635 research outputs found
Dynamics, control and sensor issues pertinent to robotic hands for the EVA retriever system
Basic dynamics, sensor, control, and related artificial intelligence issues pertinent to smart robotic hands for the Extra Vehicular Activity (EVA) Retriever system are summarized and discussed. These smart hands are to be used as end effectors on arms attached to manned maneuvering units (MMU). The Retriever robotic systems comprised of MMU, arm and smart hands, are being developed to aid crewmen in the performance of routine EVA tasks including tool and object retrieval. The ultimate goal is to enhance the effectiveness of EVA crewmen
Ground Robotic Hand Applications for the Space Program study (GRASP)
This document reports on a NASA-STDP effort to address research interests of the NASA Kennedy Space Center (KSC) through a study entitled, Ground Robotic-Hand Applications for the Space Program (GRASP). The primary objective of the GRASP study was to identify beneficial applications of specialized end-effectors and robotic hand devices for automating any ground operations which are performed at the Kennedy Space Center. Thus, operations for expendable vehicles, the Space Shuttle and its components, and all payloads were included in the study. Typical benefits of automating operations, or augmenting human operators performing physical tasks, include: reduced costs; enhanced safety and reliability; and reduced processing turnaround time
Sensors for Robotic Hands: A Survey of State of the Art
Recent decades have seen significant progress in the field of artificial hands. Most of the
surveys, which try to capture the latest developments in this field, focused on actuation and control systems of these devices. In this paper, our goal is to provide a comprehensive survey of the sensors for artificial hands. In order to present the evolution of the field, we cover five year periods starting at the turn of the millennium. At each period, we present the robot hands with a focus on their sensor systems dividing them into categories, such as prosthetics, research devices, and industrial end-effectors.We also cover the sensors developed for robot hand usage in each era. Finally, the period between 2010 and 2015 introduces the reader to the state of the art and also hints to the future directions in the sensor development for artificial hands
Graphite immobilisation in glass composite materials
Irradiated graphite is a problematic nuclear waste stream and currently raises significant concern
worldwide in identifying its long-term disposal route. This thesis describes the use of glass
materials for the immobilisation of irradiated graphite prepared by microwave, conventional and
sparks plasma sintering methods. Several potential glass compositions namely iron phosphate,
aluminoborosilicate, calcium aluminosilicate, alkali borosilicate and obsidian were considered
for the immobilisation of various loadings of graphite simulating irradiated graphite. The
properties of the samples produced using different processing methods are compared selectively.
An investigation of microwave processing using an iron phosphate glass composition revealed
that full reaction of the raw materials and formation of a glass melt occurs with consequent
removal of porosity at 8 minutes microwave processing. When graphite is present, iron
phosphate crystalline phases are formed with much higher levels of residual porosity of up to 43
% than in the samples prepared using conventional sintering under argon. It is found that
graphite reacts with the microwave field when in powder form but this reaction is minimised
when the graphite is incorporated into a pellet, and that the graphite also impedes sintering of the
glass. Mössbauer spectroscopy indicates that reduction of iron occurs with concomitant graphite
oxidation. The production of graphite-glass samples using various powdered glass compositions
by conventional sintering method still resulted in high porosity with an average of 6-17 % for
graphite loadings of 20-25 wt%. Due to the use of pre-made glasses and controlled sintering
parameters, the loss of graphite from the total mass is reduced compared to the microwaved
samples; the average mass loss is < 0.8 %. The complication of iron oxidation and reduction is
present in all the iron containing base glasses considered and this increases the total porosity of
the graphite-glass samples. It is concluded that the presence of iron in the raw materials or base
glasses as an encapsulation media for the immobilisation of the irradiated graphite waste is not
advisable. The production of glass and graphite-glass samples based calcium aluminosilicate
composition by spark plasma sintering method is found highly suitable for the immobilisation of
irradiated graphite wastes. The advantages of the method includes short processing time i.e. < 40
minutes, improved sintering transport mechanisms, limited graphite oxidation, low porosity (1-4
%) and acceptable tensile strength (2-7 MPa). The most promising samples prepared using spark
plasma sintering method were loaded with 30-50 wt% graphite
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Acquisition and Interpretation of 3-D Sensor Data from Touch
Acquisition of 3-D scene information has focused on either passive 2-D imaging methods (stereopsis, structure from motion etc.) or 3-D range sensing methods (structured lighting, laser scanning etc.). Little work has been done in using active touch sensing with a multi-fingered robotic hand to acquire scene descriptions, even though it is a well developed human capability. Touch sensing differs from other more passive sensing modalities such as vision in a number of ways. A multi-fingered robotic hand with touch sensors can probe, move, and change its environment. This imposes a level of control on the sensing that makes it typically more difficult than traditional passive sensors in which active control is not an issue. Secondly, touch sensing generates far less data than vision methods; this is especially intriguing in light of psychological evidence that shows humans can recover shape and a number of other object attributes very reliably using touch alone. Future robotic systems will need to use dextrous robotic hands for tasks such as grasping, manipulation, assembly, inspection and object recognition. This paper describes our use of touch sensing as part of a larger system we are building for 3-D shape recovery and object recognition using touch and vision methods. It focuses on three exploratory procedures we have built to acquire and interpret sparse 3-D touch data: grasping by containment, planar surface exploration and surface contour exploration. Experimental results for each of these procedures are presented
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