Reduction of dimensionality of a cellular actuator array for driving a robotic hand

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.Includes bibliographical references (p. 89-93).In an attempt to explore an alternative to today's robot actuators, a new approach to artificial muscle actuator design and control is presented. The objective of this research is to coordinate the multitude of artificial muscle actuator axes for a large DOF (degree of freedom) robotic system based on dimensionality reduction. An array of SMA actuators is segmented into many independently controlled, spatially discrete volumes, each contributing a small displacement to create a large motion. Segmented Binary Control is proposed where each segment is controlled in an on-off manner, creating a stepper-motor like actuator. This overcomes hysteresis and other nonlinearities of the actuator material. The segmented cellular architecture of SMA wires is extended to a multi-axis actuator array by arranging the segments in a two-dimensional array. The multi-axis control is streamlined and coordinated using a grouping of segments called C-segments in order to activate multiple links of a robot mechanism in a coordinated manner. This allows control of large DOF with a small number of controls. The proposed approach is inspired by the segmented architecture of biological muscles and synergies, a strategy of grouping output variables to simplify the control of large number of muscles. Data from various hand postures are collected using data glove and used in creating the C-segment design that is capable of performing the given postures. A lightweight Robotic Hand with 16 DOF is built using shape memory alloy actuators. This hand weighs less than 1kg including 32 SMA actuators and control circuitry. Eight C-segments that are ON-off controlled are used to create sixteen given postures. In the future, this approach can be applied to applications where the control signal is inherently limited due to limited amount of information that can be extracted or transferred to the robot, such as brain machine interface and tele-operation.by Kyu-Jin Cho.Ph.D

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

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

Design and Fabrication of Fabric ReinforcedTextile Actuators forSoft Robotic Graspers

abstract: Wearable assistive devices have been greatly improved thanks to advancements made in soft robotics, even creation soft extra arms for paralyzed patients. Grasping remains an active area of research of soft extra limbs. Soft robotics allow the creation of grippers that due to their inherit compliance making them lightweight, safer for human interactions, more robust in unknown environments and simpler to control than their rigid counterparts. A current problem in soft robotics is the lack of seamless integration of soft grippers into wearable devices, which is in part due to the use of elastomeric materials used for the creation of most of these grippers. This work introduces fabric-reinforced textile actuators (FRTA). The selection of materials, design logic of the fabric reinforcement layer and fabrication method are discussed. The relationship between the fabric reinforcement characteristics and the actuator deformation is studied and experimentally verified. The FRTA are made of a combination of a hyper-elastic fabric material with a stiffer fabric reinforcement on top. In this thesis, the design, fabrication, and evaluation of FRTAs are explored. It is shown that by varying the geometry of the reinforcement layer, a variety of motion can be achieve such as axial extension, radial expansion, bending, and twisting along its central axis. Multi-segmented actuators can be created by tailoring different sections of fabric-reinforcements together in order to generate a combination of motions to perform specific tasks. The applicability of this actuators for soft grippers is demonstrated by designing and providing preliminary evaluation of an anthropomorphic soft robotic hand capable of grasping daily living objects of various size and shapes.Dissertation/ThesisMasters Thesis Biomedical Engineering 201

Thermo-Mechanical Modeling and the Application of Coiled Polymer Actuators in Soft Robotics and Biomimetics

Coiled polymer actuators (CPA) are a recently discovered smart material. Due to their large tensile stoke and power densities they are often used as actuators or artificial muscles. CPA’s are fabricated from a polymer fiber, typically nylon, mechanically twisted into a coil or coiled around a mandrel and annealed. When heated over the glass transition temperature they can contract, expand or exhibit torsional actuation, depending on the fabrication method and end conditions. The fabrication and application of CPA is well documented and has made many innovations in the fields of smart materials, soft robotics and the likes. However, there is a lack of knowledge in the modeling of CPA, this is partly due to the novelty of the actuator. To address this problem, a theoretical and experimental investigation of thermo-mechanical response is proposed. An energy and variational methods and continuum mechanics approach is utilized with numerical methods to describe the actuation response. To verify the model, the numerical simulation displacement response is compared to CPA samples that are fabricated and experimentally tested in lab using a dynamic machine analyzer (DMA). The results indicate the proposed model accurately predict the actuation response of the CPA under thermal loading. The numerical simulation and experimental comparison is in good agreement and helps to further understand the underlining cause of the actuation behavior of the coiled polymer actuator. Furthermore, the model can be used in application purposes where the results of the model can be used in designing and optimizing soft robotics using CPA as an artificial muscle. In addition to the numerical and experimental investigation of the CPA’s thermomechanical response, an application in biomimetics is being studied. Biomimetics is an interdisciplinary field in engineering and sciences used to overcoming complex human challenges by designing and fabricating materials and systems modeled after nature. Applications of biomimicry can be seen in many technological advancements such as catheters, hearing devices, and artificial appendages such as arms, legs and fingers. The inspiration for this study is the hydrofoil like structured pectoral fin of the Harbor Porpoise whale. Studies will be focused on understanding the fluid forces acting on the pectoral fin. First and foremost, a highly accurate pectoral fin is fabricated from CT scans of a Harbor Porpoise whale fin. 3D models are obtained using Simpleware ScanIP and post-processed in Autodesk for 3D printing components, which were used to assemble to artificial whale fin. An array of thermally driven Coiled Polymer Actuators (CPA) fabricated from Nylon and heated with Nichrome are used as artificial muscles for actuating the pectoral fin. CPA’s were used for their similarity to biological muscles and are of great interest due to its high specific power and large actuation stroke. A simple control circuit for supplying power to the Nichrome heating wires is developed using an Arduino and motor drivers. The displacement over time of the fin is tested and captured using a laser distant sensor. The fin shows a great displacement response, largely deflecting in both direction relative to its size. The artificial fin was then be further utilized in our studies. The fluid forces imposed on the fin while in motion was measured in a laboratorycontrolled setting. A low-velocity belt driven tow tank was used to displace the artificial fin through water. The tow velocity was varied, and the drag force measurements were taken with and without fin actuation using a cantilever beam load cell. A theoretical derived drag force was compared to the experimental drag data and showed good comparison for the non-actuated fin. Increased drag was exhibited with actuation in both directions when towed through water. This demonstrates the ability of the fin to manipulate is geometry to change the drag force on itself serving as a controllable hydrofoil. We hope to elaborate on this ability and apply it to mechanical designs such as under and above water vehicles

Doctor of Philosophy

dissertationShape Memory Alloy (SMA) actuators are compact and have high force-to-weight ratios, making them strong candidates to actuate robots, exoskeletons, and prosthetics. However, these actuators are thermomechanical in nature and slow cooling rates can limit their performance. Electricity can resistively heat the SMA actuators very quickly to produce contraction. To improve the convective cooling, SMA wires have been embedded in vascular networks, allowing cold fluid to pass across the actuators and extend them faster. The vascular network can also deliver hot fluid to heat and contract the wire. To minimize the weight and size of the control hardware for the vascular and electrical networks, a scalable NxN architecture has been implemented that allows for 2N control devices to be shared amongst N2 actuators. This Network Array Architecture (NAA) allows each actuator to be controlled individually or in discrete subarrays. However, this architecture does not allow all combinations of actuators to be activated simultaneously; therefore a sequence of control commands may be required to achieve the complete desired actuation. This dissertation presents the development of an intelligent controller for large arrays of wet SMA actuators with electric and thermofluidic inputs. The controller uses graph theory to identify a sequence to control commands to optimize the performance of the actuators. By treating each actuator as binary (contracted / extended), the collected states of an actuator array can be represented as nodes of the graph and the discrete NAA control commands as the graph edges. By weighting the costs of the graph edges (actuation times, energy), graph theory algorithms can find a set of control commands to transition the array to the desired state with specific performance characteristics. NAA results in a multi-graph that has a large number of nodes (2NxN) and is highly interconnected, causing problems with scalability. The search algorithm has incorporated an expanding wavefront algorithm to construct only a small portion of the graph as needed. The computational cost to construct the graph has been minimized by using bitwise operations and the discrete nature of the array of binary actuators and the NAA control commands. The algorithm was implemented in MATLAB and it is able to identify the optimal solution for a 4x4 array with more than 14 million edges. By using an expanding wavefront, the algorithm, on average, explored less than 100 edges (<0.01%) in 0.03 seconds. A 6x6 array was optimized in 0.7 seconds, exploring just 2400 edges

Contemporary Robotics

This book book is a collection of 18 chapters written by internationally recognized experts and well-known professionals of the field. Chapters contribute to diverse facets of contemporary robotics and autonomous systems. The volume is organized in four thematic parts according to the main subjects, regarding the recent advances in the contemporary robotics. The first thematic topics of the book are devoted to the theoretical issues. This includes development of algorithms for automatic trajectory generation using redudancy resolution scheme, intelligent algorithms for robotic grasping, modelling approach for reactive mode handling of flexible manufacturing and design of an advanced controller for robot manipulators. The second part of the book deals with different aspects of robot calibration and sensing. This includes a geometric and treshold calibration of a multiple robotic line-vision system, robot-based inline 2D/3D quality monitoring using picture-giving and laser triangulation, and a study on prospective polymer composite materials for flexible tactile sensors. The third part addresses issues of mobile robots and multi-agent systems, including SLAM of mobile robots based on fusion of odometry and visual data, configuration of a localization system by a team of mobile robots, development of generic real-time motion controller for differential mobile robots, control of fuel cells of mobile robots, modelling of omni-directional wheeled-based robots, building of hunter- hybrid tracking environment, as well as design of a cooperative control in distributed population-based multi-agent approach. The fourth part presents recent approaches and results in humanoid and bioinspirative robotics. It deals with design of adaptive control of anthropomorphic biped gait, building of dynamic-based simulation for humanoid robot walking, building controller for perceptual motor control dynamics of humans and biomimetic approach to control mechatronic structure using smart materials

Frontiers of robotic endoscopic capsules: a review

Digestive diseases are a major burden for society and healthcare systems, and with an aging population, the importance of their effective management will become critical. Healthcare systems worldwide already struggle to insure quality and affordability of healthcare delivery and this will be a significant challenge in the midterm future. Wireless capsule endoscopy (WCE), introduced in 2000 by Given Imaging Ltd., is an example of disruptive technology and represents an attractive alternative to traditional diagnostic techniques. WCE overcomes conventional endoscopy enabling inspection of the digestive system without discomfort or the need for sedation. Thus, it has the advantage of encouraging patients to undergo gastrointestinal (GI) tract examinations and of facilitating mass screening programmes. With the integration of further capabilities based on microrobotics, e.g. active locomotion and embedded therapeutic modules, WCE could become the key-technology for GI diagnosis and treatment. This review presents a research update on WCE and describes the state-of-the-art of current endoscopic devices with a focus on research-oriented robotic capsule endoscopes enabled by microsystem technologies. The article also presents a visionary perspective on WCE potential for screening, diagnostic and therapeutic endoscopic procedures

Functional Soft Robotic Actuators Based on Dielectric Elastomers

Dielectric elastomer actuators (DEAs) are a promising soft actuator technology for robotics. Adding robotic functionalities--folding, variable stiffness, and adhesion--into their actuator design is a novel method to create functionalized robots with simplified actuator configurations. We first propose a foldable actuator that has a simple antagonistic DEA configuration allowing bidirectional actuation and passive folding. To prove the concept, a foldable elevon actuator with outline size of 70 mm × 130 mm is developed with a performance specification matched to a 400 mm wingspan micro air vehicle (MAV) of mass 130 g. The developed actuator exhibits actuation angles up to ± 26 ° and a torque of 2720 mN·mm in good agreement with a prediction model. During a flight, two of these integrated elevon actuators well controlled the MAV, as proven by a strong correlation of 0.7 between the control signal and the MAV motion. We next propose a variable stiffness actuator consisting of a pre-stretched DEA bonded on a low-melting-point alloy (LMPA) embedded silicone substrate. The phase of the LMPA changes between liquid and solid enabling variable stiffness of the structure, between soft and rigid states, while the DEA generates a bending actuation. A proof-of-concept actuator with dimension 40 mm length × 10mm width × 1mm thickness and a mass of 1 g is fabricated and characterized. Actuation is observed up to 47.5 ° angle and yielding up to 2.4 mN of force in the soft state. The stiffness in the rigid state is ~90 × larger than an actuator without LMPA. We develop a two-finger gripper in which the actuators act as the fingers. The rigid state allows picking up an object mass of 11 g (108 mN), to be picked up even though the actuated grasping force is only 2.4 mN. We finally propose an electroadhesion actuator that has a DEA design simultaneously maximizing electroadhesion and electrostatic actuation, while allowing self-sensing by employing an interdigitated electrode geometry. The concept is validated through development of a two-finger soft gripper, and experimental samples are characterized to address an optimal design. We observe that the proposed DEA design generates 10 × larger electroadhesion force compared to a conventional DEA design, equating to a gripper with a high holding force (3.5 N shear force for 1 cm^2) yet a low grasping force (1 mN). These features make the developed simple gripper to handle a wide range of challenging objects such as highly-deformable water balloons (35.6 g), flat paper (0.8 g), and a raw chicken egg (60.9 g), with its lightweight (1.5 g) and fast movement (100 ms to close fingers). The results in this thesis address the creation of the functionalized robots and expanding the use of DEAs in robotics