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Edoardo Sinibaldi

Publications and source records attributed to Edoardo Sinibaldi.

5 recordsLinked to original sources

Receptogenesis in a Vascularized Robotic Embodiment

Equipping robotic systems with the capacity to generate $\textit{ex novo}$ hardware during operation extends physical adaptability. Unlike modular systems that rely on discrete component integration pre- or post-deployment, we envision physical adaptation through continuous in-body development via hardware synthesis. Drawing inspiration from circulatory systems that redistribute mass and function in biological organisms, we utilize fluidics to restructure the material interface, a capability currently unmatched in robotics. Here, we realize this proof-of-concept hardware generation through a vascularized robotic composite designed for programmable material synthesis, demonstrated via receptogenesis - the on-demand construction of sensors. By coordinating the fluidic transport of precursors with external localized UV irradiation, we drove an $\textit{in situ}$ photopolymerization that chemically reconstructed the vasculature from the inside out. This reaction converted precursors with photolatent initiator into a solid dispersion of UV-sensitive polypyrrole in PETG, establishing a sensing modality validated by a characteristic decrease in electrical impedance. The newly synthesized sensor closed a local control loop in real time to regulate wing flapping in a moth-inspired robotic demonstrator. Our work is a proof-of-concept materials basis for $\textit{ex novo}$ hardware generation in a vascularized composite - a step towards situated robots adapting to environmental cues.

cs.RO

Translating Milli/Microrobots with A Value-Centered Readiness Framework

Untethered mobile milli/microrobots hold transformative potential for interventional medicine by enabling more precise and entirely non-invasive diagnosis and therapy. Realizing this promise requires bridging the gap between groundbreaking laboratory demonstrations and successful clinical integration. Despite remarkable technical progress over the past two decades, most millirobots and microrobots remain confined to laboratory proof-of-concept demonstrations, with limited real-world feasibility. In this Review, we identify key factors that slow translation from bench to bedside, focusing on the disconnect between technical innovation and real-world application. We argue that the long-term impact and sustainability of the field depend on aligning development with unmet medical needs, ensuring applied feasibility, and integrating seamlessly into existing clinical workflows, which are essential pillars for delivering meaningful patient outcomes. To support this shift, we introduce a strategic milli/microrobot Technology Readiness Level framework (mTRL), which maps system development from initial conceptualization to clinical adoption through clearly defined milestones and their associated stepwise activities. The mTRL model provides a structured gauge of technological maturity, a common language for cross-disciplinary collaboration and actionable guidance to accelerate translational development toward new, safer and more efficient interventions.

cs.RO

Functional mimicry of Ruffini receptors with Fiber Bragg Gratings and Deep Neural Networks enables a bio-inspired large-area tactile sensitive skin

Collaborative robots are expected to physically interact with humans in daily living and workplace, including industrial and healthcare settings. A related key enabling technology is tactile sensing, which currently requires addressing the outstanding scientific challenge to simultaneously detect contact location and intensity by means of soft conformable artificial skins adapting over large areas to the complex curved geometries of robot embodiments. In this work, the development of a large-area sensitive soft skin with a curved geometry is presented, allowing for robot total-body coverage through modular patches. The biomimetic skin consists of a soft polymeric matrix, resembling a human forearm, embedded with photonic Fiber Bragg Grating (FBG) transducers, which partially mimics Ruffini mechanoreceptor functionality with diffuse, overlapping receptive fields. A Convolutional Neural Network deep learning algorithm and a multigrid Neuron Integration Process were implemented to decode the FBG sensor outputs for inferring contact force magnitude and localization through the skin surface. Results achieved 35 mN (IQR = 56 mN) and 3.2 mm (IQR = 2.3 mm) median errors, for force and localization predictions, respectively. Demonstrations with an anthropomorphic arm pave the way towards AI-based integrated skins enabling safe human-robot cooperation via machine intelligence.

cs.RO

Pulsatile Viscous Flows in Elliptical Vessels and Annuli: Solution to the Inverse Problem, with Application to Blood and Cerebrospinal Fluid Flow

We consider the fully-developed flow of an incompressible Newtonian fluid in a cylindrical vessel with elliptical cross-section (both an ellipse and the annulus between two confocal ellipses). In particular, we address an inverse problem, namely to compute the velocity field associated with a given, time-periodic flow rate. This is motivated by the fact that flow rate is the main physical quantity which can be actually measured in many practical situations. We propose a novel numerical strategy, which is nonetheless grounded on several analytical relations. The proposed method leads to the solution of some simple ordinary differential systems. It holds promise to be more amenable to implementation than previous approaches, which are substantially based on the challenging computation of Mathieu functions. Some numerical results are reported, based on measured data for human blood flow in the internal carotid artery, and cerebrospinal fluid (CSF) flow in the upper cervical region of the human spine. As expected, computational efficiency is the main asset of our solution: a speed-up factor over 10^3 was obtained, compared to more elaborate numerical approaches. The main goal of the present study is to provide an improved source of initial/boundary data for more ambitious numerical approaches, as well as a benchmark solution for pulsatile flows in elliptical sections with given flow rate. The proposed method can be effectively applied to bio-fluid dynamics investigations (possibly addressing key aspects of relevant diseases), to biomedical applications (including targeted drug delivery and energy harvesting for implantable devices), up to longer-term medical microrobotics applications.

math.AP

On the existence of hylomorphic vortices in the nonlinear Klein-Gordon equation

In this paper we prove the existence of vortices, namely standing waves with non null angular momentum, for the nonlinear Klein-Gordon equation in dimension $N\geq 3$. We show with variational methods that the existence of these kind of solutions, that we have called \emph{hylomorphic vortices}, depends on a suitable energy-charge ratio. Our variational approach turns out to be useful for numerical investigations as well. In particular, some results in dimension N=2 are reported, namely exemplificative vortex profiles by varying charge and angular momentum, together with relevant trends for vortex frequency and energy-charge ratio. The stability problem for hylomorphic vortices is also addressed. In the absence of conclusive analytical results, vortex evolution is numerically investigated: the obtained results suggest that, contrarily to solitons with null angular momentum, vortex are unstable.

math.AP