Analytics for the Sharing Economy: Mathematics, Engineering and Business Perspectives
Pagination
25–37
Publisher
Springer International Publishing
City
Cham
ISBN Number
978-3-030-35032-1
Abstract
Interconnection of a large number of systems has become a reality from a technological point of view although intelligent connection among smart systems still presents a challenge in several application scenarios. More specifically, when many smart devices must accomplish an overall goal based on information exchanges with other devices, several factors render this task a real challenge, such as, knowing what specific information to exchange, with whom, how to go about it, and when this exchange will occur. Moreover, interconnected devices may require access to or the use of common resources, making the management of the overall system even more complex. The management of shared resources usually sets the goal of optimizing usage while guaranteeing achievement of the overall goals. Algorithms or protocols that grant the device a correct, safe and optimized access to resources play a fundamental role. In this chapter we will provide those algorithms that are fundamental in several different application scenarios that allow for the development of more complex algorithms in order to manage interconnected systems in the management of shared resources.
In previous chapters, human hand and arm kinematics have been analyzed through a synergstic approach and the underlying concepts were used to design robotic systems and devise simplified control algorithms. On the other hand, it is well-known that synergies can be studied also at a muscular level as a coordinated activation of multiple muscles acting as a single unit to generate different movements. As a result, muscular activations, quantified through Electromyography (EMG) signals can be then processed and used as direct inputs to external devices with a large number of DOFs. In this chapter, we present a minimalistic approach based on tele-impedance control, where EMGs from only one pair of antagonistic muscle pair are used to map the users postural and stiffness references to the synergy-driven anthropomorphic robotic hand, described in chapter 6. In this direction, we first provide an overview of the teleimpedance control concept which forms the basis for the development of the hand controller. Eventually, experimental results evaluate the effectiveness of the teleimpedance control concept in execution of the tasks which require significant dynamics variation or are executed in remote environments with dynamic uncertainties.
As described in Chaps. 2–5, neuroscientific studies showed that the control of the human hand is mainly realized in a synergistic way. Recently, taking inspiration from this observation, with the aim of facing the complications consequent to the high number of degrees of freedom, similar approaches have been used for the control of robotic hands. As Chap. 12 describes SynGrasp, a useful technical tool for grasp analysis of synergy-inspired hands, in this chapter recently developed analysis tools for studying robotic hands equipped with soft synergy underactuation (see Chap. 8) are exhaustively described under a theoretical point of view. After a review of the quasi-static model of the system, the Fundamental Grasp Matrix (FGM) and its canonical form (cFGM) are presented, from which it is possible to extract relevant information as, for example, the subspaces of the controllable internal forces, of the controllable object displacements and the grasp compliance. The definitions of some relevant types of manipulation tasks (e.g. the pure squeeze, realized maintaining the object configuration fixed but changing contact forces, or the kinematic grasp displacements, in which the grasped object can be moved without modifying contact forces) are provided in terms of nullity or non-nullity of the variables describing the system. The feasibility of such predefined tasks can be verified thanks to a decomposition method, based on the search of the row reduced echelon form (RREF) of suitable portions of the solution space. Moreover, a geometric interpretation of the FGM and the possibility to extend the above mentioned methods to the study of robotic hands with different types of underactuation are discussed. Finally, numerical results are presented for a power grasp example, the analysis of which is initially performed for the case of fully-actuated hand, and later verifying, after the introduction of a synergistic underactuation, which capacities of the system are lost, and which other are still present.
Notes
This work was supported by the European Commission under the CP-IP grant
no. 248587 “THE Hand Embodied”, within the FP7-2007-2013 program, by the
grant no. 600918 “PaCMan” - Probabilistic and Compositional Representations of
Objects for Robotic Manipulation - within the FP7-ICT-2011-9 program, the grant
no. 611832 “Walk-Man” within the FP7-ICT-2013-10 program, and the grant no.
645599 “SOMA: Soft-bodied Intelligence for Manipulation”, funded under H2020-
EU-2115.
Most of the neuroscientific results on synergies and their technical implementations in robotic systems, which are widely discussed throughout this book (see e.g. Chaps. 2, 3, 4, 8, 10, 12 and 13), moved from the analysis of hand kinematics in free motion or during the interaction with the external environment. This observation motivates both the need for the development of suitable and manageable models for kinematic recordings, as described in Chap. 14, and the calling for accurate and economic systems or “gloves” able to provide reliable hand pose reconstructions. However, this latter aspect, which represents a challenging point also for many human-machine applications, is hardly achievable in economically and ergonomically viable sensing gloves, which are often imprecise and limited. To overcome these limitations, in this chapter we propose to exploit the bi-directional relationship between neuroscience and robotic/artificial systems, showing how the findings achieved in one field can inspire and be used to advance the state of art in the other one, and vice versa. More specifically, our leading approach is to use the concept of kinematic synergies to optimally estimate the posture of a human hand using non-ideal sensing gloves. Our strategy is to collect and organize synergistic information and to fuse it with insufficient and inaccurate glove measurements in a consistent manner and with no extra costs. Furthermore, we will push forward such an analysis to the dual problem of how to design pose sensing devices, i.e. how and where to place sensors on a glove, to get maximum information about the actual hand posture, especially with a limited number of sensors. We will study the optimal design of gloves of different nature. Conclusions that can be drawn take inspiration from and might inspire further investigations on the biology of human hand receptors. Experimental evaluations of these techniques are reported and discussed.
Taking inspiration from the neuroscientific findings on hand synergies discussed in the first part of the book, in this chapter we present the Pisa/IIT SoftHand, a novel robot hand prototype. The design moves under the guidelines of making an hardware robust and easy to control, preserving an high level of grasping capabilities and an aspect as similar as possible to the human counterpart. First, the main theoretical tools used to enable such simplification are presented, as for example the notion of soft synergies. A discussion of some possible actuation schemes shows that a straightforward implementation of the soft synergy idea in an effective design is not trivial. The proposed approach, called adaptive synergy, rests on ideas coming from underactuated hand design, offering a design method to implement the desired set of soft synergies as demonstrated both with simulations and experiments. As a particular instance of application of the synthesis method of adaptive synergies, the Pisa/IIT SoftHand is described in detail. The hand has 19 joints, but only uses one actuator to activate its adaptive synergy. Of particular relevance in its design is the very soft and safe, yet powerful and extremely robust structure, obtained through the use of innovative articulations and ligaments replacing conventional joint design. Moreover, in this work, summarizing results presented in previous papers, a discussion is presented about how a new set of possibilities is open from paradigm shift in manipulation approaches, moving from manipulation with rigid to soft hands.
This work presents the translation from a humanoid robotic hand to a prosthetic prototype and its first evaluation in a set of 9 persons with amputation. The Pisa/IIT SoftHand is an underactuated hand built on the neuroscientific principle of motor synergies enabling it to perform natural, human-like movements and mold around grasped objects with minimal control input. These features motivated the development of the SoftHand Pro, a prosthetic version of the SoftHand built to interface with a prosthetic socket. The results of the preliminary testing of the SoftHand Pro showed it to be a highly functional design with an intuitive control system. Present results warrant further testing to develop the SoftHand Pro.
Notes
Proceedings of the 3rd International Conference on NeuroRehabilitation (ICNR2016), October 18-21, 2016, Segovia, Spain
Although we do not know as yet how robots of the future will look like exactly, most of us are sure that they will not resemble the heavy, bulky, rigid machines dangerously moving around in old-fashioned industrial automation. There is a growing consensus, in the research community as well as in expectations from the public, that robots of the next generation will be physically compliant and adaptable machines, closely interacting with humans and moving safely, smoothly and efficiently – in other terms, robots will be soft.
This chapter discusses the design, modeling and control of actuators for the new generation of soft robots, which can replace conventional actuators in applications where rigidity is not the first and foremost concern in performance. The chapter focuses on the technology, modeling, and control of lumped parameters of soft robotics, that is, systems of discrete, interconnected, and compliant elements. Distributed parameters, snake-like and continuum soft robotics, are presented in Chap. 20, while Chap. 23 discusses in detail the biomimetic motivations that are often behind soft robotics.
Biomedical Engineering Systems and Technologies: 7th International Joint Conference, BIOSTEC 2014, Angers, France, March 3-6, 2014, Revised Selected Papers
Diseases of hyaline cartilage represent one of the major health problems, especially in industrialized countries with high life expectancy. The erosion of the articulating surfaces of joints, known as osteoarthritis, currently affects more than 200 million citizens worldwide, and more than 50% of the patients need or will need a surgical treatment. Articular cartilage is a three dimensional avascular tissue, which covers the ends of all synovial joints. During normal daily function, articular cartilage can be repeatedly subjected to forces up to several time body weight, but it is able to provide articulating joints with a nearly frictionless motion. Despite its tremendously important function, articular cartilage has limited capacity for auto regeneration after degenerative and rheumatic diseases, like arthritis, as well as traumatic injuries. Cartilage problems are a huge and still unsolved medical issue, which therefore represents one of the most important tissue engineering targets requiring high quality products as fast as possible. For this reason, the possibility to recreate in vitro cartilage substitutes as a real alternative to total joint replacement represents an increasing and hopeful market, in which many research groups are still working. At the moment, one of the main findings in invitro cartilage studies is the importance of the role of mechanical stimuli and dynamic loads for the chondrocytes growth and differentiation. Several studies using cartilage explants or chondrocytes seeded in 3D scaffolds have shown that mechanical compressive loads affect the cells metabolic activity and their matrix production. In order to simulate the in vivo environment, the use of bioreactors is becoming fundamental: bioreactors can provide the chemical and mechanical signals that optimize tissue development. Furthermore, bioreactors could be an important instrument to reduce the cost of clinical studies, used as in vitro predictors of in vivo performance. In this way,the use of bioreactors can reduce animal studies, helping the scientists to focus their attention in the right direction before starting pre-clinical studies, which are usually more expensive than preliminary research. In the past few years, several systems for the application of different mechanical stimuli to chondrocytes have been developed. Most of these can generate biomechanical-like forces such as the direct compression, tensile and shear forces, or hydrostatic pressure, in order to stimulate the articular chondrocyctes to increase their matrix production. Generally, the most important requirements that a culture system has to satisfy are high reliability and usability, perfect sterility, easy control of all the important culture parameters and low cost. In this work, a new system, inspired by the synovial environment of mobile joints and able to apply an innovative type of stimulation on articular chondrocytes is described and modeled. The SQPR (SQueeze PRessure) bioreactor chamber is designed to impose a cyclic hydrodynamic pressure on cell cultures, constructs or tissues slices. The basic principle of this new system is the generation of a localized contact less overpressure on articular chondrocytes, using a simple vertical piston movement. This kind of stimulation is particularly useful for neo-tissue or fresh-constructs, in which cells require a dynamic environment to maintain their differentiate state, but at the same time do not tolerate direct compression or high shear stress. When the piston moves down, a controlled hydrodynamic overpressure and a shear stress is generated over the cell surface, stimulating the chondrocytes to improve their matrix production. The fluid dynamics inside the SQPR bioreactor is illustrated from an analytical and numerical point of view. We show how these models can predict the pressure, velocity field and wall shear stress generated on the cell surface of the construct. The bioreactor design is presented in detail and validation tests on chondrocytes are described.
In this chapter we describe a softness display based on the contact area spread rate (CASR) paradigm. This device uses a stretchable fabric as a substrate that can be touched by users, while contact area is directly measured via an optical system. By varying the stretching state of the fabric, different stiffness values can be conveyed to users. We describe a first technological implementation of the display and compare its performance in rendering various levels of stiffness with the one exhibited by a pneumatic CASR-based device. Psychophysical experiments are reported and discussed. Afterwards, we present a new technological implementation for the fabric-based display, with reduced dimensions and faster actuation, which enables rapid changes in the fabric stretching state. These changes are mandatory to properly track typical force/area curves of real materials. System performance in mimicking force-area curves obtained from real objects exhibits a high degree of reliability, also in eliciting overall discriminable levels of softness.
