Soft Robotics: Design for Simplicity, Performance, and Robustness of Robots for Interaction with Humans.

This thesis deals with the design possibilities concerning the next generation of advanced Robots. Aim of the work is to study, analyse and realise artificial systems that are essentially simple, performing and robust and can live and coexist with humans. The main design guideline followed in doing so is the Soft Robotics Approach, that implies the design of systems with intrinsic mechanical compliance in their architecture. The first part of the thesis addresses design of new soft robotics actuators, or robotic muscles. At the beginning are provided information about what a robotic muscle is and what is needed to realise it. A possible classification of these systems is analysed and some criteria useful for their comparison are explained. After, a set of functional specifications and parameters is identified and defined, to characterise a specific subset of this kind of actuators, called Variable Stiffness Actuators. The selected parameters converge in a data-sheet that easily defines performance and abilities of the robotic system. A complete strategy for the design and realisation of this kind of system is provided, which takes into account their me- chanical morphology and architecture. As consequence of this, some new actuators are developed, validated and employed in the execution of complex experimental tasks. In particular the actuator VSA-Cube and its add-on, a Variable Damper, are developed as the main com- ponents of a robotics low-cost platform, called VSA-CubeBot, that v can be used as an exploratory platform for multi degrees of freedom experiments. Experimental validations and mathematical models of the system employed in multi degrees of freedom tasks (bimanual as- sembly and drawing on an uneven surface), are reported. The second part of the thesis is about the design of multi fingered hands for robots. In this part of the work the Pisa-IIT SoftHand is introduced. It is a novel robot hand prototype designed with the purpose of being as easily usable, robust and simple as an industrial gripper, while exhibiting a level of grasping versatility and an aspect comparable to that of the human hand. In the thesis the main theo- retical tool used to enable such simplification, i.e. the neuroscience– based notion of soft synergies, are briefly reviewed. The approach proposed rests on ideas coming from underactuated hand design. A synthesis method to realize a desired set of soft synergies through the principled design of adaptive underactuated mechanisms, which is called the method of adaptive synergies, is discussed. This ap- proach leads to the design of hands accommodating in principle an arbitrary number of soft synergies, as demonstrated in grasping and manipulation simulations and experiments with a prototype. As a particular instance of application of the method of adaptive syner- gies, the Pisa–IIT SoftHand is then described in detail. The design and implementation of the prototype hand are shown and its effec- tiveness demonstrated through grasping experiments. Finally, control of the Pisa/IIT Hand is considered. Few different control strategies are adopted, including an experimental setup with the use of surface Electromyographic signals

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

A Helping Hand: Design process of a soft anthropomorphic end-effector for the construction industry.

This thesis conducts design-led research to develop a soft anthropomorphic end-effector that is specifically designed for use with a collaborative robot on a construction site. As the construction industry changes to meet the demands of increasing populations and lack of skilled trades workers, new approaches are needed. This research explores the possibilities of a collaborative robot working on a construction site to help workers complete tasks deemed unsafe or detrimental to their health. The study acknowledges the different requirements of human-robot collaboration. However, it focuses on designing a hybrid end-effector that allows a collaborative robot to carry out more than a singular task on a construction site to increase productivity through all construction stages. The research conducts an iterative design process using soft robot techniques to replicate human hand elements, such as muscles and ligaments and currently available sensor technologies to create a hybrid end-effector. This end-effector is tested for grip strength and the ability to use both power and precision grasp functions to pick up a paintbrush, screwdriver, and a screw

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 246)

This bibliography lists 219 reports, articles and other documents introduced into the NASA scientific and technical information system in May 1983

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

Proceedings of the NASA Conference on Space Telerobotics, volume 3

The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research

A cumulative index to the 1977 issues of a continuing bibliography on aerospace medicine and biology

This publication is a cumulative index to the abstracts contained in the Supplements 164 through 175 of Aerospace Medicine and Biology: A Continuing Bibliography. It includes three indexes-- subject, personal author, and corporate source

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 325)

This bibliography lists 192 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during June, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Sensorimotor learning under switching dynamics

Humans have a remarkable capacity to learn new motor behaviours without forgetting old ones. This capacity relies on the ability to acquire and express multiple motor memories without interference. Here we combine behavioural experiments and computational modelling to investigate how the sensorimotor system uses contextual information to create, update and recall motor memories. We first examine the role of muscle co-contraction in the learning of novel movement dynamics. We show that muscle co-contraction, as measured by surface electromyography, accelerates motor learning. We then explore the role of control points on objects in the formation of motor memories during object manipulation. We show that opposing dynamic perturbations, which interfere when controlling a single location on an object, can be learned when each is associated with a separate control point. To account for these results, we develop a parametric switching state-space model, in which the association between cues (control points) and contexts (dynamics) is learned from experience rather than fixed. We then extend this model to a Bayesian nonparametric switching state-space model, in which the number of contexts and cues are learned online rather than specified in advance. This model can instantiate new memories when novel perturbations are experienced and exhibits spontaneous recovery of a memory that has been ostensibly overwritten. To test the model, we perform an experiment in which we briefly present a previously experienced perturbation after behaviour has returned to baseline. As predicted, we observe a qualitatively distinct and more pronounced form of recovery, which we refer to as evoked recovery. Finally, we investigate Bayesian context estimation using single-trial learning. We show that people are able to learn novel associations between cues and contexts and that they use both contextual cues and state feedback to infer the current context and partition learning between memories. Taken together, these findings further the understanding of the behaviour and computational principles of sensorimotor learning under switching dynamics.Engineering and Physical Sciences Research Counci

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored