Achieving human-like dexterity in robotic hands : inspiration from human hand biomechanics and neuromuscular control

The human hand's unique biomechanical structure and neuromuscular control combine to produce amazing dexterous capabilities in a way that is still not fully understood. The Anatomically Correct Testbed (ACT) hand is a robotic system that is designed as a physical simulation of the human hand, and can help us examine and potentially uncover the roles of biomechanics and neural control in achieving dexterity. In this dissertation, I utilize the ACT hand and other robotic systems to explore the underlying sources of human hand dexterity, with the goal of understanding the fundamental differences between robotic and human hands in terms of (i) mechanical joint/tendon structure and (ii) control strategies. To begin, I develop comprehensive mechanical models that describe the musculoskeletal and tendon mechanics of the fingers and thumb of the human hand. Then, I work to isolate the contributions of biomechanical structure and neuromuscular control toward human dexterity. I have developed and implemented control strategies for achieving fine object manipulation first with the robotic hand of a space humanoid, Robonaut 2, and then with the ACT hand. I examined the unique control challenges, including uncontrollable joints and the requirement of accurate internal models, that arise due to the human hand's complex musculotendon structure and the potential advantages offered by the human hand's design, such as passive joint coupling to facilitate grasp shape adaptation and force production capabilities that are ideally suited for common manipulation tasks. Finally, inspired by the neuromuscular control strategies of the human hand, I have developed a novel hierarchical control strategy for the ACT hand and experimentally demonstrated improved grasp stability and manipulation capabilities compared to conventional robotic control laws. Through an in-depth exploration of human hand biomechanics and neuromuscular control, theoretical control analysis of robotic and human hands, and experimental demonstration of fine object manipulation, this work uncovers crucial insights into the sources of human hand dexterity that have the potential to drive innovative design and control strategies and bring robotic and prosthetic hands closer to human levels of dexterity.Mechanical Engineerin

Cable Manipulation with a Tactile-Reactive Gripper

Cables are complex, high dimensional, and dynamic objects. Standard approaches to manipulate them often rely on conservative strategies that involve long series of very slow and incremental deformations, or various mechanical fixtures such as clamps, pins or rings. We are interested in manipulating freely moving cables, in real time, with a pair of robotic grippers, and with no added mechanical constraints. The main contribution of this paper is a perception and control framework that moves in that direction, and uses real-time tactile feedback to accomplish the task of following a dangling cable. The approach relies on a vision-based tactile sensor, GelSight, that estimates the pose of the cable in the grip, and the friction forces during cable sliding. We achieve the behavior by combining two tactile-based controllers: 1) Cable grip controller, where a PD controller combined with a leaky integrator regulates the gripping force to maintain the frictional sliding forces close to a suitable value; and 2) Cable pose controller, where an LQR controller based on a learned linear model of the cable sliding dynamics keeps the cable centered and aligned on the fingertips to prevent the cable from falling from the grip. This behavior is possible by a reactive gripper fitted with GelSight-based high-resolution tactile sensors. The robot can follow one meter of cable in random configurations within 2-3 hand regrasps, adapting to cables of different materials and thicknesses. We demonstrate a robot grasping a headphone cable, sliding the fingers to the jack connector, and inserting it. To the best of our knowledge, this is the first implementation of real-time cable following without the aid of mechanical fixtures.Comment: Accepted to RSS 202

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

Investigation and development of a flexible gripper with adaptable finger geometry

Das zuverlässige und schonende Greifen ist ein Hauptanliegen bei der Entwicklung von neuartigen Greifvorrichtungen. Je größer die Kontaktfläche zwischen dem Greifer und dem Greifobjekt ist, desto schonender und zuverlässiger ist der Greifvorgang. Um dieses Ziel zu erreichen wurden in den letzten Jahrzehnten zahlreiche Untersuchungen zu adaptiven passiven Greifern durchgeführt. Ein neuer Forschungszweig im Bereich selbstadaptiver Greifer sind Greifer mit nachgiebigen blattfederartigen Greifelementen (Greiferfinger) Die Funktionsweise basiert auf dem elastischen Ausknicken der Greifelemente infolge einer translatorische Antriebsbewegung Die vorliegende Arbeit konzentriert sich auf die Verbesserung des Greifvorgangs, indem die Kontaktlänge zwischen den blattfederartigen Greiferfingern und dem zu greifenden Objekt deutlich erhöht wird. Um diese Aufgabenstellung zu lösen, muss eine geeignete Greifergeometrie für ein gegebenes Greifobjekt berechnet werden. Die gezielte Berechnung der erfoderlichen Greifergeometrie für ein bekanntes Greifobjekt ist nicht möglich. Daher wurde als Lösungsansatz die umkehrte Richtung gewählt. Für eine definierte Greifgeometrie wird die Gestalt des dazu passenden “idealen” Greifobjektes ermittelt und anschließend mit der Gestalt zu greifenden Objektes verglichen. Bei Gestaltabweichungen wird die Greifergeometrie iterative verändert, bis seine geeignete Greifergeometrie gefunden wurde. Im Rahmen der vorliegenden Arbeit wird zunächst die Ermittlung des “idealen” Greifobjektes behandelt. Es wurde ein Algorithmus entwickelt, der für eine vorgegebene Greifergeometrie die Gestalt eines runden bzw. elliptischen Objektes ermittelt. Der Algorithmus verwendet als Eingabedaten die Biegelinien der elastisch ausgeknickten Greiffinger unter Berücksichtigung unterschiedlicher Randbedingungen. Als Ausgabedaten liefert der Algorithmus die Gestalt des passenden Greifobjektes zurück. Für quadratische bzw. rechteckige sowie für dreieckige Objekte wurden unterschiedliche Greifgeometrien untersucht. Außerdem wird für quadratische und rechteckige Objekte das Lösungskonzept für die Entwicklung eines weiteren Algorithmus beschrieben. In Kapitel 1 wird eine Klassifizierung von Greifern basierend auf der Anpassungsfähigkeit vorgestellt. In Kapitel 2 werden Lösungskonzepte, Modelle und Theorien vorgestellt. In Kapitel 3 werden Ablaufdiagramme der Algorithmen dargestellt. In Kapitel 4 wird die Entwicklung des Algorithmus für elliptische Objekte und deren Betriebsmodi beschrieben. In Kapitel 5 werden Greifgeometrien für quadratische bzw. Rechteckige sowie für dreieckige Objekte analysiert und die Ideen eines Algorithmus für quadratisch bzw. rechteckige Objekte beschrieben. In Kapitel 6 wird ein kurzer Überblick über die zukünftige Arbeiten.Reliable and gentle gripping is a major concern in the development of new gripping devices. The larger contact surface between the gripper and the gripping object, the gentler and more reliable the gripping process. In order to achieve this goal, further investigations on adaptive passive grippers have been carried out in the recent decades. A new branch of research in the field of self-adaptive grippers are compliant leaf-spring-like gripping elements (gripper fingers). Its mode of operation is based on the elastic buckling of the gripping elements as a result of a translatory drive movement. The present work focuses on improving the gripping process by increasing significantly the contact length between the compliant leaf-spring-like gripper fingers and the object to be gripped. In order to solve this task, a suitable gripper geometry for a given gripping object should be calculated The specific calculation of the required gripper geometry for a known gripping object is not possible; therefore, this work aims in the opposite direction. For a defined gripping geometry, the shape of the matching “ideal” gripping object is determined and then compared with the desired object to be gripped. In case of a deviation in the size, the gripper geometry is iteratively changed until its suitable gripper geometry has been found. In the present work, the determination of the “ideal” gripping object is the first task to deal with. An algorithm has been developed to determine the shape of a round-elliptical object for a given gripper geometry. The algorithm uses as data input the bend lines of the compliant twogripper finger under different boundary conditions. As data output, the algorithm returns the shape of the matching gripping object. For square-rectangular and triangular objects, different gripping geometries have been investigated. Furthermore, for square-rectangular objects, solution concepts for the development of an algorithm is described. In chapter 1, a classification based on adaptability is presented. In chapter 2, solution concepts, models and theories involved are introduced. In chapter 3, process flow diagrams of the algorithms are presented. In chapter 4, the development of the algorithm for elliptical objects and its operation modes are described. In chapter 5, gripping geometries for square-rectangular and triangular objects are analysed and the ideas of an algorithm for square-rectangular objects are described. In chapter 6, a brief overview of the futur work is commented.Tesi

Dexterous Grasping Tasks Generated With an Add-on End Effector of a Haptic Feedback System

The simulation of grasping operations in virtual reality (VR) is required for many applications, especially in the domain of industrial product design, but it is very difficult to achieve without any haptic feedback. Force feedback on the fingers can be provided by a hand exoskeleton, but such a device is very complex, invasive, and costly. In this paper, we present a new device, called HaptiHand, which provides position and force input as well as haptic output for four fingers in a noninvasive way, and is mounted on a standard force-feedback arm. The device incorporates four independent modules, one for each finger, inside an ergonomic shape, allowing the user to generate a wide range of virtual hand configurations to grasp naturally an object. It is also possible to reconfigure the virtual finger positions when holding an object. The paper explains how the device is used to control a virtual hand in order to perform dexterous grasping operations. The structure of the HaptiHand is described through the major technical solutions required and tests of key functions serve as validation process for some key requirements. Also, an effective grasping task illustrates some capabilities of the HaptiHand

Robotic simulators for tissue examination training with multimodal sensory feedback

Tissue examination by hand remains an essential technique in clinical practice. The effective application depends on skills in sensorimotor coordination, mainly involving haptic, visual, and auditory feedback. The skills clinicians have to learn can be as subtle as regulating finger pressure with breathing, choosing palpation action, monitoring involuntary facial and vocal expressions in response to palpation, and using pain expressions both as a source of information and as a constraint on physical examination. Patient simulators can provide a safe learning platform to novice physicians before trying real patients. This paper reviews state-of-the-art medical simulators for the training for the first time with a consideration of providing multimodal feedback to learn as many manual examination techniques as possible. The study summarizes current advances in tissue examination training devices simulating different medical conditions and providing different types of feedback modalities. Opportunities with the development of pain expression, tissue modeling, actuation, and sensing are also analyzed to support the future design of effective tissue examination simulators

Artificial Intelligence and Ambient Intelligence

This book includes a series of scientific papers published in the Special Issue on Artificial Intelligence and Ambient Intelligence at the journal Electronics MDPI. The book starts with an opinion paper on “Relations between Electronics, Artificial Intelligence and Information Society through Information Society Rules”, presenting relations between information society, electronics and artificial intelligence mainly through twenty-four IS laws. After that, the book continues with a series of technical papers that present applications of Artificial Intelligence and Ambient Intelligence in a variety of fields including affective computing, privacy and security in smart environments, and robotics. More specifically, the first part presents usage of Artificial Intelligence (AI) methods in combination with wearable devices (e.g., smartphones and wristbands) for recognizing human psychological states (e.g., emotions and cognitive load). The second part presents usage of AI methods in combination with laser sensors or Wi-Fi signals for improving security in smart buildings by identifying and counting the number of visitors. The last part presents usage of AI methods in robotics for improving robots’ ability for object gripping manipulation and perception. The language of the book is rather technical, thus the intended audience are scientists and researchers who have at least some basic knowledge in computer science