Analysis of the adhesion mechanism of functionalized carbon nanotubes by molecular dynamics simulation.

Although a lot of research has been carried out on the adhesion mechanism of gecko bristles, the research on materials inspired by gecko bristles is still limited to the design of geometric structure and the optimization of preparation process, and the adhesion mechanism of materials is still unclear. In this paper, the molecular structure of the end of the bristle-like material is focused on, and the interaction between functional group modified carbon nanotubes and the interface is analyzed by molecular dynamics simulation. Thus, the influence of different polar functional groups on the interfacial force between carbon nanotubes and silica is revealed, and the adhesion enhancement mechanism of polar groups on the interface between carbon nanotubes and silica is further verified.

Interleg coordination in free-walking bug Erthesina fullo (Hemiptera: Pentatomidae).

Insects can adapt their walking patterns to complex and varied environments and retain the ability to walk even after significant changes in their physical attributes, such as amputation. Although the interleg coordination of intact insects has been widely described in previous studies, the adaptive walking patterns in free-walking insects with amputation of 1 or more legs are still unclear. The pentatomid bug Erthesina fullo exhibits a tripod gait, when walking freely on horizontal substrates, like many other insects. In this study, amputations were performed on this species to investigate changes in interleg coordination. The walking parameters were analyzed, such as the locations of touchdown and liftoff, cycle period, walking speed, and head displacement of intact and amputated insects. The results show that E. fullo displays adaptive interleg coordination in response to amputations. With 1 amputated leg, bugs changed to a 3-unit gait, whereas with 2 amputated legs they employed a wave gait. These data are helpful in exploring the motion mode control in walking insects and provide the theoretical basis for the gait control strategy of robots, when leg failure occurs.

Wall-climbing performance of gecko-inspired robot with soft feet and digits enhanced by gravity compensation.

Gravitational forces can induce deviations in body posture from desired configurations in multi-legged arboreal robot locomotion with low leg stiffness, affecting the contact angle between the swing leg's end-effector and the climbing surface during the gait cycle. The relationship between desired and actual foot positions is investigated here in a leg-stiffness-enhanced model under external forces, focusing on the challenge of unreliable end-effector attachment on climbing surfaces in such robots. Inspired by the difference in ceiling attachment postures of dead and living geckos, feedforward compensation of the stance phase legs is the key to solving this problem. A feedforward gravity compensation (FGC) strategy, complemented by leg coordination, is proposed to correct gravity-influenced body posture and improve adhesion stability by reducing body inclination. The efficacy of this strategy is validated using a quadrupedal climbing robot, EF-I, as the experimental platform. Experimental validation on an inverted surface (ceiling walking) highlights the benefits of the FGC strategy, demonstrating its role in enhancing stability and ensuring reliable end-effector attachment without external assistance. In the experiment, robots without FGC only completed 3 out of 10 trials, while robots with FGC achieved a 100% success rate in the same trials. The speed was substantially greater with FGC, achieving 9.2 mm s-1in the trot gait. This underscores the proposed potential of the FGC strategy in overcoming the challenges associated with inconsistent end-effector attachment in robots with low leg stiffness, thereby facilitating stable locomotion even at an inverted body attitude.

Tree frogs (Polypedates dennysi) landing on horizontal perches: the effects of perch diameter.

Secure landing is indispensable for both leaping animals and robotics. Tree frogs, renowned for their adhesive capabilities, can effectively jump across intricate 3D terrain and land safely. Compared with jumping, the mechanisms underlying their landing technique, particularly in arboreal environments, have remained largely unknown. In this study, we focused on the landing patterns of the tree frog Polypedates dennysi on horizontally placed perches, explicitly emphasizing the influence of perch diameters. Tree frogs demonstrated diverse landing postures, including the utilization of: (1) single front foot, (2) double front feet, (3) anterior bellies, (4) middle bellies, (5) posterior bellies, (6) single hind foot, or (5) double hind feet. Generally, tree frogs favoured bellies on slimmer targets but double front feet on large perches. Analysis of limb-trunk relationships revealed their adaptability to modify postures, including body positions and limb orientations, for successful landing. The variations in the initial landing postures affected the subsequent landing procedures and, consequently, the dynamics. As the initial contact position switched from front foot back to the hind foot, the stabilization time decreased at first, reaching a minimum in middle belly landings, and then increased again. The maximum vertical forces showed an inverse trend, whereas the maximum fore-aft forces continuously increased as the initial contact position switched. As the perch diameter increased, the time expended dropped, whereas the maximum impact force increased. These findings not only add to our understanding of frog landings but also highlight the necessity of considering perch diameters and landing styles when studying the biomechanics of arboreal locomotion.

Facial Expression Realization of Humanoid Robot Head and Strain-Based Anthropomorphic Evaluation of Robot Facial Expressions.

The facial expressions of humanoid robots play a crucial role in human-computer information interactions. However, there is a lack of quantitative evaluation methods for the anthropomorphism of robot facial expressions. In this study, we designed and manufactured a humanoid robot head that was capable of successfully realizing six basic facial expressions. The driving force behind the mechanism was efficiently transmitted to the silicone skin through a rigid linkage drive and snap button connection, which improves both the driving efficiency and the lifespan of the silicone skin. We used human facial expressions as a basis for simulating and acquiring the movement parameters. Subsequently, we designed a control system for the humanoid robot head in order to achieve these facial expressions. Moreover, we used a flexible vertical graphene sensor to measure strain on both the human face and the silicone skin of the humanoid robot head. We then proposed a method to evaluate the anthropomorphic degree of the robot's facial expressions by using the difference rate of strain. The feasibility of this method was confirmed through experiments in facial expression recognition. The evaluation results indicated a high degree of anthropomorphism for the six basic facial expressions which were achieved by the humanoid robot head. Moreover, this study also investigates factors affecting the reproduction of expressions. Finally, the impulse was calculated based on the strain curves of the energy consumption of the humanoid robot head to complete different facial expressions. This offers a reference for fellow researchers when designing humanoid robot heads, based on energy consumption ratios. To conclude, this paper offers data references for optimizing the mechanisms and selecting the drive components of the humanoid robot head. This was realized by considering the anthropomorphic degree and energy consumption of each part. Additionally, a new method for evaluating robot facial expressions is proposed.

Device for Measuring Contact Reaction Forces during Animal Adhesion Landing/Takeoff from Leaf-like Compliant Substrates.

A precise measurement of animal behavior and reaction forces from their surroundings can help elucidate the fundamental principle of animal locomotion, such as landing and takeoff. Compared with stiff substrates, compliant substrates, like leaves, readily yield to loads, presenting grand challenges in measuring the reaction forces on the substrates involving compliance. To gain insight into the kinematic mechanisms and structural-functional evolution associated with arboreal animal locomotion, this study introduces an innovative device that facilitates the quantification of the reaction forces on compliant substrates, like leaves. By utilizing the stiffness-damping characteristics of servomotors and the adjustable length of a cantilever structure, the substrate compliance of the device can be accurately controlled. The substrate was further connected to a force sensor and an acceleration sensor. With the cooperation of these sensors, the measured interaction force between the animal and the compliant substrate prevented the effects of inertial force coupling. The device was calibrated under preset conditions, and its force measurement accuracy was validated, with the error between the actual measured and theoretical values being no greater than 10%. Force curves were measured, and frictional adhesion coefficients were calculated from comparative experiments on the landing/takeoff of adherent animals (tree frogs and geckos) on this device. Analysis revealed that the adhesion force limits were significantly lower than previously reported values (0.2~0.4 times those estimated in previous research). This apparatus provides mechanical evidence for elucidating structural-functional relationships exhibited by animals during locomotion and can serve as an experimental platform for optimizing the locomotion of bioinspired robots on compliant substrates.

Multiple forces facilitate the aquatic acrobatics of grasshopper and bioinspired robot.

Aquatic locomotion is challenging for land-dwelling creatures because of the high degree of fluidity with which the water yields to loads. We surprisingly found that the Chinese rice grasshopper Oxya chinensis, known for its terrestrial acrobatics, could swiftly launch itself off the water's surface in around 25 ms and seamlessly transition into flight. Biological observations showed that jumping grasshoppers use their front and middle legs to tilt up bodies first and then lift off by propelling the water toward the lower back with hind legs at angular speeds of up to 18°/ms, whereas the swimming grasshoppers swing their front and middle legs in nearly horizontal planes and move hind legs less violently (~8°/ms). Force measurement and model analysis indicated that the weight support could be achieved by hydrostatics which are proportionate to the mass of the grasshoppers, while the propulsions for motion are derived from the controlled limb-water interactions (i.e., the hydrodynamics). After learning the structural and behavioral strategies of the grasshoppers, a robot was created and was capable of swimming and jumping on the water surface like the insects, further demonstrating the effectiveness of decoupling the challenges of aquatic locomotion by the combined use of the static and dynamic hydro forces. This work not only uncovered the combined mechanisms responsible for facilitating aquatic acrobatics in this species but also laid a foundation for developing bioinspired robots that can locomote across multiple media.

High-Frequency Local Field Potential Oscillations for Pigeons in Effective Turning.

Flexible turning behavior endows Homing Pigeons (Columba livia domestica) with high adaptability and intelligence in long-distance flight, foraging, hazard avoidance, and social interactions. The present study recorded the activity pattern of their local field potential (LFP) oscillations and explored the relationship between different bands of oscillations and turning behaviors in the formatio reticularis medialis mesencephali (FRM). The results showed that the C (13-60 Hz) and D (61-130 Hz) bands derived from FRM nuclei oscillated significantly in active turning, while the D and E (131-200 Hz) bands oscillated significantly in passive turning. Additionally, compared with lower-frequency stimulation (40 Hz and 60 Hz), 80 Hz stimulation can effectively activate the turning function of FRM nuclei. Electrical stimulation elicited stronger oscillations of neural activity, which strengthened the pigeons' turning locomotion willingness, showing an enhanced neural activation effect. These findings suggest that different band oscillations play different roles in the turning behavior; in particular, higher-frequency oscillations (D and E bands) enhance the turning behavior. These findings will help us decode the complex relationship between bird brains and behaviors and are expected to facilitate the development of neuromodulation techniques for animal robotics.

Preload-Induced Switchable Adhesion.

Animals with robust attachment abilities commonly exhibit stable attachment and convenient detachment. However, achieving an efficient attachment-detachment function in bioinspired adhesives is challenging owing to the complexity and delay of actuators. In this study, a class of multilayer adhesives (MAs) comprising backing, middle, and bottom layers is proposed to realize rapid switching by only adjusting the preload. At low preload, the MAs maintain intimate contact with the substrate. By contrast, a sufficiently large preload results in significant deformation of the middle layer, causing underside buckling and reducing adhesion. By optimizing the structural parameters of the MAs, a high switching ratio (up to 136×) can be achieved under different preloads. Furthermore, the design of the MAs incorporates a film-terminated structure, which prevents the embedding of dirt particles, simplifies cleaning, and maintains the separation and uprightness of the microstructures. Consequently, the MAs demonstrate practical potential for simple and efficient transportation applications, as they achieve switchable adhesion through their structure, exhibiting a high switching ratio and fast switching.

Rate-dependent adhesion together with limb collaborations facilitate grasshoppers reliable attachment under highly dynamic conditions.

Dynamic attachment is indispensable for animals to cope with unexpected disturbances. Minor attention has been paid to the dynamic performance of insects' adhesive pads. Through experiments pulling whole grasshoppers off a glass rod at varying speeds, surprising findings emerged. The feet did not always maintain contact but released and then reconnected to the substrate rapidly during leg extension, potentially reducing the shock damage to pads. As the pulling speeds increased from 1 to 400 mm/s, the maximum forces of single front tarsus insects and entire tarsi insects were nearly proportional to the 1/3 power of pulling speeds by 0.11 and 0.29 times, respectively. The force of some individuals could be even 800 times greater than their weight, which is unexpectedly high for smooth insect pads. This work not only helps us to understand the attachment intelligence of animals but is also informative for artificial attachment in extreme situations.

Hybrid learning mechanisms under a neural control network for various walking speed generation of a quadruped robot.

Legged robots that can instantly change motor patterns at different walking speeds are useful and can accomplish various tasks efficiently. However, state-of-the-art control methods either are difficult to develop or require long training times. In this study, we present a comprehensible neural control framework to integrate probability-based black-box optimization (PIBB) and supervised learning for robot motor pattern generation at various walking speeds. The control framework structure is based on a combination of a central pattern generator (CPG), a radial basis function (RBF) -based premotor network and a hypernetwork, resulting in a so-called neural CPG-RBF-hyper control network. First, the CPG-driven RBF network, acting as a complex motor pattern generator, was trained to learn policies (multiple motor patterns) for different speeds using PIBB. We also introduce an incremental learning strategy to avoid local optima. Second, the hypernetwork, which acts as a task/behavior to control parameter mapping, was trained using supervised learning. It creates a mapping between the internal CPG frequency (reflecting the walking speed) and motor behavior. This map represents the prior knowledge of the robot, which contains the optimal motor joint patterns at various CPG frequencies. Finally, when a user-defined robot walking frequency or speed is provided, the hypernetwork generates the corresponding policy for the CPG-RBF network. The result is a versatile locomotion controller which enables a quadruped robot to perform stable and robust walking at different speeds without sensory feedback. The policy of the controller was trained in the simulation (less than 1 h) and capable of transferring to a real robot. The generalization ability of the controller was demonstrated by testing the CPG frequencies that were not encountered during training.

Bioinspired Rigid-Flexible Coupled Adaptive Compliant Motion Control of Robot Gecko for Space Stations.

This paper presents a study on bioinspired rigid-flexible coupling adaptive compliant motion control of a robot gecko with hybrid actuation for space stations. The biomimetic robot gecko is made of a rigid trunk, four motor-driven active legs with dual-degree-of-freedom shoulder joints, and four pneumatic flexible pleated active attachment-detachment feet. The adaptive impedance model consists of four input parameters: the inertia coefficient, stiffness coefficient, damping coefficient, and segmented expected plantar force. The robot gecko is equipped with four force sensors mounted on its four feet, from which the normal force of each foot can be sensed in real-time. Based on the sensor signal, the variable stiffness characteristics of the feet in different states are analyzed. Furthermore, an adaptive active compliance control strategy with whole-body rigidity-flexibility-force feedback coupling is proposed for the robot gecko. Four sets of experiments are presented, including open-loop motion control, static anti-interference experiment, segmented variable stiffness experiment, and adaptative compliant motion control, both in a microgravity environment. The experiment results indicated that the presented control strategy worked well and the robot gecko demonstrates the capability of stable attachment and compliant detachment, thereby normal impact and microgravity instability are avoided. It achieves position tracking and force tracking while exhibiting strong robustness for external disturbances.

A solar/radiative cooling dual-regulation smart window based on shape-morphing kirigami structures.

The energy efficiency of buildings has become a critical issue due to their substantial contribution to global energy consumption. Windows, in particular, are often the least efficient component of the building envelope, and conventional smart windows focus solely on regulating solar transmittance while overlooking radiative cooling. Although several recent designs achieved dual-control of solar and radiative cooling, these windows still face limitations in terms of durability, limited modulation ability and energy-saving performance. To address these challenges, we propose a novel dual-control smart window design consisting of a reconfigurable kirigami structure and polydimethylsiloxane-laminated thermochromic hydrogel coated with silver nanowires. In summer, the thermochromic hydrogel turns translucent to suppress the solar heat gain, while the high emissivity kirigami structure covers the exterior surface of the window, promoting radiative cooling. In winter, the hydrogel becomes transparent to allow for solar transmission. Additionally, the kirigami structure undergoes an out-of-plane structural change, opening towards the outside environment to expose the underlying low-emissivity silver nanowires and suppress heat radiation. Our design achieves a promising solar transmittance modulation ability of ∼24% and a good long-wave infrared emissivity regulation ability of 0.5. Furthermore, it exhibits significantly improved durability, which is nine times longer than the lifespan of conventional smart hydrogels. Our novel approach offers a promising solution for constructing energy-efficient and durable smart windows and outperforms existing state-of-the-art solar/radiative cooling dual-regulation smart windows in the literature.

Grade-control outdoor turning flight of robo-pigeon with quantitative stimulus parameters.

Introduction: The robo-pigeon using homing pigeons as a motion carrier has great potential in search and rescue operations due to its superior weight-bearing capacity and sustained flight capabilities. However, before deploying such robo-pigeons, it is necessary to establish a safe, stable, and long-term effective neuro-electrical stimulation interface and quantify the motion responses to various stimuli. Methods: In this study, we investigated the effects of stimulation variables such as stimulation frequency (SF), stimulation duration (SD), and inter-stimulus interval (ISI) on the turning flight control of robo-pigeons outdoors, and evaluated the efficiency and accuracy of turning flight behavior accordingly. Results: The results showed that the turning angle can be significantly controlled by appropriately increasing SF and SD. Increasing ISI can significantly control the turning radius of robotic pigeons. The success rate of turning flight control decreases significantly when the stimulation parameters exceed SF > 100 Hz or SD > 5 s. Thus, the robo-pigeon's turning angle from 15 to 55° and turning radius from 25 to 135 m could be controlled in a graded manner by selecting varying stimulus variables. Discussion: These findings can be used to optimize the stimulation strategy of robo-pigeons to achieve precise control of their turning flight behavior outdoors. The results also suggest that robo-pigeons have potential for use in search and rescue operations where precise control of flight behavior is required.

Robust and reusable self-organized locomotion of legged robots under adaptive physical and neural communications.

Introduction: Animals such as cattle can achieve versatile and elegant behaviors through automatic sensorimotor coordination. Their self-organized movements convey an impression of adaptability, robustness, and motor memory. However, the adaptive mechanisms underlying such natural abilities of these animals have not been completely realized in artificial legged systems. Methods: Hence, we propose adaptive neural control that can mimic these abilities through adaptive physical and neural communications. The control algorithm consists of distributed local central pattern generator (CPG)-based neural circuits for generating basic leg movements, an adaptive sensory feedback mechanism for generating self-organized phase relationships among the local CPG circuits, and an adaptive neural coupling mechanism for transferring and storing the formed phase relationships (a gait pattern) into the neural structure. The adaptive neural control was evaluated in experiments using a quadruped robot. Results: The adaptive neural control enabled the robot to 1) rapidly and automatically form its gait (i.e., self-organized locomotion) within a few seconds, 2) memorize the gait for later recovery, and 3) robustly walk, even when a sensory feedback malfunction occurs. It also enabled maneuverability, with the robot being able to change its walking speed and direction. Moreover, implementing adaptive physical and neural communications provided an opportunity for understanding the mechanism of motor memory formation. Discussion: Overall, this study demonstrates that the integration of the two forms of communications through adaptive neural control is a powerful way to achieve robust and reusable self-organized locomotion in legged robots.

Multi-Phase Fusion for Pedestrian Localization Using Mass-Market GNSS and MEMS Sensors.

Precise pedestrian positioning based on smartphone-grade sensors has been a research hotspot for several years. Due to the poor performance of the mass-market Micro-Electro-Mechanical Systems (MEMS) Magnetic, Angular Rate, and Gravity (MARG) sensors, the standalone pedestrian dead reckoning (PDR) module cannot avoid long-time heading drift, which leads to the failure of the entire positioning system. In outdoor scenes, the Global Navigation Satellite System (GNSS) is one of the most popular positioning systems, and smartphone users can use it to acquire absolute coordinates. However, the smartphone's ultra-low-cost GNSS module is limited by some components such as the antenna, and so it is susceptible to serious interference from the multipath effect, which is a main error source of smartphone-based GNSS positioning. In this paper, we propose a multi-phase GNSS/PDR fusion framework to overcome the limitations of standalone modules. The first phase is to build a pseudorange double-difference based on smartphone and reference stations, the second phase proposes a novel multipath mitigation method based on multipath partial parameters estimation (MPPE) and a Double-Difference Code-Minus-Carrier (DDCMC) filter, and the third phase is to propose the joint stride lengths and heading estimations of the two standalone modules, to reduce the long-time drift and noise. The experimental results demonstrate that the proposed multipath error estimation can effectively suppress the double-difference multipath error exceeding 4 m, and compared to other methods, our fusion method achieves a minimum error RMSE of 1.63 m in positioning accuracy, and a minimum error RMSE of 4.71 m in long-time robustness for 20 min of continuous walking.

A Neural Coordination Strategy for Attachment and Detachment of a Climbing Robot Inspired by Gecko Locomotion.

Climbing behavior is a superior motion skill that animals have evolved to obtain a more beneficial position in complex natural environments. Compared to animals, current bionic climbing robots are less agile, stable, and energy-efficient. Further, they locomote at a low speed and have poor adaptation to the substrate. One of the key elements that can improve their locomotion efficiency is the active and flexible feet or toes observed in climbing animals. Inspired by the active attachment-detachment behavior of geckos, a hybrid pneumatic-electric-driven climbing robot with active attachment-detachment bionic flexible feet (toes) was developed. Although the introduction of bionic flexible toes can effectively improve the robot's adaptability to the environment, it also poses control challenges, specifically, the realization of attachment-detachment behavior by the mechanics of the feet, the realization of hybrid drive control with different response characteristics, and the interlimb collaboration and limb-foot coordination with a hysteresis effect. Through the analysis of geckos' limbs and foot kinematic behavior during climbing, rhythmic attachment-detachment strategies and coordination behavior between toes and limbs at different inclines were identified. To enable the robot to achieve similar foot attachment-detachment behavior for climbing ability enhancement, we propose a modular neural control framework comprising a central pattern generator module, a post-processing central pattern generation module, a hysteresis delay line module, and an actuator signal conditioning module. Among them, the hysteresis adaptation module helps the bionic flexible toes to achieve variable phase relationships with the motorized joint, thus enabling proper limb-to-foot coordination and interlimb collaboration. The experiments demonstrated that the robot with neural control achieved proper coordination, resulting in a foot with a 285% larger adhesion area than that of a conventional algorithm. In addition, in the plane/arc climbing scenario, the robot with coordination behavior increased by as much as 150%, compared to the incoordinated one owing to its higher adhesion reliability.

Reversible Adhesive Bio-Toe with Hierarchical Structure Inspired by Gecko.

The agile locomotion of adhesive animals is mainly attributed to their sophisticated hierarchical feet and reversible adhesion motility. Their structure-function relationship is an urgent issue to be solved to understand biologic adhesive systems and the design of bionic applications. In this study, the reversible adhesion/release behavior and structural properties of gecko toes were investigated, and a hierarchical adhesive bionic toe (bio-toe) consisting of an upper elastic actuator as the supporting/driving layer and lower bionic lamellae (bio-lamellae) as the adhesive layer was designed, which can adhere to and release from targets reversibly when driven by bi-directional pressure. A mathematical model of the nonlinear deformation and a finite element model of the adhesive contact of the bio-toe were developed. Meanwhile, combined with experimental tests, the effects of the structure and actuation on the adhesive behavior and mechanical properties of the bio-toe were investigated. The research found that (1) the bending curvature of the bio-toe, which is approximately linear with pressure, enables the bio-toe to adapt to a wide range of objects controllably; (2) the tabular bio-lamella could achieve a contact rate of 60% with a low squeeze contact of less than 0.5 N despite a ±10° tilt in contact posture; (3) the upward bending of the bio-toe under negative pressure provided sufficient rebounding force for a 100% success rate of release; (4) the ratio of shear adhesion force to preload of the bio-toe with tabular bio-lamellae reaches approximately 12, which is higher than that of most existing adhesion units and frictional gripping units. The bio-toe shows good adaptability, load capacity, and reversibility of adhesion when applied as the basic adhesive unit in a robot gripper and wall-climbing robot. Finally, the proposed reversible adhesive bio-toe with a hierarchical structure has great potential for application in space, defense, industry, and daily life.

Contact Electrification of Biological and Bio-Inspired Adhesive Materials on SiO2 Surfaces: Perspectives from DFT Calculations.

In this study, we investigate the contact electrification properties of glycine, cysteine, and dimethyl siloxane on silicon dioxide (SiO2) surfaces using density functional theory calculations. Molecule contacting through the sulfhydryl group has stronger adhesion to the SiO2-O and SiO2-OH surfaces. The SiOH/SiO2-Si system has the largest adhesion energy in all molecule/SiO2-Si contact systems and charge transfers from the molecule to the SiO2-O and SiO2-Si surfaces. The molecule/SiO2-OH systems have a reverse charge transfer direction. Molecules with their sulfhydryl and hydroxyl groups facing the SiO2-O and SiO2-OH surfaces have more transferred charges. The NH2/SiO2-Si system has a larger transferred charge than other molecule/SiO2-Si systems. The direction of charge transfer is determined by the Bader charge of the isolated surface atoms. The respective energy difference in the lowest unoccupied occupied molecular orbitals between contacting atoms influences the charge transfer. The respective energy difference in the highest occupied molecular orbitals reflects the electron attraction and affects charge transfer. Finally, the quantitative relationship between the transferred charge and energy gaps is established to evaluate the charge transfer. The findings propose a new perspective and in-depth understanding of contact electrification and shed light on the bio-inspired adhesive materials design and fabrication for engineering applications.

Progresses of animal robots: A historical review and perspectiveness.

Animal robots have remarkable advantages over traditional mechatronic ones in terms of energy supply, self-orientation, and natural concealment and can provide remarkable theoretical and practical values for scientific investigation, community service, military detection and other fields. Given these features, animal robots have become high-profile research objects and have recently attracted extensive attention. Herein, we have defined animal robots, reviewed the main types of animal robots, and discussed the potential developing directions. We have also detailed the mechanisms underlying the regulation of animal robots and introduced key methods for manipulating them. We have further proposed several application prospects for different types of animal robots. Finally, we have presented research directions for their further improvement.