Co-Design Optimisation of Morphing Topology and Control of Winged Drones

The design and control of winged aircraft and drones is an iterative process aimed at identifying a compromise of mission-specific costs and constraints. When agility is required, shape-shifting (morphing) drones represent an efficient solution. However, morphing drones require the addition of actuated joints that increase the topology and control coupling, making the design process more complex. We propose a co-design optimisation method that assists the engineers by proposing a morphing drone's conceptual design that includes topology, actuation, morphing strategy, and controller parameters. The method consists of applying multi-objective constraint-based optimisation to a multi-body winged drone with trajectory optimisation to solve the motion intelligence problem under diverse flight mission requirements. We show that co-designed morphing drones outperform fixed-winged drones in terms of energy efficiency and agility, suggesting that the proposed co-design method could be a useful addition to the aircraft engineering toolbox

Whole-Body Trajectory Optimization for Robot Multimodal Locomotion

The general problem of planning feasible trajec-tories for multimodal robots is still an open challenge. This paper presents a whole-body trajectory optimisation approach that addresses this challenge by combining methods and tools developed for aerial and legged robots. First, robot models that enable the presented whole-body trajectory optimisation framework are presented. The key model is the so-called robot centroidal momentum, the dynamics of which is directly related to the models of the robot actuation for aerial and terrestrial locomotion. Then, the paper presents how these models can be employed in an optimal control problem to generate either terrestrial or aerial locomotion trajectories with a unified approach. The optimisation problem considers robot kinematics, momentum, thrust forces and their bounds. The overall approach is validated using the multimodal robot iRonCub, a flying humanoid robot that expresses a degree of terrestrial and aerial locomotion. To solve the associated optimal trajectory generation problem, we employ ADAM, a custom-made open-source library that implements a collection of algorithms for calculating rigid- body dynamics using CasADi

Learning to Walk and Fly with Adversarial Motion Priors

Robot multimodal locomotion encompasses the ability to transition between walking and flying, representing a significant challenge in robotics. This work presents an approach that enables automatic smooth transitions between legged and aerial locomotion. Leveraging the concept of Adversarial Motion Priors, our method allows the robot to imitate motion datasets and accomplish the desired task without the need for complex reward functions. The robot learns walking patterns from human-like gaits and aerial locomotion patterns from motions obtained using trajectory optimization. Through this process, the robot adapts the locomotion scheme based on environmental feedback using reinforcement learning, with the spontaneous emergence of mode-switching behavior. The results highlight the potential for achieving multimodal locomotion in aerial humanoid robotics through automatic control of walking and flying modes, paving the way for applications in diverse domains such as search and rescue, surveillance, and exploration missions. This research contributes to advancing the capabilities of aerial humanoid robots in terms of versatile locomotion in various environments.Comment: 6 pages, 8 figures, submitted to ICRA 202

Modeling and Control of Morphing Covers for the Adaptive Morphology of Humanoid Robots

This article takes a step to provide humanoid robots with adaptive morphology abilities. We present a systematic approach for enabling robotic covers to morph their shape, with an overall size fitting the anthropometric dimensions of a humanoid robot. More precisely, we present a cover concept consisting of two main components: a skeleton, which is a repetition of a basic element called node, and a soft membrane, which encloses the cover and deforms with its motion. This article focuses on the cover skeleton and addresses the challenging problems of node design, system modeling, motor positioning, and control design of the morphing system. The cover modeling focuses on kinematics, and a systematic approach for defining the system kinematic constraints is presented. Then, we apply genetic algorithms to find the motor locations so that the morphing cover is fully actuated. Finally, we present control algorithms that allow the cover to morph into a time-varying shape. The entire approach is validated by performing kinematic simulations with four different covers of square dimensions and having 3x3, 4x8, 8x8, and 20x20 nodes, respectively. For each cover, we apply the genetic algorithms to choose the motor locations and perform simulations for tracking a desired shape. The simulation results show that the presented approach ensures the covers to track a desired shape with good tracking performances

Could advanced drug delivery systems be the future in cardiovascular revascularization medicine?

Acute myocardial infarction, stroke and pulmonary embolism required a prompt revascularization to restore the normal blood flow as soon as possible. Fibrinolytic treatment has gradually become both dated and underused in the treatment of acute myocardial infarction, after the wide diffusion of cathlab and percutaneous transluminal coronary angioplasty. Conversely, the use of systemic thrombolysis remained a benchmark in the treatment of both ischemic stroke and massive pulmonary embolism. In daily clinical practice, the use of thrombolytic agents is often limited by absolute and/or relative contraindications and possible adverse events after the drug administration, as intracranial and/or extracranial bleeding events. To minimize these problems, during the last years, the introduction of nanotechnology in the field of cardiovascular revascularization medicine has created several fascinating results. In the present article, we describe these recent findings and their possible implications in future clinical practice

Centroidal Aerodynamic Modeling and Control of Flying Multibody Robots

This paper presents a modeling and control frame-work for multibody flying robots subject to non-negligible aero-dynamic forces acting on the centroidal dynamics. First, aero-dynamic forces are calculated during robot flight in different operating conditions by means of Computational Fluid Dynamics (CFD) analysis. Then, analytical models of the aerodynamics coefficients are generated from the dataset collected with CFD analysis. The obtained simplified aerodynamic model is also used to improve the flying robot control design. We present two control strategies: compensating for the aerodynamic effects via feedback linearization and enforcing the controller robustness with gain-scheduling. Simulation results on the jet-powered humanoid robot iRonCub validate the proposed approach

Pathogenic variants in SOX11 mimicking Pitt-Hopkins syndrome phenotype

: Pitt-Hopkins syndrome (PTHS) is a rare neurodevelopmental disorder characterised by severe intellectual disability (ID), distinctive facial features and autonomic nervous system dysfunction, caused by TCF4 haploinsufficiency. We clinically diagnosed with PTHS a 14 6/12 -year-old female, who had a normal status of TCF4. The pathogenic c.667del (p.Asp223MetfsTer45) variant in SOX11 was identified through whole exome sequencing (WES). SOX11 variants were initially reported to cause Coffin-Siris syndrome (CSS), characterised by growth restriction, moderate ID, coarse face, hypertrichosis and hypoplastic nails. However, recent studies have provided evidence that they give rise to a distinct neurodevelopmental disorder. To date, SOX11 variants are associated with a variable phenotype, which has been described to resemble CSS in some cases, but never PTHS. By reviewing both clinically and genetically 32 out of 82 subjects reported in the literature with SOX11 variants, for whom detailed information are provided, we found that 7/32 (22%) had a clinical presentation overlapping PTHS. Furthermore, we made a confirmation that overall SOX11 abnormalities feature a distinctive disorder characterised by severe ID, high incidence of microcephaly and low frequency of congenital malformations. Purpose of the present report is to enhance the role of clinical genetics in assessing the individual diagnosis after WES results