Rigid Components Research Articles

InferLoc: Hypothesis-Based Joint Edge Inference and Localization in Sparse Sensor Networks

Ranging-based localization is a fundamental problem in the Internet of Things and unmanned aerial vehicle networks. However, the nodes’ limited-ranging scope and users’ broad coverage purpose inevitably cause network sparsity or subnetwork sparsity. The performances of existing localization algorithms are extremely unsatisfactory in sparse networks. A crucial way to deal with the sparsity is to exploit the hidden knowledge provided by the unmeasured edges, which inspires this work to propose a hypothesis-based Joint Edge Inference and Localization algorithm called InferLoc . InferLoc mines the Unmeasured but Inferable Edges (UIEs). Each UIE is an unmeasured edge, but it is restricted through other edges in the network to be inside a rigid component, so it has only a limited number of possible lengths. We propose an efficient method to detect UIEs and geometric approaches to infer possible lengths for UIEs in 2D and 3D networks. The inferred possible lengths of UIEs are then treated as multiple hypotheses to determine the node locations and the lengths of UIEs simultaneously through a joint graph optimization process. In the joint graph optimization model, to make the 0/1 decision variables for hypotheses selection differentiable, differentiable functions are proposed to relax the 0/1 selections, and rounding is applied to select the final length after the optimization converges. We also prove the condition when a UIE can contribute to sparse localization. Extensive experiments show remarkably better accuracy and efficiency performances of InferLoc than the state-of-the-art network localization algorithms. In particular, it reduces the localization errors by more than 90% and speeds up the convergence time more than 100 times than that of the widely used G2O-based methods in sparse networks.

Soft Wearable Haptic Display and Flexible 3D Force Sensor for Teleoperated Surgical Systems

AbstractHaptic (touch) is important for effective interaction with the surroundings. In teleoperated surgical systems, its absence leads to reduced perception, making delicate tasks difficult and resulting in unexpected damage to surrounding tissues. To enhance safety, a force‐feedback system and haptic device are needed. However, existing haptic prototypes are associated with rigid, bulky, and heavy components, making effective communication with the skin problematic. This paper presents a teleoperated endoscopic surgical system with an integrated 3D force sensor and real‐time haptic feedback. A surgical robotic arm is remotely controlled by a soft haptic glove incorporated 3‐axis cutaneous device and a finger kinesthetic module. The 3D force sensor is constructed from hydraulic filament soft sensors that can induce pressure change under strain. To enable precise motion, the haptic glove is operated by a feedforward controller and a master‐slave architecture. Experiments with human subjects (n = 15) show that cutaneous and kinesthetic feedback significantly improves the user's performance (9.4 out of 10) compared to no haptic feedback (2.27 out of 10). Finally, subjects rank the new system as highly wearable, comfortable, and effective, which is expected to bridge a gap in the surgical field and support the future development of advanced teleoperated systems.

Synthetic design and analysis of the new feed cabin mechanism in Five-hundred-meter Aperture Spherical radio Telescope (FAST)

Due to the large weight of the feed cabin, the observation range of the Five-hundred-meter Aperture Spherical radio Telescope (FAST) is limited and unable to cover the galactic center. To solve this problem, a new feed cabin mechanism (NFCM) is designed to replace the heavy rigid components using the novel lightweight cable-driven structure, where the observation-related characteristics are investigated. After dimensional optimization, the observation range is analyzed using a two-level optimization that has explicit graphic-based solutions, the parameter sensitivity is studied by proposing the direct numerical method, and the anti-disturbance ability is discussed using the novel disturbance unit increment method. Numerical simulations indicate that the optimal designed NFCM can achieve required larger observation range with exceptional observation performance. Additionally, considering the two-level control mode of FAST, a novel controller is proposed for the NFCM by addressing dynamics in the non-inertial frame, and the control performance in time and frequency domain is validated using actual observation data, where the NFCM can effectively suppress residual errors from the outer six-cable-driven system in FAST and has satisfactory control robustness in resisting system disturbances.

Kirigami layer jamming

Variable stiffness materials bridge the desirable qualities of soft and rigid robotic components, forming the basis of new machines that contextually adapt their structural properties. Recent developments have led to the creation of jamming materials: Collections of media that undergo pressure-dependent kinematic and frictional interactions to radically, rapidly, and reversibly change in stiffness. Among the types of jamming, laminar jamming harnesses an ensemble of sheets for stiffness changes. Most implementations of laminar jamming employ unaltered, continuous sheets, though the vast design space of mechanical anisotropy programmed via structured cuts invites a new jamming paradigm: kirigami laminar jamming. Through analytical, experimental, and numerical studies, we show how intentional topological augmentation of laminar jamming sheets through shell, void, and cut geometric primitives can elicit bespoke mechanical responses. In particular, we optimize jamming specimens to enhance the jammed to unjammed flexural stiffness ratio across a range of deflections, which unlocks new move-and-hold capabilities. We also demonstrate pressure-induced shape morphing and both sharp-edged and doubly-curved surface matching with kirigami patterns. Results hold broad significance for robotics, morphing structures, and the systematic design of variable stiffness materials.

Semi-interpenetrating network anion exchange membranes based on flexible polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene and rigid Poly(vinylbenzyl chloride) for fuel cell applications

Balancing ion conductivity, mechanical strength, and alkali stability is a significant challenge in the application of anion exchange membranes (AEMs) in anion exchange membrane fuel cells (AEMFCs). In this study, rigid poly(4-vinylbiphenyl chloride) (PVB) and flexible polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (SEBS) are selected as the polymer backbones to create semi-interpenetrating network (SIPN) AEMs. To achieve high ionic conductivity, quaternary ammonium groups are grafted onto each PVB structural unit, and TMHDA reacts with CMSEBS to construct a cross-linking network while also generating quaternary ammonium groups. This approach, along with well-defined micro-morphology, result in SIPN-SEBS/PVB-10 exhibiting an impressive ionic conductivity of 105.7 mS cm−1 at 80 °C. The SIPN structure, formed by the linear quaternary ammonium PVB and cross-linked SEBS, enhances the compatibility between the rigid and flexible components, resulting in good tensile strength (>14.5 Mpa) and elongation at break (>31.8%) for SIPN-SEBS/PVB AEMs at 25 °C in the wet state. Furthermore, SIPN-SEBS/PVB AEMs exhibit excellent chemical stability, in addition to the restricted swelling behavior, which can be attributed to the stable PVB and SEBS main chains. After immersion in a 1 M NaOH solution at 80 °C for 30 days, the degradation of backbones and cations in all membranes is less than 10% and 20%, respectively. Moreover, the peak power density of SIPN-SEBS/PVB-10 in an H2/O2 single fuel cell reaches an impressive value of 379 mW cm−2. Based on these excellent properties, the developed SIPN AEMs hold great promise as candidates for AEMFCs.

Tensegristats: Lightweight Untethered Morphing Robots

Flexible and shape-shifting structures are common in nature. Creating shape-shifting machines using rigid components requires complex design work. Soft robotic attempts are closer to the muscular hydrostats they mimic but are slow and inefficient untethered and do not generally allow large-scale shape change between forms. Here we present the idea of “tensegristat” robots in which 1) we use tendons drawn by electric motors as active tensile elements, and fluid as a passive compressive element; 2) we rely primarily on buckling for motion and shape change; and (3) the total mass of fluid in the robot remains constant. This structure is analogous to that of muscular hydrostats and allows large-scale shape changes, separate control of stiffness and motion, and fast and efficient untethered operation. We demonstrate this idea with a morphing amphibious robot.

Bio-inspired “rigid and flexible” structure design for robust superhydrophobic composite and its application

The mechano-chemical-physical robustness is essential for the practical applications of a superhydrophobic coating. However, the superhydrophobic coatings obtained following general design principles hold inherent vulnerability. In this work, inspired by the pangolins’ combination of the rigid armour and the flexible flesh, we propose a new universal “rigid and flexible” design strategy for preparing a superhydrophobic coating with intrinsic mechano-chemical-physical robustness by introducing both rigid and flexible components. As a proof-of-concept, a robust superhydrophobic “rigid and flexible” coating is fabricated using rigid corundum particles and flexible rubber particles. In our design, the rigid component (i.e. corundum particles) provides the protection for the entire structure from mechanical wear, while the flexible component (i.e. rubber particles) endows the structure excellent deformability to eliminate stress under impact, thus having a synergistical advantage in adapting to various mechanical destructions. The as-obtained superhydrophobic “rigid and flexible” coating show superior mechano-chemical-physical robustness against various harsh conditions including 1200 cycles of 2 Kg (40 KPa) linear abrasion, tape-peeling, knife-scratching, water-jetting and chemical corrosion. In addition, the “rigid and flexible” superhydrophobic coating exhibits an excellent weathering resistance and anti-icing properties. Our “rigid and flexible” design strategy will provide a new insight for the development of robust superhydrophobic materials and broaden its application scenarios.

(Invited) smart Wearable Electronics for Chronic Disease Management

60% of Americans live with at least one chronic disease. These diseases and associated comorbidities are now the leading causes of death in the United States. Effective management of complex chronic diseases requires body-wide, long-term, accurate, and continuous monitoring of multiple physiological signals from wearable devices to precisely determine the pathological state. These wearable physiological signal monitoring can dramatically reduce the demand of physician visiting and increase patients’ engagement and treatment adherence rate. Although wearable bioelectronic devices have shown huge potential in chronic disease management, existing technology still mostly relies on rigid chip components, where the interface between chips and skin/tissue has been a bottleneck that limits the system performance (noise, robustness etc). To address these challenges, my research has been involved in the exploration of rational system design concepts, material and device fabrication innovation, and tailored algorithms to enable smart wearable electronics that targets next-generation chronic disease management.Here I would like to discuss two of my developed technology platforms to elaborate the concept of smart wearables. First, I will describe a body area sensor network technology platform. In the system design concept side, this technology utilizes a novel wireless hybridization strategy and an unconventional detuned RFID working regime that provide an ideal skin interface. In the material/device side, this system integrates several skin-conforming polymer-based soft devices (ring oscillators, RF diodes, antennas, transistors etc.) as an integrated soft multimode sensing sticker. (1,2) Next, I will describe a wireless closed-loop smart bandage that can accelerate and monitor the wound healing process. (3) Such smart bandage also integrates new design concepts (wireless, battery-free design that combines both sensing and stimulation), novel materials (low-impedance, high-toughness, and tunable adhesion hydrogel as skin interface) and closed-loop control algorithms. Overall, the developed technology platform could assess multiple health outcomes and treatment responses to various chronic diseases. Ultimately, this technology will help to reduce chronic disease burden, lower medical costs, and provide a better quality of life for patients.

Liquid‐Metal/Nd2Fe14B/Ecoflex Composite Soft Robots and Their Electric Signal Transmission using Non‐Contact Tentacles

AbstractSignal transmission between rigid robots is usually realized through rigid electronic components like coil or circuit board. However, these rigid electronic units are difficult to be used in fully flexible soft robots because of the mismatch of Young's modulus. Liquid metal (LM), as a flexible fluid with superior electric conductivity, can be served as the alternative material for rigid electronic units to realize signal transmission in fully flexible soft robots. Herein, a fully flexible soft robot is fabricated, which is mainly consists of two functional units: the soft tentacle integrated with liquid metal spiral wire and the body prepared by Nd2Fe14B magnetic powders/Ecoflex composites. The fully flexible soft robot can not only transmit electric signals based on electromagnetic induction but also be actuated by an external magnetic field to form diverse signal transmission pathways. Related mechanisms of transmitting electric signal and driving are studied by Maxwell numerical simulation. Driven by an external magnetic field, three soft robots are capable to constitute two different pathways to transmit electric signals to the oscilloscope. It is believed that the integration of LM into the magnetic composites provides an open perspective to realize the signal transmission in fully flexible soft robot and favors the development of multifunctional soft robot.

Dynamic Analysis and Numerical Simulation of Arresting Hook Engaging Cable in Carried-Based UAV Landing Process

Carrier-based unmanned aerial vehicles (UAVs) require precise evaluation methods for their landing and arresting safety due to their high autonomy and demanding reliability requirements. In this paper, an efficient and accurate simulation method is presented for studying the arresting hook engaging arresting cable process. The finite element method and multibody dynamics (FEM-MBD) approach is employed. By establishing a rigid–flexible coupling model encompassing the UAV and arresting gear system, the simulation model for the engagement process is obtained. The model incorporates multiple coordinate systems to effectively capture the relative motion between the rigid and flexible components. The model considers the material properties, arresting gear system characteristics, and UAV state during engagement. Verification is conducted by comparing simulation results with experimental data from a referenced arresting hook rebound. Finally, simulations are performed under different touchdown points and roll angles of the UAV to analyze the stress distribution of the hook, center of gravity variations, and the tire touch and rollover cable response. The proposed rigid–flexible coupling arresting dynamics model in this paper enables the effective analysis of the dynamic behavior during the arresting hook engaging arresting cable process.

Bionic threshing component optimized based on MBD-DEM coupling simulation significantly improves corn kernel harvesting rate

The most widely used rigid threshing component (RTC) currently has a constant problem with high kernel damage rates. Inspired by the seldom occurrence of kernel damage in manual threshing operations, this study designed a bionic threshing component (BTC) by using the human thumb as a bionic prototype. BTC can imitate the thumb's real-time profiling capability on the shape of the corn ears, thereby reproducing the thumb's “flexible profiling impact“ method of applying force, significantly different from the “rigid impact method” of RTC. Based on EDEM and RecurDyn software, the MBD-DEM coupling simulation model of the threshing operation was constructed. Through the coupling simulation experiments, the influence law of the BTC core design parameter k (bionic joint torque elasticity coefficient) on the kernel harvesting rate η, threshing rate and damage rate was revealed. Meanwhile, the optimum value of k (2.08 KN·mm/°) was derived by modelling the k-η regression. Bench comparison and simulation accuracy verification experiments showed that BTC operated with optimal k values can increase corn kernel harvesting rates by 0.87%–1.57%, compared to RTC. (BTC was able to achieve the highest kernel harvesting and threshing rates of 98.61% and 98.97%, respectively, with breakage rates as low as 0.16%). Meanwhile, the computational results of the MBD-DEM coupling simulation model established in this study were not significantly difference from the bench experiment (P > 0.05). To sum up, this study can provide a new mechanism design idea and parameter optimization method for the development of threshing components.

Effect of surfactants on the interfacial behaviors of diacylglycerol-based solid lipid nanoparticles and physical stability of W/O emulsion

The influence of surfactants (Span 80, Span 60, PGPR and sodium caseinate) on the stability of W/O emulsions stabilized by diacylglycerol (DAG)-based solid Lipid nanoparticles (SLN) was investigated. DAG-based SLN showed phase separation at high NaCl concentration and acidic pH although the SLN-stabilized W/O emulsion was minimally affected. Span 80 increased the hydrophobicity whereas Span 60 increased the hydrophilicity of SLN. With concentration close to CMC, both Span surfactants caused detachment of SLN from interface and reduced emulsion stability. Nonetheless, addition of a small amount (0.1 wt%) of Span surfactants increased the interfacial modulus. The co-adsorption of SLN and PGPR at the oil-water interface promoted the formation of denser network structure and higher interfacial elasticity, which enhanced the emulsion rigidity and freeze-thaw stability. Sodium caseinate (NaCAS) showed intense competition with particles for adsorption at the interface and caused emulsion destabilization. Consequently, the NaCl release rate was directly influenced by the emulsion stability and the interaction between surfactants with SLN. The results have important implications for applying DAG nanoparticles as stabilizers in W/O emulsions with tailoring interfacial rigidity and water-soluble component release behaviors.

A Tensegrity Joint for Low‐Inertia, Compact, and Compliant Soft Manipulators

Compact, low‐inertia, and soft compliant robotic joint mechanisms are in great demand for ensuring safe interactions in human–robot collaborative tasks. Tensegrity, of which the structural integrity is constrained by tension, does not involve static/sliding friction among the rigid components. However, this mechanical stability is very susceptible to actuation errors. It requires complex kinematics modeling and sophisticated control model with sensing feedback. Herein, a low‐inertia tensegrity joint that is covered/protected by a fiber Bragg grating (FBG)‐embedded silicone sheath is proposed, with the aim to reinforce the joint motion stability and enable self‐contained sensing feedback. A learning‐based closed‐loop controller is also designed and trained with the proper joint configurations selected by a two‐step sampling method. Both the kinematics and static equilibriums of such configurations can be well satisfied. The experiments demonstrate that the joint can follow paths accurately in 2D by compensating manipulation error shortly under the closed‐loop control. The joint stiffness can also be varied against the external/impulsive disturbances. It can be foreseen that this primitive robot joint component with 2 degrees of freedom (DoFs) can provide safe, compliant interaction with human, for which a simple test of maneuvering a portable ultrasound probe (≈210 g) for abdominal imaging is demonstrated.

Research Progress in Stretchable Circuits: Materials, Methods, and Applications

AbstractStretchable electronic devices, with their excellent properties such as stretchability and conformal contact with complex surfaces, are widely used in health monitoring and human‐computer interactions. For stable operation of these devices, stretchable circuits are crucial, enabling integration of sensors, data collection, and transmission while under strain. To achieve stretchable system integration, addressing key issues such as elastic substrates, sensor devices, rigid components, stretchable electrodes, and packaging layers is necessary. The stretchable electrodes, which connect various functional devices, are crucial for achieving stretchability and are the main focus of this review. Firstly, this work explores the enhancement of electrode design to maintain good electrical conductivity even under stretching conditions, through studying stretchable conductive materials and the structural design of conventional materials. This work then presents studies on substrate interfaces and the design of elastic substrates, such as rigid islands, to enhance the stability of stretchable circuits during use. Finally, the article discusses the applications of stretchable circuits, the challenges they face, and provides new research directions and ways to develop stretchable circuits.

Liquid Metal Fibers with a Knitted Structure for Wearable Electronics.

Flexible conductive fibers have shown tremendous potential in diverse fields, including health monitoring, intelligent robotics, and human-machine interaction. Nevertheless, most conventional flexible conductive materials face challenges in meeting the high conductivity and stretchability requirements. In this study, we introduce a knitted structure of liquid metal conductive fibers. The knitted structure of liquid metal fiber significantly reduces the resistance variation under tension and exhibits favorable durability, as evidenced by the results of cyclic tensile testing, which indicate that their resistance only undergoes a slight increase (<3%) after 1300 cycles. Furthermore, we demonstrate the integration of these liquid metal fibers with various rigid electronic components, thereby facilitating the production of pliable LED arrays and intelligent garments for electrocardiogram (ECG) monitoring. The LED array underwent a 30 min machine wash, during which it consistently retained its normal functionality. These findings evince the devices' robust stable circuit functionality and water resistance that remain unaffected by daily human activities. The liquid metal knitted fibers offer great promise for advancing the field of flexible conductive fibers. Their exceptional electrical and mechanical properties, combined with compatibility with existing electronic components, open new possibilities for applications in the physiological signal detection of carriers, human-machine interaction, and large-area electronic skin.

A soft, self-sensing tensile valve for perceptive soft robots

Soft inflatable robots are a promising paradigm for applications that benefit from their inherent safety and adaptability. However, for perception, complex connections of rigid electronics both in hardware and software remain the mainstay. Although recent efforts have created soft analogs of individual rigid components, the integration of sensing and control systems is challenging to achieve without compromising the complete softness, form factor, or capabilities. Here, we report a soft self-sensing tensile valve that integrates the functional capabilities of sensors and control valves to directly transform applied tensile strain into distinctive steady-state output pressure states using only a single, constant pressure source. By harnessing a unique mechanism, “helical pinching”, we derive physical sharing of both sensing and control valve structures, achieving all-in-one integration in a compact form factor. We demonstrate programmability and applicability of our platform, illustrating a pathway towards fully soft, electronics-free, untethered, and autonomous robotic systems.

Non-linear Wire Rope Isolator Model to Enhance Transportation Simulation of Fragile Equipment

IntroductionWire rope isolators are often used as means of vibration isolation for the transportation of fragile machine equipment. When deployed as suspension systems in a transportation scenario, a simple spring–damper model is often used to predict the dynamic loads that act on the structure being transported. However, this simple model has proved to be too simplistic to be used in the development of an accurate numerical model that can predict the vibration levels experienced by the inner components of fragile equipment during its transportation. This paper describes the experimental tests conducted on a wire rope isolator used for the transportation of the prototype SSR1 cryomodule.Materials and methodsA hysteretic Bouc–Wen model has been used to analytically describe the force–deformation relationship of the wire rope isolators. The developed model of the isolator has been implemented in a larger model to simulate the actual transportation of the prototype SSR1 cryomodule, a section of the new PIP-II linear accelerator under construction at Fermilab. A series of multibody dynamic simulations with rigid and flexible components was used to numerically determine the acceleration of some critical components.Results and conclusionsAn actual experimental transportation was simulated using two numerical models: the developed Bouc–Wen model and a conventional spring–damper model. It is shown how the Bouc–Wen formulation of the isolator characteristics drastically improves the correspondence between experimental and simulated results if compared to a spring–damper model, especially in the range of 0–30 Hz which is the most critical for transportation problems.

Preparation and characterization of low CTE thermoplastic copolyimide resins based on the structural design of block sequence

In order to solve the challenge of balancing the thermoplastic processing properties and thermal dimensional stability of polyimide (PI) resin, in this research, 3,3′,4,4′-biphenyl tetracarboxylic diandhydride (BPDA) and 2,2′-bis(trifluoromethyl)benzidine (TFMB) were used as rigid components, 4,4′-oxydiphthalic anhydride (ODPA) and 4,4′-diaminodiphenyl sulfone (DDS) as flexible components. A series of random copolyimide resins was prepared by adjusting the molar ratio of rigid and flexible monomers. Determining the molar ratio which could balance the thermoplastic processing properties and thermal dimensional stability, block copolyimide resins with different rigid and flexible block lengths were then prepared in this ratio. The research showed that the molar ratio of monomers and the sequence structure of molecular chains had a strong influence on the performance of PI resins. When the content or block length of rigid component increased, the coefficient of thermal expansion (CTE) decreased but the glass transition temperatures (Tg) and melt viscosity increased. The PI-B343 resin had a CTE value of 40.63 ppm/K and the lowest melt viscosity reached 675 Pa·s, achieved the simultaneous regulation of the thermoplastic processing properties and thermal dimensional stability for PI resin.

One-pot ternary sequential reactions for photopatterned gradient multimaterials

One-pot ternary sequential reactions for photopatterned gradient multimaterials

GPART: Partitioning Maximal Redundant Rigid and Maximal Global Rigid Components in Generic Distance Graphs

Partitioning the Maximal Redundant Rigid Components (MRRC) and Maximal Global Rigid Components (MGRC) in generic 2D graphs are critical problem for network structure analysis, network localizability detection, and localization algorithm design. This article presents efficient algorithms to partition MRRCs and MGRCs and develops an open-sourced toolbox, GPART, for these algorithms to be conveniently used by the society. We firstly propose conditions and an efficient algorithm to merge the over-constrained regions to form the maximal redundant rigid components (MRRC). The detected MRRCs are proved to be maximal and all the MRRCs are guaranteed to be detected. The time to merge the over-constrained regions is linear to the number of nodes in the over-constrained components. To detect MGRCs, the critical problem is to decompose 3-connected components in each MRRC. We exploit SPQR-tree based method and design a local optimization algorithm, called MGRC_acce to prune the unnecessary decomposition operations so that the SPQR-tree functions can be called much less number of times. We prove the MGRCs can be detected inside MRRCs using at most O(mn ) time. Then a GPART toolbox is developed and extensively tested in graphs of different densities. We show the proposed MRRC and MGRC detection algorithms are valid and MGRC_acce greatly outperforms the direct SPQR-tree based decomposition algorithm. GPART is outsourced at https://github.com/inlab-group/gpart .