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.

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.

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.

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.

Peking geckos (Gekko swinhonis) traversing upward steps: the effect of step height on the transition from horizontal to vertical locomotion.

The ability to transition between surfaces (e.g., from the ground to vertical barriers, such as walls, tree trunks, or rock surfaces) is important for the Peking gecko's (Gekko swinhonis Günther 1864) survival. However, quantitative research on gecko's kinematic performance and the effect of obstacle height during transitional locomotion remains scarce. In this study, the transitional locomotion of geckos facing different obstacle heights was assessed. Remarkably, geckos demonstrated a bimodal locomotion ability, as they could climb and jump. Climbing was more common on smaller obstacles and took longer than jumping. The jumping type depended on the obstacle height: when geckos could jump onto the obstacle, the vertical velocity increased with obstacle height; however, geckos jumped from a closer position when the obstacle height exceeded this range and would get attached to the vertical surface. A stability analysis of vertical surface landing using a collision model revealed that geckos can reduce their restraint impulse by increasing the landing angle through limb extension close to the body, consequently dissipating collision energy and reducing their horizontal and vertical velocities. The findings of this study reveal the adaptations evolved by geckos to move in their environments and may have applicability in the robotics field.

Payload Identification and Gravity/Inertial Compensation for Six-Dimensional Force/Torque Sensor with a Fast and Robust Trajectory Design Approach.

In the robot contact operation, the robot relies on the multi-dimensional force/torque sensor installed at the end to sense the external contact force. When the effective load and speed of the robot are large, the gravity/inertial force generated by it will have a non-negligible impact on the output of the force sensor, which will seriously affect the accuracy and effect of the force control. The existing identification algorithm time is often longer, which also affects the efficiency of force control operations. In this paper, a self-developed multi-dimensional force sensor with integrated gravity/inertial force sensing function is used to directly measure the resultant force. Further, a method for the rapid identification of payload based on excitation trajectory is proposed. Firstly, both a gravity compensation algorithm and an inertial force compensation algorithm are introduced. Secondly, the optimal spatial recognition pose based on the excitation trajectory was designed, and the excitation trajectory of each joint is represented by a finite Fourier series. The least square method is used to calculate the identification parameters of the load, the gravity, and inertial force. Finally, the experiment was verified on the robot. The experimental results show that the algorithm can quickly identify the payload, and it is faster and more accurate than other algorithms.

Size, shape and orientation of macro-sized substrate protrusions affect the toe and foot adhesion of geckos.

Geckos are excellent climbers using compliant, hierarchically arranged adhesive toes to negotiate diverse terrains varying in roughness at multiple size scales. Here, we complement advancements at smaller size scales with measurements at the macro scale. We studied the attachment of a single toe and whole foot of geckos on macroscale rough substrates by pulling them along, across and off smooth rods and spheres mimicking different geometric protrusions of substrates. When we pulled a single toe along rods, the force increased with the rod diameter, whereas the attachment force of dragging toes across rods increased from about 60% on small diameter rods relative to a flat surface to ∼100% on larger diameter rods, but showed no further increase as rod diameter doubled. Toe force also increased as the pulling changed from along-rod loading to across-rod loading. When toes were pulled off spheres, the force increased with increasing sphere diameter as observed for along-rod pulling. For feet with separated toes, attachment on spheres was stronger than that on rods with the same diameter. Attachment force of a foot decreased as rod and sphere size increased but remained sufficient to support the body weight of geckos. These results provide a bridge to the macroscale roughness seen in nature by revealing the importance of the dimension, shape and orientation of macroscale substrate features for compliant toe and foot function of geckos. Our data not only enhance our understanding of geckos' environmental adaptive adhesion but can also provide inspiration for novel robot feet in development.

Role of multiple, adjustable toes in distributed control shown by sideways wall-running in geckos.

Remarkable progress has been made characterizing one of nature's most integrated, hierarchical structures--the fibrillar adhesive system of geckos. Nonetheless, we lack an understanding of how multiple toes coordinate to facilitate geckos' acrobatic locomotion. Here, we tested the control function of gecko toes by running them on vertical substrates varying in orientation, friction and roughness. Sideways wall-running geckos realigned the toes of their top feet upward to resist gravity. Toe contact area was not compromised, but redistributed. Geckos aligned all toes upward to resist slipping when encountering low-friction patches during sideways wall-running. Negotiation of intermittent slippery strips showed an increased contribution of particular toes to compensate for toes that lost adhesion. Increasing substrate roughness using discrete rods perpendicular to sideways locomotion resulted in geckos bending and/or rotating toes to conform to and even grasp the rods, with potential forces more than five times body weight. Geckos increase their effectiveness of manoeuvrability in demanding environments by taking advantage of the distributed control afforded by multiple toes. Our findings provide insight on biological attachment and offer inspiration to advance gecko-inspired robotics and other biomimetic applications.

Influence of carbon dioxide plasma treatment on the dry adhesion of vertical aligned carbon nanotube arrays.

Vertical aligned carbon nanotube (VACNT) arrays used as dry adhesive materials have broad prospects in the applied fields of space, medicine and electronics. The adhesion of VACNT arrays is believed to be related not only to the nano-array structure and a clean surface, but also to chemical composition. Here, radio-frequency (RF) carbon dioxide (CO2) plasma treatment is introduced as an effective method for purifying and functionalizing the surface to improve the dry adhesive performance of VACNT arrays. Scanning electron microscopy showed that the VACNT arrays retained the alignment architecture with minimal damage at low power. X-ray photoelectron spectroscopy and contact angle tests revealed that the content of non-polar components (C = C bonds) decreased after treatment, while the content of polar groups (C = O and O-C = O bonds) increased, which changed the surface polarity of the VACNT arrays. Raman analyses and transmission electron microscopy demonstrated that amorphous carbon can be selectively removed with increasing time (0-18 min), but was continuously generated with increasing power (30-90 W). The best adhesive strength of 18 N cm-2 (increased by 39%) was obtained after CO2 plasma treating for 10 min at 30 W power, which was attributed to the combined action of purification and polarization.

Application of robo-pigeon in ethological studies of bird flocks.

Birds flying collectively is a fascinating phenomenon in nature, which is central in ethological studies. Owing to the difficulty of introducing controlled variables into a natural bird flock, current animal behavior paradigms limit our understanding of collective behavior and mechanism. The recently developed technology of robo-pigeon, which allows behavior regulation over organisms through brain microstimulation, can potentially serve to design the controlled variables. However, it still poses challenges for unrestrained animals outdoors. Here we report the first application of robo-pigeon to the study of collective behavior, illustrating how intact pigeons in a flock interact with a program-controlled robo-pigeon. The controlled variable of direction manipulation introduced by the robo-pigeon may balance their preferred directional choice in the flock. Its effectivity depends on the hierarchical level to which the robo-pigeon belongs. This study suggests that direct manipulation of flight trajectories by a robo-pigeon might be a useful causal tool to study the collective behavior of bird flocks.

Enhanced Adhesion of Carbon Nanotubes by Dopamine Modification.

According to the fact that gecko-inspired vertically aligned carbon nanotubes (VA-CNTs) exhibit ultrastrong adhesion, dopamine is utilized to make a modification to this traditional biomimetic material. The composite material is tested for adhesion performance under different environmental conditions by an atomic force microscope. The adhesion force of the modified VA-CNTs does not show obvious fluctuation during the gradual heating process; however, the material gains improved adhesion when increasing the ambient humidity. In addition, the modified CNTs show a stronger adhesion force than the original CNTs in their performance tests. The dopamine polymer has a good combination with CNTs, which is responsible for the aforementioned excellent performance. Overall, this modification method is simple, convenient, efficient, and environmentally friendly, which all indicates a promising future in its application. The modified CNTs are expected to be used for super-adhesion in harsh environments, as well as in the field of microelectronics.

Lateral undulation of the flexible spine of sprawling posture vertebrates.

Sprawling posture vertebrates have a flexible spine that bends the trunk primarily in the horizontal plane during locomotion. By coordinating cyclical lateral trunk flexion and limb movements, these animals are very mobile and show extraordinary maneuverability. The dynamic and static stability displayed in complex and changing environments are highly correlated with such lateral bending patterns. The axial dynamics of their compliant body can also be critical for achieving energy-efficient locomotion at high velocities. In this paper, lateral undulation is used to characterize the bending pattern. The production of ground reaction forces (GRFs) and the related center of mass (COM) dynamics during locomotion are the fundamental mechanisms to be considered. Mainly based on research on geckos, which show unrestricted movement in three-dimensional space, we review current knowledge on the trunk flexibility and waveforms of lateral trunk movement. We investigate locomotion dynamics and mechanisms underlying the lateral undulation pattern. This paper also provides insights into the roles of this pattern in obtaining flexible and efficient walking, running, and climbing. Finally, we discuss the potential application of lateral undulation patterns to bio-inspired robotics.

The use of clamping grips and friction pads by tree frogs for climbing curved surfaces.

Most studies on the adhesive mechanisms of climbing animals have addressed attachment against flat surfaces, yet many animals can climb highly curved surfaces, like twigs and small branches. Here we investigated whether tree frogs use a clamping grip by recording the ground reaction forces on a cylindrical object with either a smooth or anti-adhesive, rough surface. Furthermore, we measured the contact area of fore and hindlimbs against differently sized transparent cylinders and the forces of individual pads and subarticular tubercles in restrained animals. Our study revealed that frogs use friction and normal forces of roughly a similar magnitude for holding on to cylindrical objects. When challenged with climbing a non-adhesive surface, the compressive forces between opposite legs nearly doubled, indicating a stronger clamping grip. In contrast to climbing flat surfaces, frogs increased the contact area on all limbs by engaging not just adhesive pads but also subarticular tubercles on curved surfaces. Our force measurements showed that tubercles can withstand larger shear stresses than pads. SEM images of tubercles revealed a similar structure to that of toe pads including the presence of nanopillars, though channels surrounding epithelial cells were less pronounced. The tubercles' smaller size, proximal location on the toes and shallow cells make them probably less prone to buckling and thus ideal for gripping curved surfaces.

How do the substrate reaction forces acting on a gecko's limbs respond to inclines?

Locomotion is an essential character of animals, and excellent moving ability results from the delicate sensing of the substrate reaction forces (SRF) acting on body and modulating the behavior to adapt the motion requirement. The inclined substrates present in habitats pose a number of functional challenges to locomotion. In order to effectively overcome these challenges, climbing geckos execute complex and accurate movements that involve both the front and hind limbs. Few studies have examined gecko's SRF on steeper inclines of greater than 90°. To reveal how the SRFs acting on the front and hind limbs respond to angle incline changes, we obtained detailed measurements of the three-dimensional SRFs acting on the individual limbs of the tokay gecko while it climbed on an inclined angle of 0-180°. The fore-aft forces acting on the front and hind limbs show opposite trends on inverted inclines of greater than 120°, indicating propulsion mechanism changes in response to inclines. When the incline angles change, the forces exerted in the normal and fore-aft directions by gecko's front and hind limbs are reassigned to take full advantage of limbs' different roles in overcoming resistance and in propelling locomotion. This also ensures that weight acts in the angle range between the forces generated by the front and hind limbs. The change in the distribution of SRF with a change in the incline angle is directly linked to the favorable trade-off between locomotive maneuverability and stability.

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.

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.

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.

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.

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.

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.