37 research outputs found

    Ground Robotic Hand Applications for the Space Program study (GRASP)

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    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

    Scalability study for robotic hand platform

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    The goal of this thesis project was to determine the lower limit of scale for the RIT robotic grasping hand. This was accomplished using a combination of computer simulation and experimental studies. A force analysis was conducted to determine the size of air muscles required to achieve appropriate contact forces at a smaller scale. Input variables, such as the actuation force and tendon return force, were determined experimentally. A dynamic computer model of the hand system was then created using Recurdyn. This was used to predict the contact (grasping) force of the fingers at full-scale, half-scale, and quarter-scale. Correlation between the computer model and physical testing was achieved for both a life-size and half-scale finger assembly. To further demonstrate the scalability of the hand design, both half and quarter-scale robotic hand rapid prototype assemblies were built using 3D printing techniques. This thesis work identified the point where further miniaturization would require a change in the manufacturing process to micro-fabrication. Several techniques were compared as potential methods for making a production intent quarter-scale robotic hand. Investment casting, Swiss machining, and Selective Laser Sintering were the manufacturing techniques considered. A quarter-scale robotic hand tested the limits of each technology. Below this scale, micro-machining would be required. The break point for the current actuation method, air muscles, was also explored. Below the quarter-scale, an alternative actuation method would also be required. Electroactive Polymers were discussed as an option for the micro-scale. In summary, a dynamic model of the RIT robotic grasping hand was created and validated as scalable at full and half-scales. The model was then used to predict finger contact forces at the quarter-scale. The quarter-scale was identified as the break point in terms of the current RIT robotic grasping hand based on both manufacturing and actuation. A novel, prototype quarter-scale robotic hand assembly was successfully built by an additive manufacturing process, a high resolution 3D printer. However, further miniaturization would require alternate manufacturing techniques and actuation mechanisms

    感度調整可能な3軸マルチモーダルスキンセンサーモジュールの開発

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    早大学位記番号:新8538早稲田大

    A Methodology Towards Comprehensive Evaluation of Shape Memory Alloy Actuators for Prosthetic Finger Design

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    Presently, DC motors are the actuator of choice within intelligent upper limb prostheses. However, the weight and dimensions associated with suitable DC motors are not always compatible with the geometric restrictions of a prosthetic hand; reducing available degrees of freedom and ultimately rendering the prosthesis uncomfortable for the end-user. As a result, the search is on-going to find a more appropriate actuation solution that is lightweight, noiseless, strong and cheap. Shape memory alloy (SMA) actuators offer the potential to meet these requirements. To date, no viable upper limb prosthesis using SMA actuators has been developed. The primary reasons lie in low force generation as a result of unsuitable actuator designs, and significant difficulties in control owing to the highly nonlinear response of SMAs when subjected to joule heating. This work presents a novel and comprehensive methodology to facilitate evaluation of SMA bundle actuators for prosthetic finger design. SMA bundle actuators feature multiple SMA wires in parallel. This allows for increased force generation without compromising on dynamic performance. The SMA bundle actuator is tasked with reproducing the typical forces and contractions associated with the human finger in a prosthetic finger design, whilst maintaining a high degree of energy efficiency. A novel approach to SMA control is employed, whereby an adaptive controller is developed and tuned using the underlying thermo-mechanical principles of operation of SMA wires. A mathematical simulation of the kinematics and dynamics of motion provides a platform for designing, optimizing and evaluating suitable SMA bundle actuators offline. This significantly reduces the time and cost involved in implementing an appropriate actuation solution. Experimental results show iii that the performance of SMA bundle actuators is favourable for prosthesis applications. Phalangeal tip forces are shown to improve significantly through bundling of SMA wire actuators, while dynamic performance is maintained owing to the design and implementation of the selected control strategy. The work is intended to serve as a roadmap for fellow researchers seeking to design, implement and control SMA bundle actuators in a prosthesis design. Furthermore, the methodology can also be adopted to serve as a guide in the evaluation of other non-conventional actuation technologies in alternative applications

    複数の静電容量型柔軟触覚デバイスを用いた三軸力センサの開発

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    早大学位記番号:新7325早稲田大

    Pattern recognition-based real-time myoelectric control for anthropomorphic robotic systems : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Mechatronics at Massey University, Manawatū, New Zealand

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    All copyrighted Figures have been removed but may be accessed via their source cited in their respective captions.Advanced human-computer interaction (HCI) or human-machine interaction (HMI) aims to help humans interact with computers smartly. Biosignal-based technology is one of the most promising approaches in developing intelligent HCI systems. As a means of convenient and non-invasive biosignal-based intelligent control, myoelectric control identifies human movement intentions from electromyogram (EMG) signals recorded on muscles to realise intelligent control of robotic systems. Although the history of myoelectric control research has been more than half a century, commercial myoelectric-controlled devices are still mostly based on those early threshold-based methods. The emerging pattern recognition-based myoelectric control has remained an active research topic in laboratories because of insufficient reliability and robustness. This research focuses on pattern recognition-based myoelectric control. Up to now, most of effort in pattern recognition-based myoelectric control research has been invested in improving EMG pattern classification accuracy. However, high classification accuracy cannot directly lead to high controllability and usability for EMG-driven systems. This suggests that a complete system that is composed of relevant modules, including EMG acquisition, pattern recognition-based gesture discrimination, output equipment and its controller, is desirable and helpful as a developing and validating platform that is able to closely emulate real-world situations to promote research in myoelectric control. This research aims at investigating feasible and effective EMG signal processing and pattern recognition methods to extract useful information contained in EMG signals to establish an intelligent, compact and economical biosignal-based robotic control system. The research work includes in-depth study on existing pattern recognition-based methodologies, investigation on effective EMG signal capturing and data processing, EMG-based control system development, and anthropomorphic robotic hand design. The contributions of this research are mainly in following three aspects: Developed precision electronic surface EMG (sEMG) acquisition methods that are able to collect high quality sEMG signals. The first method was designed in a single-ended signalling manner by using monolithic instrumentation amplifiers to determine and evaluate the analog sEMG signal processing chain architecture and circuit parameters. This method was then evolved into a fully differential analog sEMG detection and collection method that uses common commercial electronic components to implement all analog sEMG amplification and filtering stages in a fully differential way. The proposed fully differential sEMG detection and collection method is capable of offering a higher signal-to-noise ratio in noisy environments than the single-ended method by making full use of inherent common-mode noise rejection capability of balanced signalling. To the best of my knowledge, the literature study has not found similar methods that implement the entire analog sEMG amplification and filtering chain in a fully differential way by using common commercial electronic components. Investigated and developed a reliable EMG pattern recognition-based real-time gesture discrimination approach. Necessary functional modules for real-time gesture discrimination were identified and implemented using appropriate algorithms. Special attention was paid to the investigation and comparison of representative features and classifiers for improving accuracy and robustness. A novel EMG feature set was proposed to improve the performance of EMG pattern recognition. Designed an anthropomorphic robotic hand construction methodology for myoelectric control validation on a physical platform similar to in real-world situations. The natural anatomical structure of the human hand was imitated to kinematically model the robotic hand. The proposed robotic hand is a highly underactuated mechanism, featuring 14 degrees of freedom and three degrees of actuation. This research carried out an in-depth investigation into EMG data acquisition and EMG signal pattern recognition. A series of experiments were conducted in EMG signal processing and system development. The final myoelectric-controlled robotic hand system and the system testing confirmed the effectiveness of the proposed methods for surface EMG acquisition and human hand gesture discrimination. To verify and demonstrate the proposed myoelectric control system, real-time tests were conducted onto the anthropomorphic prototype robotic hand. Currently, the system is able to identify five patterns in real time, including hand open, hand close, wrist flexion, wrist extension and the rest state. With more motion patterns added in, this system has the potential to identify more hand movements. The research has generated a few journal and international conference publications

    Towards observable haptics: Novel sensors for capturing tactile interaction patterns

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    Kõiva R. Towards observable haptics: Novel sensors for capturing tactile interaction patterns. Bielefeld: Bielefeld University; 2014.Touch is one of the primary senses humans use when performing coordinated interaction, but the lack of a sense of touch in the majority of contemporary interactive technical systems, such as robots, which operate in non-deterministic environments, results in interactions that can at best be described as clumsy. Observing human haptics and extracting the salient information from the gathered data is not only relevant if we are to try to understand the involved underlying cognitive processes, but should also provide us with significant clues to design future intelligent interactive systems. Such systems could one day help to take the burden of tedious tasks off our hands in a similar fashion to how industrial robots revolutionized manufacturing. The aim of the work in this thesis was to provide significant advancements in tactile sensing technology, and thus move us a step closer to realizing this goal. The contributions contained herein can be broken into two major parts. The first part investigates capturing interaction patterns in humans with the goals of better understanding manual intelligence and improving the lives of hand amputees, while the second part is focused on augmenting technical systems with a sense of touch. tacTiles, a wireless tactile sensitive surface element attached to a deformable textile, was developed to capture human full-body interactions with large surfaces we come into contact with in our daily lives, such as floors, chairs, sofas or other furniture. The Tactile Dataglove, iObject and the Tactile Pen were developed especially to observe human manual intelligence. Whereas iObject allows motion sensing and a higher definition tactile signal to be captured than the Tactile Dataglove (220 tactile cells in the first iObject prototype versus 54 cells in the glove), the wearable glove makes haptic interactions with arbitrary objects observable. The Tactile Pen was designed to measure grip force during handwriting in order to better facilitate therapeutic treatment assessments. These sensors have already been extensively used by various research groups, including our own, to gain a better understanding of human manual intelligence. The Finger-Force-Linear-Sensor and the Tactile Bracelet are two novel sensors that were developed to facilitate more natural control of dexterous multi Degree-of-Freedom (DOF) hand prostheses. The Finger-Force-Linear-Sensor is a very accurate bidirectional single finger force ground-truth measurement device that was designed to enable testing and development of single finger forces and muscle activations mapping algorithms. The Tactile Bracelet was designed with the goal to provide a more robust and intuitive means of control for multi-DOF hand prostheses by measuring the muscle bulgings of the remnant muscles of lower arm amputees. It is currently in development and will eventually cover the complete forearm circumference with high spatial resolution tactile sensitive surfaces. An experiment involving a large number of lower arm amputees has already been planned. The Modular flat tactile sensor system, the Fabric-based touch sensitive artificial skin and the 3D shaped tactile sensor were developed to cover and to add touch sensing capabilities to the surfaces of technical systems. The rapid augmentation of systems with a sense of touch was the main goal of the modular flat tactile sensor system. The developed sensor modules can be used alone or in an array to form larger tactile sensitive surfaces such as tactile sensitive tabletops. As many robots have curved surfaces, using flat rigid modules severely limits the areas that can be covered with tactile sensors. The Fabric-based tactile sensor, originally developed to form a tactile dataglove for human hands, can with minor modifications also function as an artificial skin for technical systems. Finally, the 3D shaped tactile sensor based on Laser-Direct-Structuring technology is a novel tactile sensor that has a true 3D shape and provides high sensitivity and a high spatial resolution. These sensors take us further along the path towards creating general purpose technical systems that in time can be of great help to us in our daily lives. The desired tactile sensor characteristics differ significantly according to which haptic interaction patterns we wish to measure. Large tactile sensor arrays that are used to capture full body haptic interactions with floors and upholstered furniture, or that are designed to cover large areas of technical system surfaces, need to be scalable, have low power consumption and should ideally have a low material cost. Two examples of such sensors are tacTiles and the Fabric-based sensor for curved surfaces. At the other end of the tactile sensor development spectrum, if we want to observe manual interactions, high spatial and temporal resolution are crucial to enable the measurement of fine grasping and manipulation actions. Our fingertips contain the highest density area of mechanoreceptors, the organs that sense mechanical pressure and distortions. Thus, to construct biologically inspired anthropomorphic robotic hands, the artificial tactile sensors for the fingertips require similar high-fidelity sensors with surfaces that are curved under small bending radii in 2 dimensions, have high spatial densities, while simultaneously providing high sensitivity. With the fingertip tactile sensor, designed to fit the Shadow Robot Hands' fingers, I show that such sensors can indeed be constructed in the 3D-shaped high spatial resolution tactile sensor section of my thesis. With my work I have made a significant contribution towards making haptics more observable. I achieved this by developing a high number of novel tactile sensors that are usable, give a deeper insight into human haptic interactions, have great potential to help amputees and that make technical systems, such as robots, more capable

    Parametric mechanical design and optimisation of the Canterbury Hand.

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    As part of worldwide research humanoid robots have been developed for household, industrial and exploratory applications. If such robots are to interact with people and human created environments they will require human-like hands. The objective of this thesis was the parametric design and optimisation of a dexterous, and anthropomorphic robotic end effector. Known as the ‘Canterbury Hand’ it has 11 degree of freedoms with four fingers and a thumb. The hand has applications for dexterous teleoperation and object manipulation in industrial, hazardous or uncertain environments such as orbital robotics. The human hand was analysed so that the Canterbury Hand could copy its motions, appearance and grasp types. An analysis of the current literature on experimental prosthetic and robotic hands was also carried out. A disadvantage of many of these hand designs was that they were remotely powered using large, heavy actuator packs. The advantage of the Canterbury Hand is that it has been designed to hold the motors, wires, and circuit boards entirely within itself; although a belt carried battery pack is required. The hand was modelled using a parametric 3D computer aided design (CAD) program. Two different configurations of the hand were created in the model. One configuration, as a dexterous robot hand, used Ø13mm 3 Watt DC motors, while the other used Ø10mm, 0.5 Watt DC motors (although this hand is still slightly too large for a general prosthesis). The parts within the hand were modelled to permit changes to the geometry. This was necessary for the optimisation process. The bearing geometry of the finger and thumb linkages, as well as the thumb rotation axis was optimised for anthropomorphic motion, appearance and increased force output. A design table within a spreadsheet was created to interact with the CAD models of the hand to quickly implement the optimised geometry. The work reported in this thesis has shown the possibilities for parametric design and optimisation of an anthropomorphic, dexterous robotic hand

    Parametric mechanical design and optimisation of the Canterbury Hand.

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    As part of worldwide research humanoid robots have been developed for household, industrial and exploratory applications. If such robots are to interact with people and human created environments they will require human-like hands. The objective of this thesis was the parametric design and optimisation of a dexterous, and anthropomorphic robotic end effector. Known as the ‘Canterbury Hand’ it has 11 degree of freedoms with four fingers and a thumb. The hand has applications for dexterous teleoperation and object manipulation in industrial, hazardous or uncertain environments such as orbital robotics. The human hand was analysed so that the Canterbury Hand could copy its motions, appearance and grasp types. An analysis of the current literature on experimental prosthetic and robotic hands was also carried out. A disadvantage of many of these hand designs was that they were remotely powered using large, heavy actuator packs. The advantage of the Canterbury Hand is that it has been designed to hold the motors, wires, and circuit boards entirely within itself; although a belt carried battery pack is required. The hand was modelled using a parametric 3D computer aided design (CAD) program. Two different configurations of the hand were created in the model. One configuration, as a dexterous robot hand, used Ø13mm 3 Watt DC motors, while the other used Ø10mm, 0.5 Watt DC motors (although this hand is still slightly too large for a general prosthesis). The parts within the hand were modelled to permit changes to the geometry. This was necessary for the optimisation process. The bearing geometry of the finger and thumb linkages, as well as the thumb rotation axis was optimised for anthropomorphic motion, appearance and increased force output. A design table within a spreadsheet was created to interact with the CAD models of the hand to quickly implement the optimised geometry. The work reported in this thesis has shown the possibilities for parametric design and optimisation of an anthropomorphic, dexterous robotic hand
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