Combining electroencephalographic activity and instantaneous heart rate for assessing brain–heart dynamics during visual emotional elicitation in healthy subjects
Towards the development of an EIT-based stretchable sensor for multi-touch industrial human-computer interaction systems
Publication Type
Conference Paper
Year of Publication
2016
Conference Name
Cross-Cultural Design 8th International Conference, CCD 2016, Held as Part of HCI International 2016, Toronto, ON, Canada, July 17-22, 2016, Proceedings
A highly stretchable artificial sensitive skin using EIT
Publication Type
Conference Paper
Year of Publication
2016
Conference Name
Book of abstracts: 16th International Conference on Electrical Bio-Impedance, 17th International Conference on Electrical Impedance Tomography. ICEBI and EIT Stockholm 19–23 June 2016
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.
In motor control studies, the question on which
parameters human beings and animals control through their
nervous system has been extensively explored and discussed,
and several hypotheses proposed. It is widely acknowledged
that useful inputs in this problem could be provided by
developing artificial replication of the neuromusculoskeletal
system, to experiment different motor control hypothesis. In
this paper we present such device, which reproduces many of
the characteristics of an agonistic-antagonistic muscular pair
acting on a joint.
Variable stiffness actuators (VSAs) are complex mechatronic devices that are developed to build passively compliant, robust, and dexterous robots. Numerous different hardware designs have been developed in the past two decades to address various demands on their functionality. This review paper gives a guide to the design process from the analysis of the desired tasks identifying the relevant attributes and their influence on the selection of different components such as motors, sensors, and springs. The influence on the performance of different principles to generate the passive compliance and the variation of the stiffness are investigated. Furthermore, the design contradictions during the engineering process are explained in order to find the best suiting solution for the given purpose. With this in mind, the topics of output power, potential energy capacity, stiffness range, efficiency, and accuracy are discussed. Finally, the dependencies of control, models, sensor setup, and sensor quality are addressed.
This study describes an actuated bioreactor which mimics the pulsatile contractile motion of the intestinal barrier using electro-responsive elastomers as smart materials that undergo deformation upon electrical stimulation. The device consists of an annular dielectric elastomer actuator working as a radial artificial muscle able to rhythmically contract and relax a central cell culture well. The bioreactor maintained up to 4 h of actuation at a frequency of 0.15 Hz and a strain of 8%–10%, to those of the cyclic contraction and relaxation of the small intestine. In vitro tests demonstrated that the device was biocompatible and cell-adhesive for Caco-2 cells, which formed a confluent monolayer following 21 days of culture in the central well. In addition, cellular adhesion and cohesion were maintained after 4 h of continuous cyclic strain. These preliminary results encourage further investigations on the use of dielectric elastomer actuation as a versatile technology that might overcome the limitations of commercially available pneumatic driving systems to obtain bioreactors that can cyclically deform cell cultures in a biomimetic fashion.
Several advanced control laws are available for
complex robotic systems such as humanoid robots and mobile
manipulators. Controls are usually developed for locomotion or
for manipulation purposes. Resulting motions are usually executed
sequentially and the potentiality of the robotic platform
is not fully exploited.
In this work we consider the problem of loco–manipulation
planning for a robot with given parametrized control laws
known as primitives. Such primitives, may have not been
designed to be executed simultaneously and by composing
them instability may easily arise. With the proposed approach,
primitives combination that guarantee stability of the system
are obtained resulting in complex whole–body behavior.
A formal definition of motion primitives is provided and a
random sampling approach on a manifold with limited dimension
is investigated. Probabilistic completeness and asymptotic
optimality are also proved. The proposed approach is tested
both on a mobile manipulator and on the humanoid robot
Walk-Man, performing loco–manipulation tasks.
Notes
This work is supported by the European commission project Walk-Man EU FP7-ICT no. 611832 and the ECs Horizon 2020 robotics program ICT-23-2014 under grant agreement 644727 (CogIMon)
Compliance in robot design and control is often introduced to improve the robot performance in tasks where interaction with environment or human is required. However a rigorous method to choose the correct level of compliance is still not available. In this work we use robust optimization as a tool to select the optimal compliance value in a robotenvironment interaction scenario under uncertainties. We propose an approach that can be profitably applied on a variety of tasks, e.g.manipulation tasks or locomotion tasks. The aim is to minimize the forces of interaction considering model constraints and uncertainties. Numerical results show that: i) in case of perfect knowledge of the environment stiff robots behave better in terms of force minimization, ii) in case of uncertainties the optimal stiffness of the robot is lower than the previous case and optimal solutions provide a faster task accomplishment, iii) the optimal stiffness decreases as a function of the uncertainty measure. Experiments are carried out in a realistic set-up in case of bi-manual object handover.
Notes
This work was supported by the European Commission projects (FP7 framework) Walk-Man and the European Commission Grant no. H2020- ICT-645599 “SOMA”: SOft MAnipulation
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.
In this paper a quasi-static framework for optimally controlling the contact force distribution is experimentally verified with the full-size compliant humanoid robot Walk-Man. The proposed approach is general enough to cope with multi-contact scenarios, i.e. robot-environment interactions occurring on feet and hands, up to the more general case of whole-body loco-manipulation, in which the robot is in contact with the environment also with the internal limbs, with a consequent loss of contact force controllability. Experimental tests were conducted with the Walk-Man robot (i) standing on flat terrain, (ii) standing on uneven terrain and (iii) interacting with the environment with both feet and a hand touching a vertical wall. Moreover, the influence of unmodeled weight on the robot, and the combination with a higher priority Cartesian tasks are shown. Results are presented also in the attached video.
Many walking robot presented in literature stand
on rigid flat feet, with a few notable exceptions that embed
flexibility in their feet to optimize the energetic cost of walking.
This paper proposes a novel adaptive robot foot design, whose
main goal is to ease the task of standing and walking on uneven
terrains. After explaining the rationale behind our design
approach, we present the design of the SoftFoot, a foot able
to comply with uneven terrains and to absorb shocks thanks to
its intrinsic adaptivity, while still being able to rigidly support
the stance, maintaining a rather extended contact surface,
and effectively enlarging the equivalent support polygon. The
paper introduces the robot design and prototype and presents
preliminary validation and comparison versus a rigid flat foot
with comparable footprint and sole.
A novel MATLAB/Simulink based modeling and simulation environment for the design and rapid prototyping of state-of-the-art aircraft control systems is proposed. The toolbox, named APRICOT, is able to simulate the longitudinal and laterodirectional dynamics of an aircraft separately, as well as the complete 6 degrees of freedom dynamics. All details of the dynamics can be easily customized in the toolbox, some examples are shown in the paper. Moreover, different aircraft models can be easily integrated. The main goal of APRICOT is to provide a simulation environment to test and validate different control laws with different aircraft models. Hence, the proposed toolbox has applicability both for educational purposes and control rapid prototyping. With respect to similar software packages, APRICOT is customizable in all its aspects, and has been released as open source software. An interface with Flightgear Simulator allows for online visualization of the flight. Examples of control design with simulation experiments are reported and commented.
