Luca Ascari

Development and Experimental Analysis of a Soft Compliant Tactile Microsensor for Anthropomorphic Artificial Hand

This paper presents the development and preliminary experimental analysis of a soft compliant tactile microsensor (SCTM) with minimum thickness of 2 mm. A high shear sensitive triaxial force microsensor was embedded in a soft, compliant, flexible packaging. The performance of the whole system, including the SCTM, an electronic hardware and a processing algorithm, was evaluated by static calibration, maximum load tests, noise and dynamic tests, and by focusing on slippage experiments. A proper tradeoff between final robustness and sensitivity of the tactile device was identified. The experiments showed that the tactile sensor is sufficiently robust for application in artificial hands while sensitive enough for slip event detection. The sensor signals were elaborated with the cumulative summation algorithm and the results showed that the SCTM system could detect a slip event with a delay from a minimum of 24.5 ms to a maximum of 44 ms in the majority of experiments fulfilling the neurophysiological requirement.

Bio-inspired sensorization of a biomechatronic robot hand for the grasp-and-lift task

It has been concluded from numerous neurophysiological studies that humans rely on detecting discrete mechanical events that occur when grasping, lifting and replacing an object, i.e., during a prototypical manipulation task. Such events represent transitions between phases of the evolving manipulation task such as object contact, lift-off, etc., and appear to provide critical information required for the sequential control of the task as well as for corrections and parameterization of the task. We have sensorized a biomechatronic anthropomorphic hand with the goal to detect such mechanical transients. The developed sensors were designed to specifically provide the information about task-relevant discrete events rather than to mimic their biological counterparts. To accomplish this we have developed (1) a contact sensor that can be applied to the surface of the robotic fingers and that show a sensitivity to indentation and a spatial resolution comparable to that of the human glabrous skin, and (2) a sensitive low-noise three-axial force sensor that was embedded in the robotic fingertips and showed a frequency response covering the range observed in biological tactile sensors. We describe the design and fabrication of these sensors, their sensory properties and show representative recordings from the sensors during grasp-and-lift tasks. We show how the combined use of the two sensors is able to provide information about crucial mechanical events during such tasks. We discuss the importance of the sensorized hand as a test bed for low-level grasp controllers and for the development of functional sensory feedback from prosthetic devices.

Bio-inspired approach for the design and characterization of a tactile sensory system for a cybernetic prosthetic hand

Recent research in prosthetic hands aims at developing innovative cybernetic systems able to allow users to feel an artificial hand as part of their bodies by providing the tactile sensation of a natural hand. Such prostheses must be endowed with artificial proprioceptive and exteroceptive sensory systems as well as appropriate neural interfaces able to exchange sensory-motor signals between the body and the nervous system of an amputee. Based on consideration of available neurophysiological and behavioral data in humans and on the specific sensory needs to control a prototypical grasp-and-lift task, two kinds of sensors were developed: on-off contact sensor arrays and triaxial force sensors. Both sensor types were characterized and compared with their biological counterparts. Their ability to convey critical information during a lift task was evaluated with the sensors integrated in a biomechatronic cybernetic hand

A new active microendoscope for exploring the sub-arachnoid space in the spinal cord

This paper presents the design, development and preliminary test of a new active microendoscope for neuroendoscopy and therapy of the spinal cord. Endoscopy of the spinal sub-arachnoid space is useful for some pathologies, but it is a very challenging task for several reasons: the navigation space is very narrow, there are many blood vessels and delicate structures which could be damaged by maneuvers and large forces and, finally, the CerebroSpinal Fluid (CSF) is a peculiar environment which must be preserved. An innovative method for active safe navigation in the sub-arachnoid space has been devised, based on hydrojets sustentation of the endoscope. The hydrojets, if appropriately tuned and oriented, allow the tip of the endoscope to avoid the delicate structures of the spinal cord and could also assist propulsion. A MATLAB simulation of the hydrojets is illustrated and a digital controller for the regulation of the hydrojets is demonstrated. The pressure ripple is about 5%, as tested experimentally on a 2D simulator. A prototype of steerable microendoscope whose tip is equipped with hydrojets has been fabricated and tested in an artificial path simulating the sub-arachnoid space. Performance are quite interesting.

Bio-inspired grasp control in a robotic hand with massive sensorial input

The capability of grasping and lifting an object in a suitable, stable and controlled way is an outstanding feature for a robot, and thus far, one of the major problems to be solved in robotics. No robotic tools able to perform an advanced control of the grasp as, for instance, the human hand does, have been demonstrated to date. Due to its capital importance in science and in many applications, namely from biomedics to manufacturing, the issue has been matter of deep scientific investigations in both the field of neurophysiology and robotics. While the former is contributing with a profound understanding of the dynamics of real-time control of the slippage and grasp force in the human hand, the latter tries more and more to reproduce, or take inspiration by, the nature’s approach, by means of hardware and software technology. On this regard, one of the major constraints robotics has to overcome is the real-time processing of a large amounts of data generated by the tactile sensors while grasping, which poses serious problems to the available computational power. In this paper a bio-inspired approach to tactile data processing has been followed in order to design and test a hardware–software robotic architecture that works on the parallel processing of a large amount of tactile sensing signals. The working principle of the architecture bases on the cellular nonlinear/neural network (CNN) paradigm, while using both hand shape and spatial–temporal features obtained from an array of microfabricated force sensors, in order to control the sensory-motor coordination of the robotic system. Prototypical grasping tasks were selected to measure the system performances applied to a computer-interfaced robotic hand. Successful grasps of several objects, completely unknown to the robot, e.g. soft and deformable objects like plastic bottles, soft balls, and Japanese tofu, have been demonstrated.

Design of a wearable sensing system for human motion monitoring in physical rehabilitation.

Human motion monitoring and analysis can be an essential part of a wide spectrum of applications, including physical rehabilitation among other potential areas of interest. Creating non-invasive systems for monitoring patients while performing rehabilitation exercises, to provide them with an objective feedback, is one of the current challenges. In this paper we present a wearable multi-sensor system for human motion monitoring, which has been developed for use in rehabilitation. It is composed of a number of small modules that embed high-precision accelerometers and wireless communications to transmit the information related to the body motion to an acquisition device. The results of a set of experiments we made to assess its performance in real-world setups demonstrate its usefulness in human motion acquisition and tracking, as required, for example, in activity recognition, physical/athletic performance evaluation and rehabilitation.

A bioinspired autonomous swimming robot as a tool for studying goal-directed locomotion

The bioinspired approach has been key in combining the disciplines of robotics with neuroscience in an effective and promising fashion. Indeed, certain aspects in the field of neuroscience, such as goal-directed locomotion and behaviour selection, can be validated through robotic artefacts. In particular, swimming is a functionally important behaviour where neuromuscular structures, neural control architecture and operation can be replicated artificially following models from biology and neuroscience. In this article, we present a biomimetic system inspired by the lamprey, an early vertebrate that locomotes using anguilliform swimming. The artefact possesses extra- and proprioceptive sensory receptors, muscle-like actuation, distributed embedded control and a vision system. Experiments on optimised swimming and on goal-directed locomotion are reported, as well as the assessment of the performance of the system, which shows high energy efficiency and adaptive behaviour. While the focus is on providing a robotic platform for testing biological models, the reported system can also be of major relevance for the development of engineering system applications.

Experimental Analysis of a Soft Compliant Tactile Microsensor to be Integrated in an Anthropomorphic Artificial Hand

This paper presents the experimental analysis of a high shear sensitive 1.4mm3 three-axis force microsensor embedded in a soft, compliant and flexible packaging with minimum thickness of 2mm. The study is aimed at investigating the response of the tactile microsensor when it is stimulated with a combination of normal and shear loads. Experimental analysis is focused on the transient phenomena when a change of static to dynamic friction occurs at the packaged microsensor surface during interaction with an external object. According to a bioinspired design approach that is based on the emulation of natural mechanoreceptors of the human skin for providing appropriate tactile event encoding, the transient behaviour quantitative analysis is fundamental for assessing if the sensor is applicable in an artificial hand for controlling grasping and manipulation of an object.Copyright

Human-Robot Shared Control for Robot-Assisted Endoscopy of the Spinal Cord

The biomedical application this paper refers to is the neuroendoscopy of the sub-arachnoid spinal space. Such a kind of endoscopy is strongly challenging due to the tiny space to be explored and to the delicate anatomical structures which lie into it. In order to have more precision and control in catheter maneuvering, and a more efficient monitoring of medical parameters, a robotic system has been conceived. In this paper, proper strategies of human-robot shared control are introduced so as to enhance the degree of safety of the endoscopic exploration. The proposed methods are strongly based on a deep exploitation of sensorial feedbacks. In particular, the focus of the paper is on vision and pressure sensory feedbacks. The surgeon interacts with the robotic system by means of human-machine interfaces. The automatic control mainly operates at two levels; a low-level and a high-level control, implemented by an Electronic Unit and by a Workstation, respectively. Experimental results prove the reliability and the effectiveness of the proposed algorithms and their suitability to be employed in real time operation

A tool for linguistic assessment of rehabilitation exercises

In this paper, human motion analysis is performed by modeling a physical complex exercise in order to provide feedback about the patients performance in rehabilitation therapies. The Sun Salutation exercise, which is a flowing sequence of 12 yoga poses, is analyzed. This exercise provides physical benefits as improving the strength and flexibility of the muscles and the alignment of the spinal column. A temporal series of measures that contains a numerical description of this sequence is obtained by using a wearable sensing system for monitoring, which is formed by five high precision tri-axial accelerometer sensors worn by the patient while performing the exercise. Due to the complexity of the exercise and the huge amount of available data, its interpretation is a challenging task. Therefore, this paper describes the design of a computational system able of interpreting and generating linguistic descriptions about this exercise. Previous works on both Granular Linguistic Models of Phenomena and Fuzzy Finite State Machines are used to create a basic linguistic model of the Sun Salutation. This model allows generating human friendly reports focused on the assessment of the exercise quality based on its symmetry, stability and rhythm.