Francesco Visentin

Hydrodynamic pressure sensing with an artificial lateral line in steady and unsteady flows

With the overall goal being a better understanding of the sensing environment from the local perspective of a situated agent, we studied uniform flows and Kármán vortex streets in a frame of reference relevant to a fish or swimming robot. We visualized each flow regime with digital particle image velocimetry and then took local measurements using a rigid body with laterally distributed parallel pressure sensor arrays. Time and frequency domain methods were used to characterize hydrodynamically relevant scenarios in steady and unsteady flows for control applications. Here we report that a distributed pressure sensing mechanism has the capability to discriminate Kármán vortex streets from uniform flows, and determine the orientation and position of the platform with respect to the incoming flow and the centre axis of the Kármán vortex street. It also enables the computation of hydrodynamic features which may be relevant for a robot while interacting with the flow, such as vortex shedding frequency, vortex travelling speed and downstream distance between vortices. A Kármán vortex street was distinguished in this study from uniform flows by analysing the magnitude of fluctuations present in the sensor measurements and the number of sensors detecting the same dominant frequency. In the Kármán vortex street the turbulence intensity was 30% higher than that in the uniform flow and the sensors collectively sensed the vortex shedding frequency as the dominant frequency. The position and orientation of the sensor platform were determined via a comparative analysis between laterally distributed sensor arrays; the vortex travelling speed was estimated via a cross-correlation analysis among the sensors.

FILOSE for Svenning: A Flow Sensing Bioinspired Robot

The trend of biomimetic underwater robots has emerged as a search for an alternative to traditional propeller-driven underwater vehicles. The drive of this trend, as in any other areas of bioinspired and biomimetic robotics, is the belief that exploiting solutions that evolution has already optimized leads to more advanced technologies and devices. In underwater robotics, bioinspired design is expected to offer more energy-efficient, highly maneuverable, agile, robust, and stable underwater robots. The 30,000 fish species have inspired roboticists to mimic tuna [1], rays [2], boxfish [3], eels [4], and others. The development of the first commercialized fish robot Ghostswimmer by Boston Engineering and the development of fish robots for field trials with specific applications in mind (http://www.roboshoal. com) mark a new degree of maturity of this engineering discipline after decades of laboratory trials.

What information do Karman streets offer to flow sensing

In this work, we focus on biomimetic lateral line sensing in Kármán vortex streets. After generating a Kármán street in a controlled environment, we examine the hydrodynamic images obtained with digital particle image velocimetry (DPIV). On the grounds that positioning in the flow and interaction with the vortices govern bio-inspired underwater locomotion, we inspect the fluid in the swimming robot frame of reference. We spatially subsample the flow field obtained using DPIV to emulate the local flow around the body. In particular, we look at various sensor configurations in order to reliably identify the vortex shedding frequency, wake wavelength and downstream flow speed. Moreover, we propose methods that differentiate between being in and out of the Kármán street with >70% accuracy, distinguish right from left with respect to Kármán vortex street centreline (>80%) and highlight when the sensor system enters the vortex formation zone (>75%). Finally, we present a method that estimates the relative position of a sensor array with respect to the vortex formation point within 15% error margin.

A Deformable Smart Skin for Continuous Sensing Based on Electrical Impedance Tomography

In this paper, we present a low-cost, adaptable, and flexible pressure sensor that can be applied as a smart skin over both stiff and deformable media. The sensor can be easily adapted for use in applications related to the fields of robotics, rehabilitation, or costumer electronic devices. In order to remove most of the stiff components that block the flexibility of the sensor, we based the sensing capability on the use of a tomographic technique known as Electrical Impedance Tomography. The technique allows the internal structure of the domain under study to be inferred by reconstructing its conductivity map. By applying the technique to a material that changes its resistivity according to applied forces, it is possible to identify these changes and then localise the area where the force was applied. We tested the system when applied to flat and curved surfaces. For all configurations, we evaluate the artificial skin capabilities to detect forces applied over a single point, over multiple points, and changes in the underlying geometry. The results are all promising, and open the way for the application of such sensors in different robotic contexts where deformability is the key point.

Sheet type soft robot with magnetic fluid for object transportation

In this paper, we propose a novel method for object transportation at an automated distribution and warehousing facility based on the use of a novel type of soft robot. The robot employs a magnetic fluids that is capable of adjusting its shape -creating concave and convex surfaces- depending on the presence of a magnetic gradient. By exploiting the deformation of the surface of the fluid, the system is able to provide physical force and mechanical work to raise and transport a spherical object to any desired destination on its surface. In this paper, we present the development of this novel robotic device, and the result of experiments that conducted to characterize the system and demonstrate the feasibility of the proposed method.

Towards flow-sensing robots: Situated analysis for PIV flow imaging

Fluid environments can be monitored experimentally through Particle Image Velocimetry (PIV), whereas recent technological developments allow endowing underwater robots with flow-sensing capabilities. This combination opens the way to designing for context-aware robot navigation. However, such innovation demands that flow analysis be carried out from a situated perspective, rather than from the traditional birds eye view. In this context, we present a PIV post-processing toolbox developed with the intention of bringing the observation point into the flow — to support exploring the sensing picture in a given flow environment, as well as characterizing the flow regime. In order to show how the toolbox can address questions emerging from a situated perspective, we present a case-study in regime-specific feature extraction.

Analytical derivation of elasticity in breast phantoms for deformation tracking

PurposePatient-specific biomedical modeling of the breast is of interest for medical applications such as image registration, image guided procedures and the alignment for biopsy or surgery purposes. The computation of elastic properties is essential to simulate deformations in a realistic way. This study presents an innovative analytical method to compute the elastic modulus and evaluate the elasticity of a breast using magnetic resonance (MRI) images of breast phantoms.MethodsAn analytical method for elasticity computation was developed and subsequently validated on a series of geometric shapes, and on four physical breast phantoms that are supported by a planar frame. This method can compute the elasticity of a shape directly from a set of MRI scans. For comparison, elasticity values were also computed numerically using two different simulation software packages.ResultsApplication of the different methods on the geometric shapes shows that the analytically derived elongation differs from simulated elongation by less than 9% for cylindrical shapes, and up to 18% for other shapes that are also substantially vertically supported by a planar base. For the four physical breast phantoms, the analytically derived elasticity differs from numeric elasticity by 18% on average, which is in accordance with the difference in elongation estimation for the geometric shapes. The analytic method has shown to be multiple orders of magnitude faster than the numerical methods.ConclusionIt can be concluded that the analytical elasticity computation method has good potential to supplement or replace numerical elasticity simulations in gravity-induced deformations, for shapes that are substantially supported by a planar base perpendicular to the gravitational field. The error is manageable, while the calculation procedure takes less than one second as opposed to multiple minutes with numerical methods. The results will be used in the MRI and Ultrasound Robotic Assisted Biopsy (MURAB) project.

Friend*Chip: A Bracelet with Digital Pet for Socially Inclusive Games for Children

Learning in groups have different potential benefits for children. They have the opportunity to solve problems together, to share experiences and to develop social skills. However, from teachers point of view, creating a safe and inclusive positive environment for children is not an simple task since each child has differences that represent a challenge for implementing effectively group dynamics. The focus of this work is the design of a system that motivates children to approach to others and create opportunities of social interaction. The system creates a fun and enjoyable situation that is always supervised by the teacher, who can monitor and change the group dynamics at any moment during the activity.

Deformable sensors for soft robot by electrical impedance tomography

Soft robots are by now an established trend in the robotic community. They are made by soft, deformable materials that enable them to easily conform to unstructured environment like biological systems do. In order to control this ability, sensors that return information about their spatial configuration and feedbacks from the environments are needed. Common solutions consist in the use of traditional type of sensors that can limit the capabilities of the deformable material. A different type of sensor has to be developed in order to exploit all the features of the material used for the robot structure. In this paper a first step toward the development of a novel type of sensor that enables sensing capabilities without limiting the deformation property of the soft material is presented. The sensor is based on a imaging technique known as Electrical Impedance Tomography.

The interaction between vortices and a biomimetic flexible fin

The fluid-structure interaction of flexible bodies in steady and unsteady flow is a key area of interest for the development of underwater vehicles. In the design of marine vehicles the flow can often be seen as an obstacle to overcome, whilst in nature a fish interacts with the flow and is capable of achieving a high level of efficiency. Therefore by understanding how fish – or flexible bodies – interact with the flow we may be able to achieve a better level of co-operation between our vehicles and their environment, potentially attaining a better efficiency in design.