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At least 145 records · Page 8

Infrared-Proximity-Sensor Modules For Robot

Collision-avoidance system for articulated robot manipulators uses infrared proximity sensors grouped together in array of sensor modules. Sensor modules, called "sensorCells," distributed processing board-level products for acquiring data from proximity-sensors strategically mounted on robot manipulators. Each sensorCell self-contained and consists of multiple sensing elements, discrete electronics, microcontroller and communications components. Modules connected to central control computer by redundant serial digital communication subsystem including both serial and a multi-drop bus. Detects objects made of various materials at distance of up to 50 cm. For some materials, such as thermal protection system tiles, detection range reduced to approximately 20 cm.

Parton, William↗

Robot learning and error correction

A model of robot learning is described that associates previously unknown perceptions with the sensed known consequences of robot actions. For these actions, both the categories of outcomes and the corresponding sensory patterns are incorporated in a knowledge base by the system designer. Thus the robot is able to predict the outcome of an action and compare the expectation with the experience. New knowledge about what to expect in the world may then be incorporated by the robot in a pre-existing structure whether it detects accordance or discrepancy between a predicted consequence and experience. Errors committed during plan execution are detected by the same type of comparison process and learning may be applied to avoiding the errors.

Friedman, L.↗

PHALANX: Expendable Projectile Sensor Networks for Planetary Exploration

Technologies enabling long-term, wide-ranging measurement in hard-to-reach areas are a critical need for planetary science inquiry. Phenomena of interest include flows or variations in volatiles, gas composition or concentration, particulate density, or even simply temperature. Improved measurement of these processes enables understanding of exotic geologies and distributions or correlating indicators of trapped water or biological activity. However, such data is often needed in unsafe areas such as caves, lava tubes, or steep ravines not easily reached by current spacecraft and planetary robots. To address this capability gap, we have developed miniaturized, expendable sensors which can be ballistically lobbed from a robotic rover or static lander - or even dropped during a flyover. These projectiles can perform sensing during flight and after anchoring to terrain features. By augmenting exploration systems with these sensors, we can extend situational awareness, perform long-duration monitoring, and reduce utilization of primary mobility resources, all of which are crucial in surface missions. We call the integrated payload that includes a cold gas launcher, smart projectiles, planning software, network discovery, and science sensing: PHALANX. In this paper, we introduce the mission architecture for PHALANX and describe an exploration concept that pairs projectile sensors with a rover “mothership.” Science use cases explored include reconnaissance using ballistic cameras, volatiles detection, and building timelapse maps of temperature and illumination conditions. Strategies to autonomously coordinate constellations of deployed sensors to self-discover and localize with peer ranging (i.e. a “local GPS”) are summarized, thus providing communications infrastructure beyond-line-of-sight (BLOS) of the rover. Capabilities were demonstrated through both simulation and physical testing with a terrestrial prototype. The approach to developing a terrestrial prototype is discussed, including design of the launching mechanism, projectile optimization, micro-electronics fabrication, and sensor selection. Results from early testing and characterization of commercial-off-the-shelf (COTS) components are reported. Nodes were subjected to successful burn-in tests over 48 hours at full logging duty cycle. Integrated field tests were conducted in the Roverscape, a half-acre planetary analog environment at NASA Ames, where we tested up to 10 sensor nodes simultaneously coordinating with an exploration rover. Ranging accuracy has been demonstrated to be within +/-10cm over 20m using commodity radios when compared to high-resolution laser scanner ground truthing. Evolution of the design, including progressive miniaturization of the electronics and iterated modifications of the enclosure housing for streamlining and optimized radio performance are described. Finally, lessons learned to date, gaps toward eventual flight mission implementation, and continuing future development plans are discussed.

Dille, Michael↗

Robotic vehicles for planetary exploration

A program to develop planetary rover technology is underway at the Jet Propulsion Laboratory (JPL) under sponsorship of the National Aeronautics and Space Administration. Developmental systems with the necessary sensing, computing, power, and mobility resources to demonstrate realistic forms of control for various missions have been developed, and initial testing has been completed. These testbed systems and the associated navigation techniques used are described. Particular emphasis is placed on three technologies: Computer-Aided Remote Driving (CARD), Semiautonomous Navigation (SAN), and behavior control. It is concluded that, through the development and evaluation of such technologies, research at JPL has expanded the set of viable planetary rover mission possibilities beyond the limits of remotely teleoperated systems such as Lunakhod. These are potentially applicable to exploration of all the solid planetary surfaces in the solar system, including Mars, Venus, and the moons of the gas giant planets.

Wilcox, Brian↗

Intelligent Autonomy for Unmanned Surface and Underwater Vehicles

As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic systems to perform a high level of on-board decisionmaking, which would otherwise be performed by humanoperators. With more decision making capabilities, less a priori knowledge of the area of operations would be required, as these systems would be able to sense and adapt to changing environmental conditions, such as unknown topography, currents, obstructions, bays, harbors, islands, and river channels. Existing vehicle sensors would be dual-use; that is they would be utilized for the primary mission, which may be mapping or hydrographic reconnaissance; as well as for autonomous hazard avoidance, route planning, and bathymetric-based navigation. This paper describes a tightly integrated instantiation of an autonomous agent called CARACaS (Control Architecture for Robotic Agent Command and Sensing) developed at JPL (Jet Propulsion Laboratory) that was designed to address many of the issues for survivable ASV/AUV control and to provide adaptive mission capabilities. The results of some on-water tests with US Navy technology test platforms are also presented.

environmental sensing↗

Working and Learning with Knowledge in the Lobes of a Humanoid's Mind

Humanoid class robots must have sufficient dexterity to assist people and work in an environment designed for human comfort and productivity. This dexterity, in particular the ability to use tools, requires a cognitive understanding of self and the world that exceeds contemporary robotics. Our hypothesis is that the sense-think-act paradigm that has proven so successful for autonomous robots is missing one or more key elements that will be needed for humanoids to meet their full potential as autonomous human assistants. This key ingredient is knowledge. The presented work includes experiments conducted on the Robonaut system, a NASA and the Defense Advanced research Projects Agency (DARPA) joint project, and includes collaborative efforts with a DARPA Mobile Autonomous Robot Software technical program team of researchers at NASA, MIT, USC, NRL, UMass and Vanderbilt. The paper reports on results in the areas of human-robot interaction (human tracking, gesture recognition, natural language, supervised control), perception (stereo vision, object identification, object pose estimation), autonomous grasping (tactile sensing, grasp reflex, grasp stability) and learning (human instruction, task level sequences, and sensorimotor association).

Ambrose, Robert↗

Video-Based Sensor for Robotic Position and Attitude determination

NASA's Marshall Space Flight Center (MSFC) has, for the last ten years, developed various video-based sensors for use in automated docking systems. The latest generation of sensor will operate at rates of up to 100 Hz, determining the relative position (X, Y, and Z) and attitude (Roll, Pitch, and Yaw) between the sensor and a small 3-dimensional target, making it suitable for applications in robotic sensing. The Advanced Video Guidance Sensor (AVGS) is designed to track multiple targets at different ranges and determine the position and attitude of each one. The previous generation of video sensor, the Video Guidance Sensor (VGS), was flown twice on the Space Shuttle to test its performance on orbit. One of the tests performed was determining the relative positions and attitudes between the VGS and its target, which was moved to various positions using the Remote Manipulator System (RMS). The RMS position data and VGS measured data were analyzed after the flights, with good correlation between the position and attitude data of the two data sets. The test using the RMS gives a good idea of the ability of the use of the AVGS as a sensor for end-effector position and attitude determination.

Howard, Richard T.↗

Hubble Space Telescope Magnetometer and Two-Gyro Control Law Design, Implementation, and On-Orbit Performance

For f i h years, the science mission of the Hubble Space Telescope (HST) required using at least three of six rate gyros for attitude control. In the past, HST has mitigated gyro hardware failures by replacement of the failed units through Space Shuttle Servicing Missions. Following the tragic loss of Space Shuttle Columbia on STS-107, the desire to have a safe haven for astronauts during missions has resulted in the cancellation of all planned maxu14 missions to HST. While a robotic servicing mission is being currently being planned, controlling with alternate sensors to replace failed gyros can extend the HST Science mission until the robotic mission can be performed and extend science at HST s end of life. A two-gym control law has been designed and implemented using magnetometers (Magnetic Sensing System - MSS), fixed head star trackers (FHSTs), and Fine Guidance Sensors (FGSs) to control vehicle rate about the missing gyro axis. The three aforementioned sensors are used in succession to reduce HST boresight jitter to less than 7 milli-arcseconds rms and attitude error to less than 10 milli-arcseconds prior to science imaging. The MSS and 2-Gyro (M2G) control law is used for large angle maneuvers and attitude control during earth occultation of FHSTs and FGSs. The Tracker and 2-Gyro (T2G) control law dampens M2G rates and corrects the majority of attitude error in preparation for guide star acquisition with the FGSs. The Fine Guidance Sensor and 2-Gyro (F2G) control law d a m p T2G rates and controls HST attitude during science imaging. This paper describes the M2G control law. Details of M2G algorithms are presented, including computation of the HST 3-axis attitude error estimate, design of the M2G control law, SISO hear stability analyses, and restrictions on operations to maintain the h d t h and safety requirement of a 10degree maximum attitude error. Results of simulations performed in HSTSIM, a high-fidelity non-linear time domain simulation, are presented to predict HST on-orbit performance in attitude hold and maneuver modes. Simulation results are compared to on-orbit data from M2G flight tests performed in November and December 2004 and February 2005. Flight telemetry, using a currently available third gyro, shows that HST attitude error with the new M2G control law is maintained below the 10-degree requirement, and attitude errors are under 2 degrees for 95% of the time.

Wirzburger, John H.↗

Spectral Monitoring of Volatiles During Drilling into Frozen Lunar Simulant

NASA's Resource Prospector (RP) project intends to characterize the 3D distribution of volatiles in permanently shadowed regions at the lunar poles. One RP remote sensing instrument is a near-infrared spectrometer with an associated camera and radiometer, called the Near-InfraRed Volatile Spectrometer System (NIRVSS). In May 2016, NIRVSS, a Honeybee Robotics drill, and an Inficon mass spectrometer were placed in a vacuum chamber at Glenn Research Center. Also inside was a tube (1.2 m high x 25 cm diameter) filled with lunar simulant NU-LHT-3M, initially doped with a homogeneous water abundance of ~5%, chilled to cryogenic temperatures and exposed to a vacuum (~10e-6 Torr). During drilling, the NIRVSS instruments observed the cuttings pile as subsurface materials were emplaced on the surface. Spectral features associated with water ice, near 2000 and 3000 nm, were measured by the spectrometer during drilling. The spectral data documents development of a desiccated soil layer in the tube down to ~25-30 cm (confirmed by post-test soil analyses), formed during the initial pump down to vacuum. Drilling occurred in 10 cm segments, with the drill stem extracted and flutes brushed after each 10 cm depth. One exception to this was the 40 cm depth segment where the soil was delivered to a sample capture mechanism, and sealed for post-test analyses. To ~30 cm depth the greatest 2000 and 3000 nm signatures were associated with brushing of the drill flutes above the surface. At depths >40 cm the strongest ice signatures were associated with the drill clearing soil from the existing hole, or beginning to encounter new material. For these greater depths, brushing the flutes after extraction produced much weaker ice signatures than for shallower depths. This suggests that the soil may remain trapped in the exit funnel and is not emplaced on the surface. After each event creating strong ice signatures, these signatures decreased to near background levels in 5 minutes or less, due to surface exposure to vacuum.

lunar poles↗

Integrated system for sensing and traverse of cliff faces

In this paper, we describe the development of an integrated suite of autonomous, adaptive hardware/software control methods called SMART (System for Mobility and Access to Rough Terrain) that enables mobile robots to explore potentially important science sites currently beyond the reach of conventional rover designs.

cooperative↗

Real time control for NASA robotic gripper

Control laws (in some optimal sense) are being developed for the gripper/nut runner end effector. Control laws for the gripper and nut runner portions of the end effector may be developed independently since these two systems are decoupled. A hybrid force/position controller will be used for both the gripper and nut runner. The development of the gripper controller is explained. Sensory data available to the controller is obtained from an array of strain gages as well as a linear potentiometer. Applying well known optimal control theoretic principles, the control which minimizes the transition time between positions is obtained. In addition, a robust force control scheme is developed to contend with the strain gage drift caused by extreme temperature variations encountered in space.

Salter, Carole A.↗

The Second Skin: A Wearable Sensor Suite that Enables Real-Time Human Biomechanics Tracking Through Deep Learning

Objective: Real-time determination of human kinematics and kinetics could advance biomechanics research and enable valuable applications of biofeedback and generalizable exoskeleton control. Here, this work aims to investigate a taskindependent, user-independent method for obtaining precise realtime joint state estimation across lower-body joints during a wide variety of tasks. Methods: We developed a generalizable sensing approach using a suit comprised of inertial measurement units (IMUs) and pressure insoles. With the suit, we collected a dataset of 33 tasks commonly performed during construction and hazardous waste cleanup (N = 10). We then trained deep learning user-independent, task-agnostic models to estimate joint lowerbody kinematics and dynamics using only worn sensor data. We likewise computed joint kinematics and dynamics analytically from sensor data to serve as a comparison tool for model results. Results: Our models achieved overall angle estimation root-meansquared-errors (RMSE) of 6.56±.92°, 8.60±1.01°, 7.58±.89°, and 6.00±.73° compared to 13.9±.1.3°, 15.31±1.0°, 10.76±.70°, and 7.56±.48° via analytical methods at the lower back, hip, knee, and ankle, respectively. Likewise, our models achieved overall normalized moment estimation RMSEs of .207±.069 Nm/kg, .242±.044 Nm/kg, .202±.038 Nm/kg, and .193±.034 Nm/kg compared to .306±.036 Nm/kg, .407±.021 Nm/kg, 1.18 ±.022 Nm/kg, and 1.73±.071 Nm/kg via analytical methods at the lower back, hip, knee, and ankle, respectively. Conclusion: These results are comparable to other state-of-the-art wearable sensing systems, establishing deep learning as a viable sensing approach that generalizes to new users and tasks. Significance: This work shows promise for enabling accurate real-world biomechanical data collection and enhancement of biofeedback systems and wearable robot control.

Casey, Ryan T. F. [Georgia Institute of Technology↗

Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

Schenker, Paul S.↗

Robotic Recon for Human Exploration

Robotic reconnaissance has the potential to significantly improve scientific and technical return from lunar surface exploration. In particular, robotic recon may increase crew productivity and reduce operational risk for exploration. However, additional research, development and field-testing is needed to mature robot and ground control systems, refine operational protocols, and specify detailed requirements. When the new lunar surface campaign begins around 2020, and before permanent outposts are established, humans will initially be on the Moon less than 10% of the time. During the 90% of time between crew visits, robots will be available to perform surface operations under ground control. Understanding how robotic systems can best address surface science needs, therefore, becomes a central issue Prior to surface missions, lunar orbiters (LRO, Kaguya, Chandrayyan-1, etc.) will map the Moon. These orbital missions will provide numerous types of maps: visible photography, topographic, mineralogical and geochemical distributions, etc. However, remote sensing data will not be of sufficient resolution, lighting, nor view angle, to fully optimize pre-human exploration planning, e.g., crew traverses for field geology and geophysics. Thus, it is important to acquire supplemental and complementary surface data. Robotic recon can obtain such data, using robot-mounted instruments to scout the surface and subsurface at resolutions and at viewpoints not achievable from orbit. This data can then be used to select locations for detailed field activity and prioritize targets to improve crew productivity. Surface data can also help identify and assess terrain hazards, and evaluate alternate routes to reduce operational risk. Robotic recon could be done months in advance, or be part of a continuing planning process during human missions.

Deans, Matthew↗

An Operations and Maintenance Roadmap for U.S. Offshore Wind: Enabling a Cost-Effective and Sustainable U.S. Offshore Wind Energy Industry Through Innovative Operations and Maintenance

The United States is currently targeting 30GW of offshore wind to be installed by 2030, and 150GW by 2050. Even considering future turbine sizes, this represents thousands of new turbines installed in a diverse set of environments, each with their unique design, installation, and maintenance challenges. While much can be learned from European and Asian experience with offshore wind over the past two decades, it is important to understand the unique circumstances of the U.S. This document explores operations and maintenance of offshore wind energy, specific to the U.S. and attempts to lay out a roadmap for needed activities to ensure reliability of future installations. The roadmap was informed through dozens of interviews with a wide cross-section of the industry, including representatives from OEMs, owner/operators, service companies, certification agencies, service providers, and researchers. The roadmap first describes the problem by component - blades, drivetrain and nacelle, structures and foundations, and electrical systems - through a look at current practices and opportunities for improvement in the areas of Failure Mode Analysis and Mitigation; Monitoring, Sensing, and Inspection; and Maintenance Execution. Crosscutting areas of Digitalization, Robotics and Automation, Prognostics and Health Management and O&M Optimization, Experimentation and Demonstration, Standardization, and Design Optimization Considering Reliability and O&M are then discussed. Finally, the roadmap summarizes all of these topics with recommendations for short (1-3 years), medium (4-7 years), and long term (8-12 years) activities, with a description of needed public and private sector contributions.

17 WIND ENERGY↗

The Lunar Orbital Prospector

The establishment of lunar bases will not end the need for remote sensing of the lunar surface by orbiting platforms. Human and robotic surface exploration will necessarily be limited to some proximate distance from the support base. Near real-time, high-resolution, global characterization of the lunar surface by orbiting sensing systems will continue to be essential to the understanding of the Moon's geophysical structure and the location of exploitable minerals and deposits of raw materials. The Lunar Orbital Prospector (LOP) is an orbiting sensing platform capable of supporting a variety of modular sensing packages. Serviced by a lunar-based shuttle, the LOP will permit the exchange of instrument packages to meet evolving mission needs. The ability to recover, modify, and rotate sensing packages allows their reuse in varying combinations. Combining this flexibility with robust orbit modification capabilities and near real-time telemetry links provides considerable system responsiveness. Maintenance and modification of the LOP orbit are accomplished through use of an onboard propulsion system that burns lunar-supplied oxygen and aluminum. The relatively low performance of such a system is more than compensated for by the elimination of the need for Earth-supplied propellants. The LOP concept envisions a continuous expansion of capability through the incorporation of new instrument technologies and the addition of platforms.

Redd, Frank J.↗

Intelligent sensing and control for advanced teleoperation

A theoretical framework is presented for a 'sensing-knowledge command-fusion' paradigm of interactive and cooperative sensing and control in advanced teleoperators, which takes advantage of both current and projected robotic dexterousness and sensor-based autonomy capabilities. Attention is given to (1) a method for the achievement of a sensing-knowledge-command computational mechanism that implements the intended cooperative/interactive system, and (2) the system architecture and man/machine-interface protocols entailed by this implementation.

Lee, Sukhan↗

Robonaut 2 - The First Humanoid Robot in Space

NASA and General Motors have developed the second generation Robonaut, Robonaut 2 or R2, and it is scheduled to arrive on the International Space Station in late 2010 and undergo initial testing in early 2011. This state of the art, dexterous, anthropomorphic robotic torso has significant technical improvements over its predecessor making it a far more valuable tool for astronauts. Upgrades include: increased force sensing, greater range of motion, higher bandwidth and improved dexterity. R2 s integrated mechatronics design results in a more compact and robust distributed control system with a faction of the wiring of the original Robonaut. Modularity is prevalent throughout the hardware and software along with innovative and layered approaches for sensing and control. The most important aspects of the Robonaut philosophy are clearly present in this latest model s ability to allow comfortable human interaction and in its design to perform significant work using the same hardware and interfaces used by people. The following describes the mechanisms, integrated electronics, control strategies and user interface that make R2 a promising addition to the Space Station and other environments where humanoid robots can assist people.

Diftler, M. A.↗