuous feedback, but again a discontinuous feedback control strategy is constructed.

Krishnan, Hariharan↗

NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RAS-SOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar sur-face, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensing. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗

NASA NTRS1989

A prototype autonomous agent for crew and equipment retrieval in space

The ground-based demonstration of Extra Vehicular Activity (EVA) Retriever, a voice-supervised, intelligent, free-flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles. The software architecture incorporates a hierarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: perception, world model, reasoning, sensing, and acting. The design provides for supervised autonomy as the primary mode of operation with teleoperation as the backup mode. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable operation.

Erickson, J. D.↗

NASA NTRS1991

A lightweight, high strength dexterous manipulator for commercial applications

The concept, design, and features are described of a lightweight, high strength, modular robot manipulator being developed for space and commercial applications. The manipulator has seven fully active degrees of freedom and is fully operational in 1 G. Each of the seven joints incorporates a unique drivetrain design which provides zero backlash operation, is insensitive to wear, and is single fault tolerant to motor or servo amplifier failure. Feedback sensors provide position, velocity, torque, and motor winding temperature information at each joint. This sensing system is also designed to be single fault tolerant. The manipulator consists of five modules (not including gripper). These modules join via simple quick-disconnect couplings and self-mating connectors which allow rapid assembly and/or disassembly for reconfiguration, transport, or servicing. The manipulator is a completely enclosed assembly, with no exposed components or wires. Although the initial prototype will not be space qualified, the design is well suited to meeting space requirements. The control system provides dexterous motion by controlling the endpoint location and arm pose simultaneously. Potential applications are discussed.

Marzwell, Neville I.↗

NASA NTRS1992

Technology test results from an intelligent, free-flying robot for crew and equipment retrieval in space

The ground-based demonstrations of Extra Vehicular Activity (EVA) Retriever, a voice-supervised, intelligent, free-flying robot, are designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles with subsequent object handover. The software architecture incorporates a heirarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: sensing, perception, world model, reasoning, and acting. The design provides for supervised autonomy as the primary mode of operation. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable and safe operation. This paper gives an overview of the hardware, a focus on software, and a summary of results achieved recently from both computer simulations and air bearing floor demonstrations. Limitations of the technology used are evaluated. Plans for the next phase, during which moving targets and obstacles drive realtime behavior requirements, are discussed.

Erickson, J.↗

NASA NTRS2012

Estimation and Bias Correction of Aerosol Abundance using Data-driven Machine Learning and Remote Sensing

Air quality information is increasingly becoming a public health concern, since some of the aerosol particles pose harmful effects to peoples health. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. The comparison between the AOD measured from the ground-based Aerosol Robotic Network (AERONET) system and the satellite MODIS instruments at 550 nm shows that there is a bias between the two data products. We performed a comprehensive analysis exploring possible factors which may be contributing to the inter-instrumental bias between MODIS and AERONET. The analysis used several measured variables, including the MODIS AOD, as input in order to train a neural network in regression mode to predict the AERONET AOD values. This not only allowed us to obtain an estimate, but also allowed us to infer the optimal sets of variables that played an important role in the prediction. In addition, we applied machine learning to infer the global abundance of ground level PM2.5 from the AOD data and other ancillary satellite and meteorology products. This research is part of our goal to provide air quality information, which can also be useful for global epidemiology studies.

Malakar, Nabin K.↗

NASA NTRS1996

On-Board Perception System For Planetary Aerobot Balloon Navigation

NASA's Jet Propulsion Laboratory is implementing the Planetary Aerobot Testbed to develop the technology needed to operate a robotic balloon aero-vehicle (Aerobot). This earth-based system would be the precursor for aerobots designed to explore Venus, Mars, Titan and other gaseous planetary bodies. The on-board perception system allows the aerobot to localize itself and navigate on a planet using information derived from a variety of celestial, inertial, ground-imaging, ranging, and radiometric sensors.

Planetary Aerobot Testbed robotic balloon aero-veh↗

NASA NTRS1988

Man-systems requirements for the control of teleoperators in space

The microgravity of the space environment has profound effects on humans and, consequently, on the design requirements for subsystems and components with which humans interact. There are changes in the anthropometry, vision, the perception of orientation, posture, and the ways in which we exert energy. The design requirements for proper human engineering must reflect each of the changes that results, and this is especially true in the exercise of control over remote and teleoperated systems where the operator is removed from any direct sense of control. The National Aeronautics and Space Administration has recently completed the first NASA-wide human factors standard for microgravity. The Man-Systems Integration Standard, NASA-STD-3000, contains considerable information on the appropriate design criteria for microgravity, and there is information that is useful in the design for teleoperated systems. There is not, however, a dedicated collection of data which pertains directly to the special cases of remote and robotic operations. The design considerations for human-system interaction in the control of remote systems in space are discussed, with brief details on the information to be found in the NASA-STD-3000, and arguments for a dedicated section within the Standard which deals with robotic, teleoperated and remote systems and the design requirements for effective human control of these systems in the space environment, and from the space environment.

Shields, Nicholas L., Jr.↗

NASA NTRS2012

Mapping the Upper Subsurface of MARS Using Radar Polarimetry

Future human exploration of Mars will require detailed knowledge of the surface and upper several meters of the subsurface in potential landing sites. Likewise, many of the Planetary Science Decadal Survey science goals, such as understanding the history of Mars climate change, determining how the surface was altered through processes like volcanism and fluvial activity, and locating regions that may have been hospitable to life in the past, would be significantly advanced through mapping of the upper meters of the surface. Synthetic aperture radar (SAR) is the only remote sensing technique capable of penetrating through meters of material and imaging buried surfaces at high (meters to tens-of-meters) spatial resolution. SAR is capable of mapping the boundaries of buried units and radar polarimetry can provide quantitative information about the roughness of surface and subsurface units, depth of burial of stratigraphic units, and density of materials. Orbital SAR systems can obtain broad coverage at a spatial scale relevant to human and robotic surface operations. A polarimetric SAR system would greatly increase the safety and utility of future landed systems including sample caching.

Carter, L. M.↗

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 NTRS2020

Robotic Assembly Activities at NASA Langley Research Center

Over the past several decades, NASA Langley Research Center (LaRC) has developed a suite of hardware and software capabilities for robotic in-space assembly. Specific robots include the Lightweight Surface Manipulation System (LSMS), Tendon-Actuated Lightweight In-Space Manipulator (TALISMAN), NASA Intelligent Jigging and Assembly Robot (NINJAR), Strut Assembly, Manufacturing, Utility & Robotic Aid (SAMURAI), and most recently the Assemblers modular robots. Alongside the hardware, software tools such as the Autonomous Entity Operations Network (AEON) and the Baseline Environment for Autonomous Modeling (BEAM) have been developed to enable communication and simulation respectively. These tools have supported foundational research in single and multi-agent control, sensing and perception, trajectory generation, task allocation, and human-machine teaming. This talk will provide a broad overview of these capabilities and go into detail on recent developments made by the Assemblers project to create modular, reconfigurable robots for autonomous in-space assembly.

John R Cooper↗

NASA NTRS2020

Spatiotemporal Characteristics of the Association between AOD and PM over the California Central Valley

Many air pollution health effects studies rely on exposure estimates of particulate matter (PM) concentrations derived from remote sensing observations of aerosol optical depth (AOD). Simple but robust calibration models between AOD and PM are therefore important for generating reliable PM exposures. We conduct an in-depth examination of the spatial and temporal characteristics of the AOD-PM2.5 relationship by leveraging data from the Distributed Regional Aerosol Gridded Observation Networks (DRAGON) field campaign where eight NASA Aerosol Robotic Network (AERONET) sites were co-located with EPA Air Quality System (AQS) monitoring sites in California’s Central Valley from November 2012 to April 2013. With this spatiotemporally rich data we found that linear calibration models (R(exp 2) = 0.35, RMSE = 10.38 µg/cu.m) were significantly improved when spatial (R(exp 2) = 0.45, RMSE = 9.54 µg/cu.m), temporal (R(exp 2) = 0.62, RMSE = 8.30 µg/cu.m), and spatiotemporal (R(exp 2) = 0.65, RMSE = 7.58 µg/cu.m) functions were included. As a use-case we applied the best spatiotemporal model to convert space-borne MultiAngle Imaging Spectroradiometer (MISR) AOD observations to predict PM2.5 over the region (R(exp 2) = 0.60, RMSE = 8.42 µg/cu.m). Our results imply that simple AERONET AOD-PM2.5 calibrations are robust and can be reliably applied to space-borne AOD observations, resulting in PM2.5 prediction surfaces for use in downstream applications.

Meytar Sorek-Hamer↗

NASA NTRS2003

Automated Rock Identification for Future Mars Exploration Missions

A key task for human or robotic explorers on the surface of Mars is choosing which particular rock or mineral samples should be selected for more intensive study. The usual challenges of such a task are compounded by the lack of sensory input available to a suited astronaut or the limited downlink bandwidth available to a rover. Additional challenges facing a human mission include limited surface time and the similarities in appearance of important minerals (e.g. carbonates, silicates, salts). Yet the choice of which sample to collect is critical. To address this challenge we are developing science analysis algorithms to interface with a Geologist's Field Assistant (GFA) device that will allow robotic or human remote explorers to better sense and explore their surroundings during limited surface excursions. We aim for our algorithms to interpret spectral and imaging data obtained by various sensors. The algorithms, for example, will identify key minerals, rocks, and sediments from mid-IR, Raman, and visible/near-IR spectra as well as from high resolution and microscopic images to help interpret data and to provide high-level advice to the remote explorer. A top-level system will consider multiple inputs from raw sensor data output by imagers and spectrometers (visible/near-IR, mid-IR, and Raman) as well as human opinion to identify rock and mineral samples.

Gulick, V. C.↗

NASA NTRS2017

The Intelligent Landing System for Safe and Precise Landing on Europa

Europa, the smallest of Jupiter’s Galilean moons, is thought to harbor a vast liquid water ocean beneath its icy crust, making it one of the most scientifically intriguing targets for a robotic surface sampling mission in our Solar System. However, autonomously landing a spacecraft safely and precisely on Europa poses unique challenges, such as very little existing high-resolution reconnaissance imagery, a surface expected to be very rough and hazardous over a wide range of scales, an extremely intense ionizing radiation environment, and very limited lander resources for mass and volume. To address these challenges, we propose a novel Intelligent Landing System (ILS) combining four Guidance, Navigation & Control (GN&C) sensing functions – velocimetry, altimetry, map-relative localization, and hazard detection – that would together enable safe and precise landing on Europa’s surface. The ILS is a smart sensor system, combining an inertial measurement unit (IMU), a monocular, passive-optical camera, and a light detection and ranging (Li-DAR) sensor with dedicated computing resources as well as an onboard 3D terrain map. The ILS leverages more than a decade of technology development from programs such as the Lander Vision System, currently baselined on the Mars 2020 mission. This paper provides a detailed description of the proposed ILS architecture and concept of operations, as well as select preliminary simulation results to assess performance and robustness.

Trawny, Nikolas↗

NASA NTRS2016

Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?

Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations.

Sridhar, Banavar↗