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Touch sensor for robot hands provides information about shape of grasped object and force exerted by gripper on object. Pins projecting from sensor create electrical signals when pressed. When grasped object depresses pin, it contacts electrode under it, connecting electrode to common electrode. Sensor indicates where, and how firmly, gripper has touched object.
Electromechanical hand incorporates touch sensors, concealed fingers, and a structure that allows the hand to hold a tool on a flat surface. The hands can be mounted on most types of existing manipulators either directly or by means of modified mounting brackets.
Description of the equipment employed and results obtained in experiments with tactile feedback and different levels of automatic control. In the experiments described tactile feedback was investigated by incorporating a touch sensing and touch display system into a teleoperator, while the levels of automatic control were investigated by incorporating supervisory control features in the teleoperator control system. In particular, a hand contact system which senses and reproduces to the operator the contact between the end-effector and the object being touched or manipulated is described, as well as a jaw contact system which senses and reproduces to the operator the shape and location of the object held in the remote jaws, and an arm control system consisting of a control station where the operator controls the motion of the arm by transmitting commands, a remote station that accepts the commands and uses them, and a communications link that limits information flow. In addition, an algorithmic language for remote manipulation is described, and the desired features that an automatic arm controller should possess are reviewed.
Optical tactile sensor for mechanical hands senses contact pressure via change in light reflected from an elastic covering. Pressure against a cell cover causes distortion, which changes internal reflection of light. Change is sensed by detector, and output signal informs operator of contact. The greater the pressure and distortion, the greater the change in light reflection.
Sensor determines when thickness of film of electrically conductive wastewater on rotating evaporator drum exceeds preset value. Sensor simple electrical probe that makes contact with liquid surface. Made of materials resistant to chemicals in liquid. Mounted on shaft in rotating cylinder, liquid-thickness sensor extends toward cylinder wall so tip almost touches. Sensor body accommodates probe measuring temperature of evaporated water in cylinder.
The feasibility of realistic autonomous space manipulation tasks using multisensory information is shown through two experiments involving a fluid interchange system and a module interchange system. In both cases, autonomous location of the mating element, autonomous location of the guiding light target, mating, and demating of the system were performed. Specifically, vision-driven techniques were implemented to determine the arbitrary two-dimensional position and orientation of the mating elements as well as the arbitrary three-dimensional position and orientation of the light targets. The robotic system was also equipped with a force/torque sensor that continuously monitored the six components of force and torque exerted on the end effector. Using vision, force, torque, proximity, and touch sensors, the two experiments were completed successfully and autonomously.
MapX will provide elemental imaging at ≤100 micron spatial resolution over 2.5 X 2.5 centimeter areas, yielding elemental chemistry at or below the scale length where many relict physical, chemical, and biological features can be imaged and interpreted in ancient rocks. MapX is a full-frame spectroscopic imager positioned on soil or regolith with touch sensors. During an analysis, an X-ray source (tube or radioisotope) bombards the sample surface with X-rays or αlpha-particles / gamma rays, resulting in sample X-ray Fluorescence (XRF). Fluoresced X-rays pass through an X-ray lens (X-ray μ-Pore Optic, "MPO") that projects a spatially resolved image of the X-rays onto a CCD. The CCD is operated in single photon counting mode so that the positions and energies of individual photons are retained. In a single analysis, several thousand frames are stored and processed. A MapX experiment provides elemental maps having a spatial resolution of ≤100 micron and quantitative XRF spectra from Regions of Interest (ROI) 2 centimers ≤ x ≤ 100 micron. ROI are compared with known rock and mineral compositions to extrapolate the data to rock types and putative mineralogies. The MapX geometry is being refined with ray-tracing simulations and with synchrotron experiments at SLAC. Source requirements are being determined through Monte Carlo modeling and experiment using XMIMSIM [1], GEANT4 [2] and PyMca [3] and a dedicated XRF test fixture. A flow-down of requirements for both tube and radioisotope sources is being developed from these experiments. In addition to Mars lander and rover missions, MapX could be used for landed science on other airless bodies (Phobos/Deimos, Comet nucleus, asteroids, the Earth's moon, and the icy satellites of the outer planets, including Europa.
A hand/touch sensing system is described that, when mounted on a position-controlled manipulator, greatly expands the kinds of automated manipulation tasks that can be undertaken. Because of the variety of coordinate conversions, control equations, and completion criteria, control is necessarily dependent upon a small digital computer. The sensing system is designed both to be rugged and to sense the necessary touch and force information required to execute a wide range of manipulation tasks. The system consists of a six-axis wrist sensor, external touch sensors, and a pair of matrix jaw sensors. Details of the construction of the particular sensors, the integration of the end effector into the sensor system, and the control algorithms for using the sensor outputs to perform manipulation tasks automatically are discussed.
Robotic systems will be used as precursors to human exploration to explore the solar system and expand our knowledge of planetary surfaces. Robotic systems will also be used to build habitats and infrastructure required for human presence in space and on other planetary surfaces . Such robots will require a high level of intelligence and automation. The ability to flexibly manipulate their physical environment is one characteristic that makes humans so effective at these building and exploring tasks . The development of a generic autonomous grasp ing capability will greatly enhance the efficiency and ability of robotics to build, maintain and explore. To tele-operate a robot over vast distances of space, with long communication delays, has proven to be troublesome. Having an autonomous grasping capability that can react in real-time to disturbances or adapt to generic objects, without operator intervention, will reduce the probability of mishandled tools and samples and reduce the number of re-grasp attempts due to dropping. One aspect that separates humans from machines is a rich sensor set. We have the ability to feel objects and respond to forces and textures. The development of touch or tactile sensors for use on a robot that emulates human skin and nerves is the basis for this discussion. We will discuss the use of new piezo-electric and resistive materials that have emerged on the market with the intention of developing a touch sensitive sensor. With viable tacti le sensors we will be one step closer to developing an autonomous grasping capability.
Proximity, force-torque, touch and slippage sensors developed or applied by the JPL Teleoperator Project for remote manipulator control are described, including sensor data handling by computers for display and control. Examples are quoted showing the significance of these sensors for manual or computer control of manipulators. An interesting example is a proximity sensor system implemented for a four-claw JSC end effector and tested at the Shuttle Manipulator Training Facility of JSC. New sensing concepts aimed at simplifying the implementation of 'Smart Sensors for Smart Hands' in the space environment are discussed.
NASA's Ames Research Center has designed a simple but medically important device--one which holds temperature probes, called thermistors, to a person's skin without affecting the characteristics of the skin segment being measured. The device improves the accuracy of skin surface temperature measurements, valuable data in health evaluation. The need for such a device was recognized in the course of life science experiments at Ames. In earlier methods, the sensing head of the temperature probe was affixed to the patient's skin by tape or elastic bands. This created a heat variance which altered skin temperature readings. The Ames-developed thermistor holder is a plastic ring with tab extensions, shown in the upper photo on the chest, arm and leg of the patient undergoing examination. The ring holds the sensing head of the temperature probe and provides firm, constant pressure between the skin and the probe. The tabs help stabilize the ring and provide attachment points for the fastening tape or bands, which do not directly touch the sensor. With this new tool, it is possible to determine more accurately the physiological effects of strenuous exercise, particularly on the treadmill. The holder is commercially available from Yellow Springs Instrument Company, Inc., Yellow Springs, Ohio, which is producing the device under a NASA patent license.
Matrix of pressure sensors determines shape and pressure distribution of object in contact with its surface. Output can be used to develop pressure map of objects' surface and displayed as array of alphanumeric symbols on video monitor.
This project seeks to develop an optical method to reduce graphite oxide into graphene efficiently and in larger formats than currently available. Current reduction methods are expensive, time-consuming or restricted to small, limited formats. Graphene has potential uses in ultracapacitors, energy storage, solar cells, flexible and light-weight circuits, touch screens, and chemical sensors. In addition, graphite oxide is a sustainable material that can be produced from any form of carbon, making this method environmentally friendly and adaptable for in-situ reduction.
The Orion vehicle will be required to perform rendezvous, proximity operations, and docking with the International Space Station (ISS) and the Earth Departure Stage (EDS)/Lunar Landing Vehicle (LLV) stack in Low Earth Orbit (LEO) as well as with the Lunar Landing Vehicle in Low Lunar Orbit (LLO). The RPOD system, which consists of sensors, actuators, and software is being designed to be flexible and robust enough to perform RPOD with different vehicles in different environments. This paper will describe the design and the analysis which has been performed to date to allow the vehicle to perform its mission. Since the RPOD design touches on many areas such as sensors selection and placement, trajectory design, navigation performance, and effector performance, it is inherently a systems design problem. This paper will address each of these issues in order to demonstrate how the Orion RPOD has been designed to accommodate and meet all the requirements levied on the system.
An algorithm has been developed to solve the problem of mapping from (1) a glove instrumented with joint-angle sensors to (2) an anthropomorphic robot hand. Such a mapping is needed to generate control signals to make the robot hand mimic the configuration of the hand of a human attempting to control the robot. The mapping problem is complicated by uncertainties in sensor locations caused by variations in sizes and shapes of hands and variations in the fit of the glove. The present mapping algorithm is robust in the face of these uncertainties, largely because it includes a calibration sub-algorithm that inherently adapts the mapping to the specific hand and glove, without need for measuring the hand and without regard for goodness of fit. The algorithm utilizes a forward-kinematics model of the glove derived from documentation provided by the manufacturer of the glove. In this case, forward-kinematics model signifies a mathematical model of the glove fingertip positions as functions of the sensor readings. More specifically, given the sensor readings, the forward-kinematics model calculates the glove fingertip positions in a Cartesian reference frame nominally attached to the palm. The algorithm also utilizes an inverse-kinematics model of the robot hand. In this case, inverse-kinematics model signifies a mathematical model of the robot finger-joint angles as functions of the robot fingertip positions. Again, more specifically, the inverse-kinematics model calculates the finger-joint commands needed to place the fingertips at specified positions in a Cartesian reference frame that is attached to the palm of the robot hand and that nominally corresponds to the Cartesian reference frame attached to the palm of the glove. Initially, because of the aforementioned uncertainties, the glove fingertip positions calculated by the forwardkinematics model in the glove Cartesian reference frame cannot be expected to match the robot fingertip positions in the robot-hand Cartesian reference frame. A calibration must be performed to make the glove and robot-hand fingertip positions correspond more precisely. The calibration procedure involves a few simple hand poses designed to provide well-defined fingertip positions. One of the poses is a fist. In each of the other poses, a finger touches the thumb. The calibration subalgorithm uses the sensor readings from these poses to modify the kinematical models to make the two sets of fingertip positions agree more closely.
Beginning with the mathematical prediction of planetary orbits in the early seventeenth century up through the most recent developments in sensor fusion methods, many techniques have emerged that can be employed on the problem of endo and exoatmospheric trajectory estimation. Although early methods were ad hoc, the twentieth century saw the emergence of many systematic approaches to estimation theory that produced a wealth of useful techniques. The broad genesis of estimation theory has resulted in an equally broad array of mathematical principles, methods and vocabulary. Among the fundamental ideas and methods that are briefly touched on are batch and sequential processing, smoothing, estimation, and prediction, sensor fusion, sensor fusion architectures, data association, Bayesian and non Bayesian filtering, the family of Kalman filters, models of the dynamics of the phases of a rocket's flight, and asynchronous, delayed, and asequent data. Along the way, a few trajectory estimation issues are addressed and much of the vocabulary is defined.
A relatively rapid, economical process has been devised for patterning a thin film of indium tin oxide (ITO) that has been deposited on a polyester film. ITO is a transparent, electrically conductive substance made from a mixture of indium oxide and tin oxide that is commonly used in touch panels, liquid-crystal and plasma display devices, gas sensors, and solar photovoltaic panels. In a typical application, the ITO film must be patterned to form electrodes, current collectors, and the like. Heretofore it has been common practice to pattern an ITO film by means of either a laser ablation process or a photolithography/etching process. The laser ablation process includes the use of expensive equipment to precisely position and focus a laser. The photolithography/etching process is time-consuming. The present process is a variant of the direct toner process an inexpensive but often highly effective process for patterning conductors for printed circuits. Relative to a conventional photolithography/ etching process, this process is simpler, takes less time, and is less expensive. This process involves equipment that costs less than $500 (at 2005 prices) and enables patterning of an ITO film in a process time of less than about a half hour.
The inversion of electromagnetic information to physical and biological properties of the water column is a notoriously difficult problem, yet fundamental to our ability of understanding aquatic processes on large time and space scales. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will discuss research integrating advanced biological and radiative modeling, high-end computation, and machine learning to develop a portable global processor for simultaneous retrieval of atmosphere and water optics for diverse aquatic systems from the open and coastal ocean to optically extreme inland waters and harmful algal blooms. We will discuss some of the basic concepts behind the forward modeling approach including DEAP, the novel Distributed Equivalent Algal Populations model, for developing large spectral libraries of aquatic particle optics to aid in our ability to distinguish phytoplankton functional types (PFTs) and inorganic material, as well as other factors which enable comprehensive modeling from the benthos to top-of-atmosphere (TOA). This information is being used to understand how we can leverage next-generation deep learning methods for maximum information retrieval and rapid image processing, while also providing capabilities to identify minimum sensor spectral requirements necessary for certain aquatic applications. Further, I will touch on how we envision this research to enable the aquatic community for science discovery and how we are moving closer towards the capability for high-fidelity global analysis of aquatic ecosystems.