SORI: A softness-rendering interface to unravel the nature of softness perception.

Tactile perception of softness serves a critical role in the survival, well-being, and social interaction among various species, including humans. This perception informs activities from food selection in animals to medical palpation for disease detection in humans. Despite its fundamental importance, a comprehensive understanding of how softness is neurologically and cognitively processed remains elusive. Previous research has demonstrated that the somatosensory system leverages both cutaneous and kinesthetic cues for the sensation of softness. Factors such as contact area, depth, and force play a particularly critical role in sensations experienced at the fingertips. Yet, existing haptic technologies designed to explore this phenomenon are limited, as they often couple force and contact area, failing to provide a real-world experience of softness perception. Our research introduces the softness-rendering interface (SORI), a haptic softness display designed to bridge this knowledge gap. Unlike its predecessors, SORI has the unique ability to decouple contact area and force, thereby allowing for a quantitative representation of softness sensations at the fingertips. Furthermore, SORI incorporates individual physical fingertip properties and model-based softness cue estimation and mapping to provide a highly personalized experience. Utilizing this method, SORI quantitatively replicates the sensation of softness on stationary, dynamic, homogeneous, and heterogeneous surfaces. We demonstrate that SORI accurately renders the surfaces of both virtual and daily objects, thereby presenting opportunities across a range of fields, from teleoperation to medical technology. Finally, our proposed method and SORI will expedite psychological and neuroscience research to unlock the nature of softness perception.

Designing minimal and scalable insect-inspired multi-locomotion millirobots.

In ant colonies, collectivity enables division of labour and resources1-3 with great scalability. Beyond their intricate social behaviours, individuals of the genus Odontomachus4, also known as trap-jaw ants, have developed remarkable multi-locomotion mechanisms to 'escape-jump' upwards when threatened, using the sudden snapping of their mandibles5, and to negotiate obstacles by leaping forwards using their legs6. Emulating such diverse insect biomechanics and studying collective behaviours in a variety of environments may lead to the development of multi-locomotion robotic collectives deployable in situations such as emergency relief, exploration and monitoring7; however, reproducing these abilities in small-scale robotic systems with simple design and scalability remains a key challenge. Existing robotic collectives8-12 are confined to two-dimensional surfaces owing to limited locomotion, and individual multi-locomotion robots13-17 are difficult to scale up to large groups owing to the increased complexity, size and cost of hardware designs, which hinder mass production. Here we demonstrate an autonomous multi-locomotion insect-scale robot (millirobot) inspired by trap-jaw ants that addresses the design and scalability challenges of small-scale terrestrial robots. The robot's compact locomotion mechanism is constructed with minimal components and assembly steps, has tunable power requirements, and realizes five distinct gaits: vertical jumping for height, horizontal jumping for distance, somersault jumping to clear obstacles, walking on textured terrain and crawling on flat surfaces. The untethered, battery-powered millirobot can selectively switch gaits to traverse diverse terrain types, and groups of millirobots can operate collectively to manipulate objects and overcome obstacles. We constructed the ten-gram palm-sized prototype-the smallest and lightest self-contained multi-locomotion robot reported so far-by folding a quasi-two-dimensional metamaterial18 sandwich formed of easily integrated mechanical, material and electronic layers, which will enable assembly-free mass-manufacturing of robots with high task efficiency, flexibility and disposability.

Text-to-Microstructure Generation Using Generative Deep Learning.

Designing novel materials is greatly dependent on understanding the design principles, physical mechanisms, and modeling methods of material microstructures, requiring experienced designers with expertise and several rounds of trial and error. Although recent advances in deep generative networks have enabled the inverse design of material microstructures, most studies involve property-conditional generation and focus on a specific type of structure, resulting in limited generation diversity and poor human-computer interaction. In this study, a pioneering text-to-microstructure deep generative network (Txt2Microstruct-Net) is proposed that enables the generation of 3D material microstructures directly from text prompts without additional optimization procedures. The Txt2Microstruct-Net model is trained on a large microstructure-caption paired dataset that is extensible using the algorithms provided. Moreover, the model is sufficiently flexible to generate different geometric representations, such as voxels and point clouds. The model's performance is also demonstrated in the inverse design of material microstructures and metamaterials. It has promising potential for interactive microstructure design when associated with large language models and could be a user-friendly tool for material design and discovery.

Hand and face somatotopy shown using MRI-safe vibrotactile stimulation with a novel soft pneumatic actuator (SPA)-skin interface.

The exact somatotopy of the human facial representation in the primary somatosensory cortex (S1) remains debated. One reason that progress has been hampered is due to the methodological challenge of how to apply automated vibrotactile stimuli to face areas in a manner that is: (1) reliable despite differences in the curvatures of face locations; and (2) MR-compatible and free of MR-interference artefacts when applied in the MR head-coil. Here we overcome this challenge by using soft pneumatic actuator (SPA) technology. SPAs are made of a soft silicon material and can be in- or deflated by means of airflow, have a small diameter, and are flexible in structure, enabling good skin contact even on curved body surfaces (as on the face). To validate our approach, we first mapped the well-characterised S1 finger layout using this novel device and confirmed that tactile stimulation of the fingers elicited characteristic somatotopic finger activations in S1. We then used the device to automatically and systematically deliver somatosensory stimulation to different face locations. We found that the forehead representation was least distant from the representation of the hand. Within the face representation, we found that the lip representation is most distant from the forehead representation, with the chin represented in between. Together, our results demonstrate that this novel MR compatible device produces robust and clear somatotopic representational patterns using vibrotactile stimulation through SPA-technology.

Sensorless force and displacement estimation in soft actuators.

Sensing forms an integral part of soft matter based robots due to their compliance, dependence on loading conditions, and virtually infinite degrees of freedom. Previous studies have developed several extrinsic sensors and embedded them into soft actuators for displacement and force estimation. What has not been investigated is whether soft robots themselves possess intrinsic sensing capabilities, especially in the case of pneumatically powered soft robots. Such an approach, that exploits the inherent properties of a system toward sensing is called sensorless estimation. Here, we introduce sensorless estimation for the first time in pneumatically powered soft actuators. Specifically, we show that the intrinsic properties of pressure and volume can be used to estimate the output force and displacement of soft actuators. On testing this approach with a bending actuator, we observed errors under 10% and 15% for force and displacement estimation respectively, with randomized and previously unseen test conditions. We also show that combining this approach with a conventional embedded sensor improves estimation accuracy due to sensing redundancy. By modelling soft actuators additionally as sensors, this work presents a new, readily implementable sensing modality that helps us better understand the highly complex behaviour of soft matter based robots.

Centralized care management support for "high utilizers" in primary care practices at an academic medical center.

Although evidence of effectiveness is limited, care management based outside primary care practices or hospitals is receiving increased attention. The University of Michigan (UM) Complex Care Management Program (CCMP) provides care management for uninsured and underinsured, high-utilizing patients in multiple primary care practices. To inform development of optimal care management models, we describe the CCMP model and characteristics and health care utilization patterns of its patients. Of a consecutive series of 49 patients enrolled at CCMP in 2011, the mean (SD) age was 48 (+/- 14); 23 (47%) were women; and 29 (59%) were White. Twenty-eight (57%) had two or more chronic medical conditions, 39 (80%) had one or more psychiatric condition, 28 (57%) had a substance abuse disorder, and 11 (22%) were homeless. Through phone, e-mail, and face-to-face contact with patients and primary care providers (PCPs), care managers coordinated health and social services and facilitated access to medical and mental health care. Patients had a mean (SD) number of hospitalizations and emergency room (ER) visits in 6 months prior to enrollment of2.2 (2.5) and 4.2 (4.3), respectively, with a nonstatistically significant decrease in hospitalizations, hospital days, and emergency room visits in 6 months following enrollment in CCMP. Centralized care management support for primary care practices engages high-utilizing patients with complex medical and behavioral conditions in care management that would be difficult to provide through individual practices and may decrease health care utilization by these patients.

Lattice-and-Plate Model: Mechanics Modeling of Physical Origami Robots.

Origami robots are characterized by their compact design, quasi-two-dimensional manufacturing process, and folding joint-based transmission kinematics. The physical requirements in terms of payload, range of motion, and embedding core robotic components have made it unrealistic to rely on conventional mathematical models for designing these new robots. Therefore, origami robots require a comprehensive approach to model their mechanics. Currently, there is no generalized mechanics model to achieve this goal. Therefore, in this work, we propose a nonlinear lattice-and-plate model to simulate the mechanics of physical origami robots within several seconds, including the localized bending on flexible hinges, global displacements of rigid panels, and trajectory of predefined outputs. Moreover, this proposed model captures the large displacement and self-contact of adjacent panels during locomotion. We validate the efficiency of the model on various origami actuators, grippers, and metamaterials. To conclude, the computational model can help to accelerate the design iteration of origami robots.

Earwig-inspired foldable origami wing for micro air vehicle gliding.

Foldable wings serve as an effective solution for reducing the size of micro air vehicles (MAVs) during non-flight phases, without compromising the gliding capacity provided by the wing area. Among insects, earwigs exhibit the highest folding ratio in their wings. Inspired by the intricate folding mechanism in earwig hindwings, we aimed to develop artificial wings with similar high-folding ratios. By leveraging an origami hinge, which is a compliant mechanism, we successfully designed and prototyped wings capable of opening and folding in the wind, which helps reduce the surface area by a factor of seven. The experimental evaluation involved measuring the lift force generated by the wings under Reynolds numbers less than 2.2 × 104. When in the open position, our foldable wings demonstrated increased lift force proportional to higher wind speeds. Properties such as wind responsiveness, efficient folding ratios, and practical feasibility highlight the potential of these wings for diverse applications in MAVs.