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.

Multi-modal deformation and temperature sensing for context-sensitive machines.

Owing to the remarkable properties of the somatosensory system, human skin compactly perceives myriad forms of physical stimuli with high precision. Machines, conversely, are often equipped with sensory suites constituted of dozens of unique sensors, each made for detecting limited stimuli. Emerging high degree-of-freedom human-robot interfaces and soft robot applications are delimited by the lack of simple, cohesive, and information-dense sensing technologies. Stepping toward biological levels of proprioception, we present a sensing technology capable of decoding omnidirectional bending, compression, stretch, binary changes in temperature, and combinations thereof. This multi-modal deformation and temperature sensor harnesses chromaticity and intensity of light as it travels through patterned elastomer doped with functional dyes. Deformations and temperature shifts augment the light chromaticity and intensity, resulting in a one-to-one mapping between stimulus modes that are sequentially combined and the sensor output. We study the working principle of the sensor via a comprehensive opto-thermo-mechanical assay, and find that the information density provided by a single sensing element permits deciphering rich and diverse human-robot and robot-environmental interactions.

Haptigami: A Fingertip Haptic Interface With Vibrotactile and 3-DoF Cutaneous Force Feedback.

Wearable fingertip haptic devices aim todeliver somatosensory feedback for applications such as virtual reality, rehabilitation, and enhancing hardware/physical control interfaces. However, providing various kinds of feedback requires several Degrees of Freedom (DoF) and high mechanical complexity which are mechanically difficult to achieve at the mesoscale. Using compliant low-profile transmissions embedded in an origami structure and PCBmotors as actuators, we designed and fabricated a novel 3-DoF fingertip haptic device, called Haptigami. This under-actuated system, measuring 36 x 25 x 26 mm and weighing 13 g, can render vibrotactile and cutaneous force feedback. We tested our device by creating a novel experimental protocol and robotic platform allowing quantitative characterization of mechanical performance. The current prototype of Haptigami produces 678 mN in compression, and 400 mN and 150 mN in shear for the Y and X directions, respectively. By virtue of its unique origami-inspired design, Haptigami brings a new direction for future designs of lightweight and compact wearable robots.

3D Printed Motor-Sensory Module Prototype for Facial Rehabilitation.

This work demonstrates the first 3D printed wearable motor-sensory module prototype designed for facial rehabilitation, focusing on facial paralysis. The novelty of the work lies in the fast fabrication of the first fully soft working prototype, including feedback control, with a focus on the methodology for individual customization. Facial paralysis results from a variety of conditions, and more wearable and modular technologies are needed to address the complexity of facial movement rehabilitation. Smiling muscles are especially important for both expression and eating, and so this work focuses on this motion as an example of how the module can be applied to mimic and support needed muscle movement. A generalized actuator-sensor pair with a feedback control system is created to translate signals from smiling on the healthy side of the face (notably temporal and zygomatic branch) to actuation on the paralyzed side of the face for augmented physiotherapy. Fabric and a sensor fluid are integrated during the silicone printing process to create a multicomponent wearable that is ready to use with minimal postprocessing. The actuators' force and vertical contraction results under a 0.98 and 1.96 N load meet the 1-7 N requirements needed for smiling. It is a challenge to measure soft surface-based force and contraction ratio consistently; therefore, a novel modular surface is designed to simulate the interaction of skin and bone using 3D printed hard plastic (bone) and a silicone sheet (skin). The actuator is tested on top of four different repeatable and standardized surface morphologies, and results reveal that the actuator force application will vary based on topography and hardness of the facial surface. Demonstration of the complete system on the face while collecting sensor and pressure data serves as a proof-of-concept and motivates potential applications in rapid customization of highly specialized soft wearable orthotics, prosthetics, and rehabilitation devices. This unique actuator-sensor combination can have additional applications for wearables due to the (1) customizability, (2) closed-loop control, and (3) unique "grounding" test platform.

Pneumatic Supply System Parameter Optimization for Soft Actuators.

Soft actuators using pressurized air are being widely used due to their inherent compliance, conformability, and customizability. These actuators are powered and controlled by pneumatic supply systems (PSSs) consisting of components such as compressors, valves, tubing, and reservoirs. Regardless of the choice of actuator, the PSS critically affects overall performance of soft robots because it governs the soft actuator pressure dynamics, and thereby, the general dynamic behavior. While selecting and controlling PSS components for meeting desired soft actuator performance, specifications such as PSS mass, volume, and duration of operation must also be considered. Currently, there is no comprehensive study on PSS optimization for meeting dynamic performance and PSS specifications, due to limited understanding of soft actuator pressure dynamics, large solution space for PSSs, and variability in soft actuators. By considering critical parameters of PSS and soft actuators, we introduce and demonstrate PSS parameter optimization. We propose a normalized model for soft actuator pressure dynamics and quantify the relationship between PSS parameters, soft actuator design parameters, and dynamic performance metrics of rise time, fall time, and actuation frequency. After experimental validation, we applied these results and optimally select and control PSS components to meet desired soft actuator performance for a soft exosuit, while minimizing mass of selected components. The measured pressure response with this prototype agrees well with simulations, with root mean square errors <5.2%. This work is a step toward furthering the scope of soft robotics, as it enables PSS modeling and optimization, for meeting the desired soft actuator performance while also addressing PSS specifications.

CMOS-Inspired Complementary Fluidic Circuits for Soft Robots.

The latest efforts in digital fluidic circuits' research aim at being electronics-free, light-weight, and compliant controllers for soft robots; however, challenges arise to adjust the fluidic circuit's digital logic operations. Currently there is no other way to modulate the amplitude or frequency but to structurally redesign the entire fluidic circuitry. This is mainly because there is currently no method to create an analog circuit-like behavior in the digital fluidic circuits using conventional digitized fluidic gates. In this work, a new approach is presented to designing a circuit with digitized fluidic gates that is comparable to an analog circuit capable of actively tuning the circuit's fluidic characteristics, such as pressure gain, amplitude of output, and time response. For the first time, a pressure-controlled oscillator is modeled, designed, and prototyped that not only controls the fluidic oscillation, but also modulates its frequency using only a single, quasi-static pressure input. It can also demonstrate the circuit's performance for the control of a soft robotic system by actively modulating the motion of a soft earthworm robot up to twice of crawling speeds. This work has distinct contributions to designing and building intelligent pneumatic controllers toward truly comprehensive soft robotic systems.

Multimodal pipe-climbing robot with origami clutches and soft modular legs.

In nature, climbing trees and pipes of varying diameters or even navigating inside of hollow pipes and tree holes is easy for some climbing animals and insects. However, today's pipe-climbing robots, which are important for automatically conducting periodic inspections and maintenance of pipelines to save time and keep humans away from hazardous environments, are designed mainly for a specific task, limiting their adaptability to different working scenarios and further implementation in real-life. In this paper, we propose a pipe-climbing robot with a soft linear actuator for bioinspired propulsion, two origami clutches to realize multi-degrees-of-freedom (DoF) motion and two pairs of soft modular legs for multimodal climbing. Design, modeling and experimental validation of the origami clutch are introduced in detail. Preliminary experimental results show that we can achieve a stroke of up to 289.6% and a maximum 45° bending angle on the soft linear actuator by regulating the air pressure inside the soft actuator and origami clutches. Additionally, by choosing the leg-type, three climbing modes, including out-pipe versatile mode, out-pipe high-force mode and in-pipe mode can be realized for particular working scenarios. A prototype climbing robot demonstrates that in out-pipe versatile mode, the robot can climb on the exterior of pipes made of various materials including PVC, rubber and metal with diameters ranging from 105 to 117 mm. In the out-pipe high-force mode, the climber can navigate along a specific pipe carrying maximum 675 g external load at the top or 200 g hanging from the bottom, as well as keeping functional without failure under static loads as high as 1968 g. In the in-pipe mode, the robot is able to travel inside pipes. This research might bridge the design gap between in-pipe and out-pipe climbing robots while offering an alternative option for soft robots to execute multi-DoF motion.

Closed-Loop Haptic Feedback Control Using a Self-Sensing Soft Pneumatic Actuator Skin.

In this article, we achieve a closed-loop control over haptic feedback, first time for an entirely soft platform. We prototyped a novel self-sensing soft pneumatic actuator (SPA) with soft strain sensors, called SPA-skin, which withstands large multiaxial strains and is capable of high-frequency sensing and actuation. To close-loop control the haptic feedback, the platform requires a cohesively integrated system. Our system consists of a stretchable low profile (<500 µm) SPA and an ultra-compliant thin-metal film strain sensor that create a novel bidirectional platform for tactile sensing via force-tunable vibratory feedback. With this prototype, we demonstrated control of the actuator shape in real time up to 100 Hz at output forces up to 1 N, maintained under variable mechanical loadings. We further characterized the SPA-skin platform for its static and dynamic behavior over a range of actuation amplitudes and frequencies as well as developed an analytical model of this system to predict the actuator inflation state only using the embedded sensor's resistance. Our SPA-skin is a multifunctional multilayer system that can readily be implemented as a high-speed wearable bidirectional interface for contact sensing and vibrotactile feedback.

Age-Dependent Asymmetry of Wrist Position Sense Is Not Influenced by Stochastic Tactile Stimulation.

Stochastic stimulation has been shown to improve movement, balance, the sense of touch, and may also improve position sense. This stimulation can be non-invasive and may be a simple technology to enhance proprioception. In this study, we investigated whether sub-threshold stochastic tactile stimulation of mechanoreceptors reduces age-related errors in wrist position estimation. Fifteen young (24.5±1.5y) and 23 elderly (71.7±7.3y) unimpaired, right-handed adults completed a wrist position gauge-matching experiment. In each trial, the participant's concealed wrist was moved to a target position between 10 and 30° of wrist flexion or extension by a robotic manipulandum. The participant then estimated the wrist's position on a virtual gauge. During half of the trials, sub-threshold stochastic tactile stimulation was applied to the wrist muscle tendon areas. Stochastic stimulation did not significantly influence wrist position sense. In the elderly group, estimation errors decreased non-significantly when stimulation was applied compared to the trials without stimulation [mean constant error reduction Δ µ ( θ c o n o f ) = 0 . 8 ° in flexion and Δ µ ( θ c o n o e ) = 0 . 7 ° in extension direction, p = 0.95]. This effect was less pronounced in the young group [ Δ µ ( θ c o n y ) = 0 . 2 ° in flexion and in extension direction, p = 0.99]. These improvements did not yield a relevant effect size (Cohen's d < 0.1). Estimation errors increased with target angle magnitude in both movement directions. In young participants, estimation errors were non-symmetric, with estimations in flexion [ µ ( θ c o n y f ) = 1 . 8 ° , σ ( θ c o n y f ) = 7 . 0 ° ] being significantly more accurate than in extension [ µ ( θ c o n y e ) = 8 . 3 ° , σ ( θ c o n y e ) = 9 . 3 ° , p < 0.01]. This asymmetry was not present in the elderly group, where estimations in flexion [ µ ( θ c o n o f ) = 7 . 5 ° , σ ( θ c o n o f ) = 9 . 8 ° ] were similar to extension [ µ ( θ c o n o e ) = 7 . 7 ° , σ ( θ c o n o e ) = 9 . 3 ° ]. Hence, young and elderly participants performed equally in extension direction, whereas wrist position sense in flexion direction deteriorated with age (p < 0.01). Though unimpaired elderly adults did not benefit from stochastic stimulation, it cannot be deduced that individuals with more severe impairments of their sensory system do not profit from this treatment. While the errors in estimating wrist position are symmetric in flexion and extension in elderly adults, young adults are more accurate when estimating wrist flexion, an effect that has not been described before.

Author Correction: Design and Computational Modeling of a Modular, Compliant Robotic Assembly for Human Lumbar Unit and Spinal Cord Assistance.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.