Intelligent Haptic Perception for Physical Robot Interaction

Doctorado en Ingeniería mecatrónica. Fecha de entrega de la Tesis doctoral: 8 de enero de 2020. Fecha de lectura de Tesis doctoral: 30 de marzo 2020.The dream of having robots living among us is coming true thanks to the recent advances in Artificial Intelligence (AI). The gap that still exists between that dream and reality will be filled by scientific research, but manifold challenges are yet to be addressed. Handling the complexity and uncertainty of real-world scenarios is still the major challenge in robotics nowadays. In this respect, novel AI methods are giving the robots the capability to learn from experience and therefore to cope with real-life situations. Moreover, we live in a physical world in which physical interactions are both vital and natural. Thus, those robots that are being developed to live among humans must perform tasks that require physical interactions. Haptic perception, conceived as the idea of feeling and processing tactile and kinesthetic sensations, is essential for making this physical interaction possible. This research is inspired by the dream of having robots among us, and therefore, addresses the challenge of developing robots with haptic perception capabilities that can operate in real-world scenarios. This PhD thesis tackles the problems related to physical robot interaction by employing machine learning techniques. Three AI solutions are proposed for different physical robot interaction challenges: i) Grasping and manipulation of humans’ limbs; ii) Tactile object recognition; iii) Control of Variable-Stiffness-Link (VSL) manipulators. The ideas behind this research work have potential robotic applications such as search and rescue, healthcare or rehabilitation. This dissertation consists of a compendium of publications comprising as the main body a compilation of previously published scientific articles. The baseline of this research is composed of a total of five papers published in prestigious peer-reviewed scientific journals and international robotics conferences

Grasping Angle Estimation of Human Forearm with Underactuated Grippers Using Proprioceptive Feedback

In this paper, a method for the estimation of the angle of grasping of a human forearm, when grasped by a robot with an underactuated gripper, using proprioceptive information only, is presented. Knowing the angle around the forearm’s axis (i.e. roll angle) is key for the safe manipulation of the human limb and biomedical sensor placement among others. The adaptive gripper has two independent underactuated fingers with two phalanges and a single actuator each. The final joint position of the gripper provides information related to the shape of the grasped object without the need for external contact or force sensors. Regression methods to estimate the roll angle of the grasping have been trained with forearm grasping information from different humans at each angular position. The results show that it is possible to accurately estimate the rolling angle of the human arm, for trained and unknown people.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Adaptive Underactuated Finger with Active Rolling Surface

This paper presents the design, prototype and kinematic model of a new adaptive underactuated finger with an articulated skin/surface that is able to bend and, at the same time, provides active rolling motion along its central axis while keeping the finger configuration. The design is based on a planar chain of overlapping spherical phalanxes that are tendon-driven. The finger has an articulated surface made of an external chain of hollow universal joints that can rotate via its central axis on the surface of the internal structure. The outer surface provides a second active Degree of Freedom (DoF). The two actuators, driving the bending and/or rolling motion, can be used independently. A set of experiments have been included to validate and measure the performance of the prototype for the grasping and rolling actions. The proposed finger can be built with a different number of phalanxes and sizes. A number of these fingers can be arranged along a palm structure resulting in a multi-finger robotic grasper for applications that require adaptation and in-hand manipulation capabilities such as pHRI

Adaptive Force Controller for Contact-Rich Robotic Systems using an Unscented Kalman Filter

In multi-point contact systems, precise force control is crucial for achieving stable and safe interactions between robots and their environment. Thus, we demonstrate an admittance controller with auto-tuning that can be applied for these systems. The controller's objective is to track the target wrench profiles of each contact point while considering the additional torque due to rotational friction. Our admittance controller is adaptive during online operation by using an auto-tuning method that tunes the gains of the controller while following user-specified training objectives. These objectives include facilitating controller stability, such as tracking the wrench profiles as closely as possible, ensuring control outputs are within force limits that minimize slippage, and avoiding configurations that induce kinematic singularity. We demonstrate the robustness of our controller on hardware for both manipulation and locomotion tasks using a multi-limbed climbing robot.Comment: Submitted to IROS 202

Human-robot interaction for assistive robotics

This dissertation presents an in-depth study of human-robot interaction (HRI) withapplication to assistive robotics. In various studies, dexterous in-hand manipulation is included, assistive robots for Sit-To-stand (STS) assistance along with the human intention estimation. In Chapter 1, the background and issues of HRI are explicitly discussed. In Chapter 2, the literature review introduces the recent state-of-the-art research on HRI, such as physical Human-Robot Interaction (HRI), robot STS assistance, dexterous in hand manipulation and human intention estimation. In Chapter 3, various models and control algorithms are described in detail. Chapter 4 introduces the research equipment. Chapter 5 presents innovative theories and implementations of HRI in assistive robotics, including a general methodology of robotic assistance from the human perspective, novel hardware design, robotic sit-to-stand (STS) assistance, human intention estimation, and control

Towards Living Machines: current and future trends of tactile sensing, grasping, and social robotics

The development of future technologies can be highly influenced by our deeper understanding of the principles that underlie living organisms. The Living Machines conference aims at presenting (among others) the interdisciplinary work of behaving systems based on such principles. Celebrating the 10 years of the conference, we present the progress and future challenges of some of the key themes presented in the robotics workshop of the Living Machines conference. More specifically, in this perspective paper, we focus on the advances in the field of biomimetics and robotics for the creation of artificial systems that can robustly interact with their environment, ranging from tactile sensing, grasping, and manipulation to the creation of psychologically plausible agents

Robotic Platforms for Assistance to People with Disabilities

People with congenital and/or acquired disabilities constitute a great number of dependents today. Robotic platforms to help people with disabilities are being developed with the aim of providing both rehabilitation treatment and assistance to improve their quality of life. A high demand for robotic platforms that provide assistance during rehabilitation is expected because of the health status of the world due to the COVID-19 pandemic. The pandemic has resulted in countries facing major challenges to ensure the health and autonomy of their disabled population. Robotic platforms are necessary to ensure assistance and rehabilitation for disabled people in the current global situation. The capacity of robotic platforms in this area must be continuously improved to benefit the healthcare sector in terms of chronic disease prevention, assistance, and autonomy. For this reason, research about human–robot interaction in these robotic assistance environments must grow and advance because this topic demands sensitive and intelligent robotic platforms that are equipped with complex sensory systems, high handling functionalities, safe control strategies, and intelligent computer vision algorithms. This Special Issue has published eight papers covering recent advances in the field of robotic platforms to assist disabled people in daily or clinical environments. The papers address innovative solutions in this field, including affordable assistive robotics devices, new techniques in computer vision for intelligent and safe human–robot interaction, and advances in mobile manipulators for assistive tasks

Robotic Actuation and Control with Programmable, Field-Activated Material Systems

This dissertation presents novel, field-activated smart material systems for the actuation and control of autonomous robots. Smart materials, a type of material whose properties can be changed with an external stimuli, represent a promising direction to expand upon existing robotic control and actuation methods, particularly in the sub-fields of soft robotics and robotic grasping. Specifically, this work makes the following contributions: i) a literature review that synthesizes recent work on field-activated smart materials and their use in soft robotics; ii) an electrorheological fluid (ERF) valve to control soft actuators; iii) magnetic elastomers (MEs) to increase the grip strength of soft grippers; and iv) a low-power method for torque transmission enabled by magnetorheological fluid (MRF) and electropermanent magnet arrays. After the introduction, this dissertation presents a comprehensive literature review paper (Chapter 2) regarding the use of field-activated materials in soft robotics, with an emphasis on magnetic elastomers. The second paper (Chapter 3) describes the development of a 3D-printed pressure valve intended to leverage the pressuring-holding properties of ERF when under the influence of a high voltage field to actuate soft actuators. The third paper (Chapter 4) demonstrates how magnetic elastomers and magnetic fields can enhance soft robotic grip strength and versatility. The fourth paper (Chapter 5) models, fabricates, and characterizes a MRF-containing clutch device able to rapidly and reversibly module the amount of torque transmitted from an input shaft to an output by leveraging low-power electropermanent magnet arrays. Each work focuses on a field-activated smart material to perform a specific robotic function, with particular emphasis given to compliant mechanisms and soft robotics, as well as to reducing cost and improving ease of fabrication with the use of modern fabrication techniques. In these described papers, field-activated materials are first modeled and then deployed in functional prototypes, and their robotic utility is described in detail after extensive experimental characterization

Robust Grasp with Compliant Multi-Fingered Hand

As robots find more and more applications in unstructured environments, the need for grippers able to grasp and manipulate a large variety of objects has brought consistent attention to the use of multi-fingered hands. The hardware development and the control of these devices have become one of the most active research subjects in the field of grasping and dexterous manipulation. Despite a large number of publications on grasp planning, grasping frameworks that strongly depend on information collected by touching the object are getting attention only in recent years. The objective of this thesis focuses on the development of a controller for a robotic system composed of a 7-dof collaborative arm + a 16-dof torque-controlled multi-fingered hand to successfully and robustly grasp various objects. The robustness of the grasp is increased through active interaction between the object and the arm/hand robotic system. Algorithms that rely on the kinematic model of the arm/hand system and its compliance characteristics are proposed and tested on real grasping applications. The obtained results underline the importance of taking advantage of information from hand-object contacts, which is necessary to achieve human-like abilities in grasping tasks

A hand exoskeleton for study of rehabilitation and assistance of spinal cord injury patients

A large number of people experience neurological disorders in their life time, and these patients seek to regain their body functions with rehabilitation and assistive devices. In this dissertation, we present the development of a hand exoskeleton, called Maestro, which is designed to advance research in fields of hand rehabilitation and hand assistive devices. Maestro is mechanically and electrically robust, accurate in sensing and actuation, and compatible to various rehabilitation schemes, subjects, hardware/software, and different operators. As a result of these features, Maestro has led to research on adaptive control theories for diverse properties of hands, the development of a hand-wrist exoskeleton, the development of a novel rehabilitation framework, progress of hand muscle fatigues, and assistance for SCI patients. Particularly on the assistance for SCI patients, we present that the advantage of a compliant hand assistive device may result in high success ratios for grasping various objects required in activities of daily living (ADL) with surface EMG sensors. The hand functions of SCI subjects are evaluated with and without Maestro through a standardized hand function test called Sollerman hand function test (SHFT). The results with six SCI subjects show that the hand functions of C6 and C7 SCI subjects improved with assistance from Maestro.Mechanical Engineerin