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
The past thirty years have seen increasingly rapid advances in the field of laparoscopic surgery, in part because of the use of robots. A well-known example is the da Vinci surgical system. However, far too little attention has been paid to Hand Assisted Laparoscopic Surgery (HALS), a surgery in which the surgeon introduces the non-dominant hand into the abdomen of the patient. The risk of collision between the hand of the surgeon and the tool moved by the robot is the reason why these robots for laparoscopic surgery are not appropriate for HALS. On the other hand, in recent years, there has been an increasing interest in wearables, which have been introduced in our daily life. This interest and the lack of surgery robots for HALS are the reasons to develop a sensing glove which co-works whit a collaborative robot in this kind of surgery. The aim of this paper is to study the use of a sensing glove which will provide information of the movements of the surgeon’s hand to the collaborative robot. This information determinates the actions that the robot will carry on. The first step was to define different movements of the hand which could be identified. An algorithm identifies these movements using the data given by the sensing glove. For the purpose of algorithm accuracy measurement, 4 persons wearing the sensing glove made a sequence with different movements. The evidence from this study suggests that a sensing glove can be used to send information of the movements of the surgeon’s hand to a collaborative robot during a HALS.
In this paper we present the design of a one degree of freedom assistive platform to augment the strength of upper limbs. The core element is a variable stiffness actuator, closely reproducing the behavior of a pair of antagonistic muscles. The novelty introduced by this device is the analogy of its control parameters with those of the human muscle system, the threshold lengths. The analogy can be obtained from a proper tuning of the mechanical system parameters. Based on this, the idea is to control inputs by directly mapping the estimation of the muscle activations, e.g. via ElectroMyoGraphic(EMG) sensors, on the exoskeleton. The control policy resulting from this mapping acts in feedforward in a way to exploit the muscle-like dynamics of the mechanical device. Thanks to the particular structure of the actuator, the exoskeleton joint stiffness naturally results from that mapping. The platform as well as the novel control idea have been experimentally validated and the results show a substantial reduction of the subject muscle effort.
Low stiffness elements have a number of applications in Soft Robotics, from Series Elastic Actuators (SEA) to torque sensors for compliant systems. In its general formulation, the design problem of elastic components is complex and depends on several variables: material properties, load range, shape factor and size constraints. Consequently, most of the spring designs presented in literature are based on heuristics or are optimized for specific working conditions. This work presents the design study and characterization of a scalable spoked elastic element with hinge tip constraints. We compared the proposed design with three existing spring principles, showing that the spoked solution is the convenient option for low-stiffness and low shape factor elastic elements. Therefore, a design analysis on the main scaling parameters of the spoked spring, namely number of spokes and type of constraints, is presented. Finally, an experimental characterization has been conducted on physical prototypes. The agreement among simulations and experimental results demonstrates the effectiveness of the proposed concept.
Robotic hands embedding human motor control principles in their mechanical design are getting increasing interest thanks to their simplicity and robustness, combined with good performance. Another key aspect of these hands is that humans can use them very effectively thanks to the similarity of their behavior with real hands. Nevertheless, controlling more than one degree of actuation remains a challenging task. In this paper, we take advantage of these characteristics in a multi-synergistic prosthesis. We propose an integrated setup composed of Pisa/IIT SoftHand 2 and a control strategy which simultaneously and proportionally maps the human hand movements to the robotic hand. The control technique is based on a combination of non-negative matrix factorization and linear regression algorithms. It also features a real-time continuous posture compensation of the electromyographic signals based on an IMU. The algorithm is tested on five healthy subjects through an experiment in a virtual environment. In a separate experiment, the efficacy of the posture compensation strategy is evaluated on five healthy subjects and, finally, the whole setup is successfully tested in performing realistic daily life activities.
The paper presents the first simulative results and algorithmic developments of the task-priority based control applied to a distributed sampling network in an area coverage or adaptive sampling mission scenario. The proposed approach allowing the fulfilment of a chain of tasks with decreasing priority each of which directly related to both operability and safety aspects of the entire mission. The task-priority control is presented both in the centralized and decentralized implementations showing a comparison of performance. Finally simulations of the area coverage mission scenario are provided showing the effectiveness of the proposed approach.
The cerebellum is a crucial brain structure in enabling precise motor control in animals. Recent advances suggest that the timing of the plasticity rule of Purkinje cells, the main cells of the cerebellum, is matched to behavioral function.Simultaneously, counter-factual predictive control (CFPC), a cerebellar-based control scheme, has shown that the optimal rule for learning feed-forward action in an adaptive filter playing the role of the cerebellum must include a forward model of the system controlled. Here we show how the same learning rule obtained in CFPC, which we term as Model-enhanced least mean squares (ME-LMS), emerges in the problem of learning the gains of a feedback controller. To that end, we frame a model-reference adaptive control (MRAC) problem and derive an adaptive control scheme treating the gains of a feedback controller as if they were the weights of an adaptive linear unit. Our results demonstrate that the approach of controlling plasticity with a forward model of the subsystem controlled can provide a solution to a wide set of adaptive control problems
Touch provides an important cue to perceive the physical properties of the external objects. Recent studies showed that tactile sensation also contributes to our sense of hand position and displacement in perceptual tasks. In this study, we tested the hypothesis that, sliding our hand over a stationary surface, tactile motion may provide a feedback for guiding hand trajectory. We asked participants to touch a plate having parallel ridges at different orientations and to perform a self-paced, straight movement of the hand. In our daily-life experience, tactile slip motion is equal and opposite to hand motion. Here, we used a well-established perceptual illusion to dissociate, in a controlled manner, the two motion estimates. According to previous studies, this stimulus produces a bias in the perceived direction of tactile motion, predicted by tactile flow model. We showed a systematic deviation in the movement of the hand towards a direction opposite to the one predicted by tactile flow, supporting the hypothesis that touch contributes to motor control of the hand. We suggested a model where the perceived hand motion is equal to a weighted sum of the estimate from classical proprioceptive cues (e.g., from musculoskeletal system) and the estimate from tactile slip.
Notes
This work is supported in part by the European Research Council under the Advanced Grant SoftHands “A Theory of Soft Synergies for a New Generation of Artificial Hands” no. ERC-291166, by the EU H2020 project “SOFTPRO: Synergy-based Open-source Foundations and Technologies for Prosthetics and RehabilitatiOn” (no. 688857) and by the EU FP7 project (no. 601165), “WEARable HAPtics for Humans and Robots (WEARHAP)”. We thank Priscilla Balestrucci and Colleen P. Ryan for helpful comments and suggestions.
Myoelectric prostheses have seen increased application in clinical practice and research, due to their potential for good functionality and versatility. Yet, myoelectric prostheses still suffer from a lack of intuitive control and haptic feedback, which can frustrate users and lead to abandonment. To address this problem, we propose to convey proprioceptive information for a prosthetic hand with skin stretch using the Rice Haptic Rocker. This device was integrated with the myo-controlled version of Pisa/IIT SoftHand and a size discrimination test with 18 able bodied subjects was performed to evaluate the effectiveness of the proposed approach. Results show that the Rice Haptic Rocker can be successfully used to convey proprioceptive information. A Likert survey was also presented to the experiment participants, who evaluated the integrated setup as easy to use and effective in conveying proprioception.
Notes
The authors gratefully acknowledge Matteo Rossi for his valuable advice and Mikaela Juzswik for her unique contribution in the physical realization of some of the equipment used in the experiments. This work was partially supported by the European Community funded project WEARHAP (contract 601165), by the European Commission project (Horizon 2020 research program) SOFTPRO (no. 688857), by the ERC Advanced Grant no. 291166 SoftHands and by the NSF grant IIS-1065497.
An effective robotic wrist represents a key enabling element in robotic manipulation, especially in prosthetics. In this paper, we propose an under-actuated wrist system, which is also adaptable and allows to implement different under-actuation schemes. Our approach leverages upon the idea of soft synergies - in particular the design method of adaptive synergies - as it derives from the field of robot hand design. First we introduce the design principle and its implementation and function in a configurable test bench prototype, which can be used to demonstrate the feasibility of our idea. Furthermore, we report on results from preliminary experiments with humans, aiming to identify the most probable wrist pose during the pre-grasp phase in activities of daily living. Based on these outcomes, we calibrate our wrist prototype accordingly and demonstrate its effectiveness to accomplish grasping and manipulation tasks.
