Bioinspiration & Biomimetics

The past ten years have seen the rapid expansion of the field of biohybrid robotics. By combining engineered, synthetic components with living biological materials, new robotics solutions have been developed that harness the adaptability of living muscles, the sensitivity of living sensory cells, and even the computational abilities of living neurons. Biohybrid robotics has taken the popular and scientific media by storm with advances in the field, moving biohybrid robotics out of science fiction and into real science and engineering. So how did we get here, and where should the field of biohybrid robotics go next? In this perspective, we first provide the historical context of crucial subareas of biohybrid robotics by reviewing the past 10+ years of advances in microorganism-bots and sperm-bots, cyborgs, and tissue-based robots. We then present critical challenges facing the field and provide our perspectives on the vital future steps toward creating autonomous living machines.

In this study, a miniature artificial compound eye (15 mm in diameter) called the curved artificial compound eye (CurvACE) was endowed for the first time with hyperacuity, using similar micro-movements to those occurring in the fly's compound eye. A periodic micro-scanning movement of only a few degrees enables the vibrating compound eye to locate contrasting objects with a 40-fold greater resolution than that imposed by the interommatidial angle. In this study, we developed a new algorithm merging the output of 35 local processing units consisting of adjacent pairs of artificial ommatidia. The local measurements performed by each pair are processed in parallel with very few computational resources, which makes it possible to reach a high refresh rate of 500 Hz. An aerial robotic platform with two degrees of freedom equipped with the active CurvACE placed over naturally textured panels was able to assess its linear position accurately with respect to the environment thanks to its efficient gaze stabilization system. The algorithm was found to perform robustly at different light conditions as well as distance variations relative to the ground and featured small closed-loop positioning errors of the robot in the range of 45 mm. In addition, three tasks of interest were performed without having to change the algorithm: short-range odometry, visual stabilization, and tracking contrasting objects (hands) moving over a textured background.

Biomimetics as the transdisciplinary field leveraging biologically inspired solutions for technical and practical challenges has gained traction in recent decades. Despite its potential for innovation, the complexity of its process requires a deeper understanding of underlying tasks, leading to the development of various tools to aid this process. This study identified an inventory of 104 tools used in biomimetics, of which 24 have been classified as fully accessible, functional, and ready-to-use biomimetic tools. Additionally, it provides definitions and evaluation criteria for biomimetic tools, offering a structured approach to tool assessment. The 24 tools have been assessed based on ten criteria in a qualitative and quantitative analysis yielding an overview of their typology, accessibility, stage of development, and other key characteristics. Patterns of the typology development of tools over time revealed a trend towards integrating computational methods and artificial intelligence, thereby enhancing the tool's functionality and user engagement. However, gaps in tool functionality and maturity, such as the lack of tools designed to support technical processes, the absence of tools tailored for solution-based approaches, and insufficient evidence of successful tool application, highlight areas for future research. The study results underscore the need for empirical validation of tools, and research into the effectiveness of holistic tools covering multiple stages of the biomimetic process. By addressing these gaps and leveraging existing strengths, the field of biomimetics can continue to advance, providing innovative solutions inspired by biological models.

Birds and mammals have evolved many thermal adaptations that are relevant to the bioinspired design of temperature control systems and energy management in buildings. Similar to many buildings, endothermic animals generate internal metabolic heat, are well insulated, regulate their temperature within set limits, modify microclimate and adjust thermal exchange with their environment. We review the major components of animal thermoregulation in endothermic birds and mammals that are pertinent to building engineering, in a world where climate is changing and reduction in energy use is needed. In animals, adjustment of insulation together with physiological and behavioural responses to changing environmental conditions fine-tune spatial and temporal regulation of body temperature, while also minimizing energy expenditure. These biological adaptations are characteristically flexible, allowing animals to alter their body temperatures to hourly, daily, or annual demands for energy. They exemplify how buildings could become more thermally reactive to meteorological fluctuations, capitalising on dynamic thermal materials and system properties. Based on this synthesis, we suggest that heat transfer modelling could be used to simulate these flexible biomimetic features and assess their success in reducing energy costs while maintaining thermal comfort for given building types.

Locomotion on soft yielding grounds is more complicated and energetically demanding than on hard ground. Wet soft ground (such as mud or snow) is a particularly difficult substance because it dissipates energy when stepping and resists extrusion of the foot. Sinkage in mud forces walkers to make higher steps, thus, to spend more energy. Yet wet yielding terrains are part of the habitat of numerous even-toed ungulates (large mammals with split hooves). We hypothesized that split hooves provide an advantage on wet grounds and investigated the behavior of moose legs on a test rig. We found that split hooves of a moose reduce suction force at extrusion but could not find conclusive evidence that the hoof reduces sinkage. We then continued by designing artificial feet equipped with split-hoof-inspired protuberances and testing them under different conditions. These bio-inspired feet demonstrate an anisotropic behavior enabling reduction of sinkage depth up to 46.3%, suction force by 47.6%, and energy cost of stepping on mud by up to 70.4%. Finally, we mounted these artificial feet on a Go1 quadruped robot moving in mud and observed 38.7% reduction of the mechanical cost of transport and 55.0% increase of speed. Those results help us understand the physics of mud locomotion of animals and design better robots moving on wet terrains. We did not find any disadvantages of the split-hooves-inspired design on hard ground, which suggests that redesigning the feet of quadruped robots improves their overall versatility and efficiency on natural terrains.

In the aquatic world jet propulsion is a highly successful locomotion method utilized by a variety of species. Among them cephalopods such as squids excel in their ability for high-speed swimming. This mechanism inspires the development of underwater locomotion techniques which are particularly useful in soft-bodied robots. In this overview we summarize existing studies on this topic, ranging from investigations on the underlying physics to the creation of mechanical systems utilizing this locomotion mode. Research directions that worth future investigation are also discussed.

Due to the complexity of deformations in soft manipulators, achieving precise control of their orientation is particularly challenging, especially in the presence of external disturbances and human interactions. Inspired by the decentralized growth mechanism of plant gravitropism, which enables plants' roots and stems to grow in the direction of gravity despite complex environmental interactions, this study proposes a decentralized control strategy for robust orientation control of multi-segment soft manipulators. This gravitropism-inspired decentralized controller was validated through simulations for convergence and robustness, and benchmarked against the traditional inverse Jacobian-based controller on a large-scale multi-segment soft manipulator. Experimental results demonstrate that the decentralized controller achieves comparable convergence and better control precision to the inverse Jacobian-based controller, while significantly outperforming it in disturbance rejection. Even in the presence of partial damage and human interaction, the decentralized controller provides robust control. This study provides a robust new approach for managing disturbances in complex environments, laying the foundation for further exploration of decentralized control strategies in soft robotics.

A transverse ledge brachiation robot is designed to move transversely along a ledge on a vertical wall by generating energy from the swinging motion of its lower limbs. This method reduces the force required by the upper limbs to propel the robot forward. However, previously developed robots often encounter a common issue: lateral posture deviation, which is typically caused by slippage when the grippers grasp the ledge. Without compensation, this deviation can increase the risk of falling during continuous brachiation cycles. To address this problem, we propose an active wrist joint mechanism utilizing a feedback control approach as the compensator to effectively correct gripper position deviations. In our robot design, we develop a motion control strategy that coordinates the upper and lower limbs in order to maintain the swing energy that can be transferred to the subsequent cycles. Then we propose a potential energy-based phase switching condition in the motion control strategy in order to simplify the computation process. Simulation results demonstrate that the optimized parameter for compensation effectively maintains the gripper's position relative to the ledge throughout 55 brachiation cycles. Furthermore, experiment validation shows that this posture compensation reduces deviation by one-third compared to results without compensation. This study has demonstrated a 68% improvement in energy consumption efficiency for continuous transverse brachiation compared to the previous generation, as well as a 37% improvement over transverse ricochetal brachiation locomotion.

In the early twenty-first century, extensive research has been conducted on geckos' ability to climb vertical walls with the advancement of microscopy technology. Unprecedented studies and developments have focused on the adhesion mechanism, structural design, preparation methods, and applications of bioinspired dry adhesives. Notably, strong adhesion that adheres to both the principles of contact splitting and stress uniform distribution has been discovered and proposed. The increasing popularity of flexible electronic skins, soft crawling robots, and smart assembly systems has made switchable adhesion properties essential for smart adhesives. These adhesives are designed to be programmable and switchable in response to external stimuli such as magnetic fields, thermal changes, electrical signals, light exposure as well as mechanical processes. This paper provides a comprehensive review of the development history of bioinspired dry adhesives from achieving strong adhesion to realizing switchable adhesion.

This paper broadly summarizes the variation of design features found in vertebrate limbs and analyses the resultant versatility and multifunctionality in order to make recommendations for bioinspired robotics. The vertebrate limb pattern (e.g. shoulder, elbow, wrist and digits) has been proven to be very successful in many different applications in the animal kingdom. However, the actual level of optimality of the limb for each animal application is not clear because for some cases (e.g. whale flippers and bird wings), the basic skeletal layout is assumed to be highly constrained by evolutionary ancestry. This paper addresses this important and fundamental question of optimality by analysing six limbs with contrasting functions: human arm, whale flipper, bird wing, human leg, feline hindlimb and frog hindlimb. A central finding of this study is that the vertebrate limb pattern is highly versatile and optimal not just for arms and legs but also for flippers and wings. One key design feature of the vertebrate limb pattern is that of networks of segmented bones that enable smooth morphing of shapes as well as multifunctioning structures. Another key design feature is that of linkage mechanisms that fine-tune motions and mechanical advantage. A total of 52 biomechanical design features of the vertebrate limb are identified and tabulated for these applications. These tables can be a helpful reference for designers of bioinspired robotic and prosthetic limbs. The vertebrate limb has significant potential for the bioinspired design of robotic and prosthetic limbs, especially because of progress in the development of soft actuators.

One of the most ancient and evolutionarily conserved behaviors in the animal kingdom involves utilizing wind-borne odor plumes to track essential elements such as food, mates, and predators. Insects, particularly flies, demonstrate a remarkable proficiency in this behavior, efficiently processing complex odor information encompassing concentrations, direction, and speed through their olfactory system, thereby facilitating effective odor-guided navigation. Recent years have witnessed substantial research explaining the impact of wing flexibility and kinematics on the aerodynamics and flow field physics governing the flight of insects. However, the relationship between the flow field and olfactory functions remains largely unexplored, presenting an attractive frontier with numerous intriguing questions. One such question pertains to whether flies intentionally manipulate the flow field around their antennae using their wing structure and kinematics to augment their olfactory capabilities. To address this question, we first reconstructed the wing kinematics based on high-speed video recordings of wing surface deformation. Subsequently, we simulated the unsteady flow field and odorant transport during the forward flight of blue bottle flies (Calliphora vomitoria) by solving the Navier–Stokes equations and odorant advection–diffusion equations using an in-house computational fluid dynamics solver. Our simulation results demonstrated that flexible wings generated greater cycle-averaged aerodynamic forces compared to purely rigid flapping wings, underscoring the aerodynamic advantages of wing flexibility. Additionally, flexible wings produced 25% greater odor intensity, enhancing the insect's ability to detect and interpret olfactory cues. This study not only advances our understanding of the intricate interplay between wing motion, aerodynamics, and olfactory capabilities in flying insects but also raises intriguing questions about the intentional modulation of flow fields for sensory purposes in other behaviors.

Natural photonic structures allow us to reveal and mold the thermophoretic effect at the nanoscale within condensed matter systems. In this paper, for the first time, holography has been exploited to disclose conditions that determine the strength and dynamics of the thermophoretic effect. We experimentally revealed the link between geometry and nano-corrugation of biological structures that shapes the power of thermophoresis. The presented study opens enormous possibilities for harnessing the thermophoretic effect in various bioinspired sensing applications, uniquely merging the fields of photonics and mechanics.

Animals have to navigate complex environments and perform intricate swimming maneuvers in the real world. To conquer these challenges, animals evolved a variety of motion control strategies. While it is known that many factors contribute to motion control, we specifically focus on the role of stretch sensory feedback. We investigate how stretch feedback potentially serves as a way to coordinate locomotion, and how different stretch feedback topologies, such as networks spanning varying ranges along the spinal cord, impact the locomotion. We conduct our studies on a simulated robot model of the lamprey consisting of an articulated spine with eleven segments connected by actuated joints. The stretch feedback is modeled with neural networks trained with deep reinforcement learning. We find that the topology of the feedback influences the energy efficiency and smoothness of the swimming, along with various other metrics characterizing the locomotion, such as frequency, amplitude and stride length. By analyzing the learned feedback networks, we highlight the importances of very local, caudally-directed, as well as stretch derivative information. Our results deliver valuable insights into the potential mechanisms and benefits of stretch feedback control and inspire novel decentralized control strategies for complex robots.

Bionic flapping wing robots achieve flight by imitating animal flapping wings, which are safe, flexible, and efficient. Their practicality and human-machine symbiosis in narrow and complex environments are better than traditional fixed-wing or multirotor drones, indicating broader application potential. By systematic and biomimetic methods, a bionic dragonfly robot with four independent drive flapping wings, called DFly-I, was designed. Firstly, the mechanical structure of the robot was introduced, especially the fluttering structure and the wing structure. Then, a novel motion controller utilizing multi-channel field-oriented control (FOC) is proposed for its motion mechanism, which relies on four sets of brushless DC motors based on FOC control and four sets of servos to achieve independent control of the flapping speed, rhythm, and angle of the four flapping wings. In addition, the system model is analyzed, and based on this, the robot motion and posture control are realized by a proportional–integral–derivative and active disturbance rejection based controller. Lastly, a physical prototype was made, and its feasibility was verified through flight experiments in indoor venues.

Interlocking metasurfaces (ILMs) are patterned arrays of mating features that enable the joining of bodies by constraining motion and transmitting force. They offer an alternative to traditional joining solutions such as mechanical fasteners, welds, and adhesives. This study explores the development of bio-inspired ILMs using a problem-driven bioinspired design (BID) framework. We develop a taxonomy of attachment solutions that considers both biological and engineered systems and derive conventional design principles for ILM design. We conceptualize two engineering implementations to demonstrate concept development using the taxonomy and ILM conventional design principle through the BID framework: one for rapidly assembled bridge truss members and another for modular microrobots. These implementations highlight the potential of BID to enhance performance, functionality, and tunability in ILMs.

Bird-like flapping-wing aerial vehicles (BFAVs) have attracted significant attention due to their advantages in endurance, range, and load capacity. For a long time, biologists have been studying the enigma of bird flight to understand its mechanism. In contrast, aviation designers focus more on bionic flight systems. This paper presents a comprehensive review of the development of BFAV design. The study aims to provide insights into building a flyable model from the perspective of aviation designers, focusing on the methods in the process of overall design, flapping wing design and drive system design. The review examines the annual progress of flight-capable BFAVs, analyzing changes in prototype size and performance over the years. Additionally, the paper highlights various applications of these vehicles. Furthermore, it discusses the challenges encountered in BFAV design and proposes several possible directions for future research, including perfecting design methods, improving component performance, and promoting practical application. This review will provide essential guidelines and insights for designing BFAVs with higher performance.

This paper broadly summarizes the variation of design features found in vertebrate limbs and analyses the resultant versatility and multifunctionality in order to make recommendations for bioinspired robotics. The vertebrate limb pattern (e.g. shoulder, elbow, wrist and digits) has been proven to be very successful in many different applications in the animal kingdom. However, the actual level of optimality of the limb for each animal application is not clear because for some cases (e.g. whale flippers and bird wings), the basic skeletal layout is assumed to be highly constrained by evolutionary ancestry. This paper addresses this important and fundamental question of optimality by analysing six limbs with contrasting functions: human arm, whale flipper, bird wing, human leg, feline hindlimb and frog hindlimb. A central finding of this study is that the vertebrate limb pattern is highly versatile and optimal not just for arms and legs but also for flippers and wings. One key design feature of the vertebrate limb pattern is that of networks of segmented bones that enable smooth morphing of shapes as well as multifunctioning structures. Another key design feature is that of linkage mechanisms that fine-tune motions and mechanical advantage. A total of 52 biomechanical design features of the vertebrate limb are identified and tabulated for these applications. These tables can be a helpful reference for designers of bioinspired robotic and prosthetic limbs. The vertebrate limb has significant potential for the bioinspired design of robotic and prosthetic limbs, especially because of progress in the development of soft actuators.

In the early twenty-first century, extensive research has been conducted on geckos' ability to climb vertical walls with the advancement of microscopy technology. Unprecedented studies and developments have focused on the adhesion mechanism, structural design, preparation methods, and applications of bioinspired dry adhesives. Notably, strong adhesion that adheres to both the principles of contact splitting and stress uniform distribution has been discovered and proposed. The increasing popularity of flexible electronic skins, soft crawling robots, and smart assembly systems has made switchable adhesion properties essential for smart adhesives. These adhesives are designed to be programmable and switchable in response to external stimuli such as magnetic fields, thermal changes, electrical signals, light exposure as well as mechanical processes. This paper provides a comprehensive review of the development history of bioinspired dry adhesives from achieving strong adhesion to realizing switchable adhesion.

This review explores the present knowledge of the unique properties of shark skin and possible applications of its functionalities, including drag reduction and swimming efficiency. Tooth-like denticles, with varied morphologies, sizes, and densities across the shark's body, significantly influence the flow and interaction of fluids. Examining dermal denticle morphology, this study unveils the functional properties of real shark skin, including mechanical properties such as stiffness, stress–strain characteristics, and denticle density's impact on tensile properties. The adaptive capabilities of the Mako shark scales, especially in high-speed swimming, are explored, emphasizing their passive flow-actuated dynamic micro-roughness. This research contains an overview of various studies on real shark skin, categorizing them into skin properties, morphology, and hydrodynamics. The paper extends exploration into industrial applications, detailing fabrication techniques and potential uses in vessels, aircraft, and water pipes for friction reduction. Three manufacturing approaches, bio-replicated forming, direct fabrication, and indirect manufacturing, are examined, with 3D printing and photoconfiguration technology emerging as promising alternatives. Investigations into the mechanical properties of shark skin fabrics reveal the impact of denticle size on tensile strength, stress, and strain. Beyond drag reduction, the study highlights the shark skin's role in enhancing thrust and lift during locomotion. The paper identifies future research directions, emphasizing live shark testing and developing synthetic skin with the help of 3D printing incorporating the bristling effect.

This research presents a 10-year systematic review based on bibliometric analysis of the bio-inspired design of hard-bodied mobile robot mechatronic systems considering the anatomy of arthropods. These are the most diverse group of animals whose flexible biomechanics and adaptable morphology, thus, it can inspire robot development. Papers were reviewed from two international databases (Scopus and Web of Science) and one platform (Aerospace Research Central), then they were classified according to: Year of publication (January 2013 to April 2023), arthropod group, published journal, conference proceedings, editorial publisher, research teams, robot classification according to the name of arthropod, limb's locomotion support, number of legs/arms, number of legs/body segments, limb's degrees of freedom, mechanical actuation type, modular system, and environment adaptation. During the screening, more than 33 000 works were analyzed. Finally, a total of 174 studies (90 journal-type, 84 conference-type) were selected for in-depth study: Insecta—hexapods (53.8%), Arachnida—octopods (20.7%), Crustacea—decapods (16.1%), and Myriapoda—centipedes and millipedes (9.2%). The study reveals that the most active editorials are the Institute of Electrical and Electronics Engineers Inc., Springer, MDPI, and Elsevier, while the most influential researchers are located in the USA, China, Singapore, and Japan. Most works pertained to spiders, crabs, caterpillars, cockroaches, and centipedes. We conclude that 'arthrobotics' research, which merges arthropods and robotics, is constantly growing and includes a high number of relevant studies with findings that can inspire new methods to design biomechatronic systems.

Seals are able to use their uniquely shaped whiskers to track hydrodynamic trails generated 30 s ago and detect hydrodynamic velocities as low as 245 m s⁻¹. The high sensibility has long thought to be related to the wavy shape of the whiskers. This work revisited the hydrodynamics of a seal whisker model in a uniform flow, and discovered a new mechanism of seal whiskers in reducing self-induced noises, which is different from the long thought-of effect of the wavy shape. It was reported that the major and minor axes of the elliptical cross-sections of seal whisker are out of phase by approximately 180 degrees. Three-dimensional numerical simulations of laminar flow (Reynolds number range: 150–500) around seal-whisker-like cylinders were performed to examine the effect of the phase-difference on hydrodynamic forces and wake structures. It was found that the phase-difference induced hairpin vortices in the wake over a wide range of geometric and flow parameters (wavelength, wavy amplitude and Reynolds number), therefore substantially reducing lift-oscillations and self-induced noises. The formation mechanism of the hairpin vortices was analyzed and is discussed in details. The results provide valuable insights into an innovative vibration reduction and hydrodynamic sensing mechanism.

Quadrupeds achieve rapid and highly adaptive locomotion owing to the coordination between their legs and other body parts such as their trunk, head, and tail, i.e. body–limb coordination. Therefore, a better understanding of the mechanism underlying body–limb coordination could provide informative insights into the improvement of legged robot mobility. Sprawling locomotion is a walking gait with lateral bending exhibited in primitive legged vertebrates such as salamanders and newts. Because primitive animals are anticipated to possess the essence of quadruped motor control, their locomotion helps better understand body–limb coordination mechanisms. Previous studies modeled neural networks in salamanders and employed it to control robots and investigate and emulate sprawling locomotion. However, these models predefined the relationship between the legs and the trunk, such that how body–limb coordination is attained is largely unknown. In this article, we demonstrate that sensory feedback facilitates body–limb coordination in sprawling locomotion and improves mobility through mathematical modeling and robot simulations. Our proposed model has cross-coupled sensory feedback, that is, bidirectional feedback from body to limb and limb to body, which leads to an appropriate relationship between the legs and the trunk without any predefined relationship. Resulting gaits are similar to the sprawling locomotion of salamanders and achieve high speed and energy efficiency that are at the same level as those of a neural network model, such as conventional models, optimizing the relationship between the legs and the trunk. Furthermore, sensory feedback contributes to the adaptability toward leg failure, and the bidirectionality of feedback facilitates parameter tuning for stable locomotion. These results suggest that cross-coupled sensory feedback facilitates sprawling locomotion and potentially plays an important role in the body–limb coordination mechanism.

Chimney swifts (Chaetura pelagica) are highly aerial, small, insectivorous birds well known for roosting en masse in chimneys during their autumn migration. These roosting events require hundreds to thousands of birds to enter a small opening (here 0.64 m²) within a short amount of time (15–30 min). Thus, these entry events pose a complex navigational and behavioral challenge as birds identify their entry route, cooperate with other birds present to form an entry flock, and compete with other birds at the time of chimney entry. We used six synchronized cameras to capture and reconstruct the 3D flight trajectories of swifts before and during chimney entry. Navigation into the chimney is consistent with use of a relative retinal expansion velocity cue, which results in an entry/non-entry decision point about 1.5 m above the chimney, or 0.4 s at typical entry speeds. Entries were highly clustered with 91 of 136 entries occurring within 1 s of another entry. We observed both synchronous (entry within 0.2 s) and sequential entry behavior (entry separated by ~0.4 s). Birds entering the chimney flew in close proximity to other birds (median minimum distance 0.51 m; 1.7 wingspans). In cases where two birds appeared to attempt a near-simultaneous entry, the bird either slightly to the rear or with a velocity vector bringing it closer to the current position of the other bird tended to make an avoidance maneuver and abandon its entry attempt. Overall, these results show how groups of animals execute complex landing and collision avoidance maneuvers in a natural setting without central control authority.

Groups of organisms such as flocks, swarms, herds, and schools form for a variety of motivations linked to survival and proliferation. Their size, locomotive domain, population, and the environmental stimuli guiding motion make challenging the study of member interactions and global behaviors. In this review, we borrow principles and analogies from fluids to describe the characteristics of organismal aggregations, which may inspire new tools for the analysis of collective motion. Examples of fluid resemblance include open channel flow, droplet formation, and particle-laden flow. We show how the properties of density, viscosity, and surface tension have strong parallels in the structure and behavior of aggregations of contrasting scale and domain. In certain cases, aggregations are sufficiently fluid-like that values can be assigned to such properties. We highlight how organisms engaging in collective motion can flow, roll, and change phase. Finally, we present limitations and exceptions for the application of fluidic principles to the motion of living groups.

While numerous gait families have been defined and studied for legged systems traversing level ground (e.g. walking, running, bounding, etc), formal distinctions have yet to be developed for dynamic gaits in the vertical regime. Recognition and understanding of different gait families has clear implications to control strategy, efficiency, and stability. While several climbing robotic systems have been described as achieving 'running' behaviors on vertical surfaces, the question of whether distinct dynamic gaits exist and what differentiates these gaits has not been rigorously explored. In this paper, by applying definitions developed in the horizontal regime to simulation and experimental data, we show evidence of three distinct dynamic climbing gaits families and discuss the implications of these gaits on the development of more advanced climbing robots.

This study presents a flexible aquatic swimming robot, which is a promising candidate for underwater search and detection missions. The robot is a living eel fitted with a wireless electronic backpack stimulator attached to its dorsal region. Leveraging the eel's inherent self-balancing and self-adaptation abilities, the robot can adapt seamlessly to complex underwater environments without the need for sophisticated controllers. Lateral line stimulation allows the robot to execute forward and backward swimming, as well as left and right curls. We graded the forward and backward swimming speed by varying the stimulus frequency and pulse width. The optimal stimulus parameters are as follows: amplitude 3.0-4.5 V, frequency 5-20 Hz, and pulse width 40-60 ms. The maximum success rates for forward and backward swimming responses to stimuli were approximately 96% and 77%, respectively. Utilizing lower pulse frequencies (5-20 Hz) and wider pulse widths (40-60 ms) facilitated sustained and efficient activation of the lateral line neural system. Electrical stimulation of the lateral line increases the eel's forward swimming speed by approximately 70%, while the electronic backpack draws only 48.1 mW of external power. Compared to bio-inspired robots, the eel-machine hybrid robot consumes 1.5 to 1100 times less external power per unit mass. The remarkable efficiency of this bio-robot enhances its performance in tasks such as underwater cave exploration.

Most walking organisms tend to have relatively light limbs and heavy bodies in order to facilitate rapid limb motion. However, the limbs of brittle stars (Class Ophiuroidea) are primarily comprised of dense skeletal elements, with potentially much higher mass and density compared to the body disk. To date, little is understood about how the relatively unique distribution of mass in these animals influences their locomotion. In this work, we use a brittle star inspired soft robot and computational modeling to examine how the distribution of mass and density in brittle stars affects their movement. The soft robot is fully untethered, powered using embedded shape memory alloy (SMA) actuators, and designed based on the morphology of a natural brittle star. Computational simulations of the brittle star model are performed in a differentiable robotics physics engine in conjunction with an iterative linear quadratic regulator (iLQR) to explore the relationship between different mass distributions and their optimal gaits. The results from both methods indicate that there are robust physical advantages to having the majority of the mass concentrated in the limbs for brittle star-like locomotion, providing insight into the physical forces at play.

Multi-terrain adaptation and landing capabilities pose substantial challenges for pneumatic bionic robots, particularly in crossing obstacles. This paper designs a turtle-inspired quadrupedal pneumatic soft crawling robot with four deformable bionic legs to mimic the structure and movement of turtle legs. Finite element software is used to design and optimize the wall thickness of the soft actuator. Experimental tests are conducted under different pressures to verify the bending capability of the upper leg (0-40 kPa) and lower leg (0-60 kPa). Four gait models of the robot are achieved by controlling the airflow in different chambers of four soft actuators. Then the corresponding test scenarios are established to confirm gait control effectiveness. The soft actuator is designed with adjusted gait overlap ratios (0, 0.25, 0.5, 0.75, 1), enabling the soft robot to overcome obstacles up to 25mm in height, showcasing superior obstacle-crossing capabilities. In addition to moving straight (maximum speed: 0.41 BL/s) and turning on rigid surfaces (45°/s), the robot is capable of crawling on various complex terrains (cloth, sand, flat ground, and slope) as well as water planing. These characteristics make the robot suitable for a wide range of applications, such as search and rescue, exploration, and inspection. The robot's ability to traverse complex environments and its robust performance in various conditions highlight its potential for real-world deployment.

Traditional underwater sonar detection systems are primarily based on numerical methods such as pulse compression, Doppler velocity measurement, and beamforming to measure target distance, velocity, and azimuth parameters. In contrast, the sonar systems of organisms like bats rely on highly evolved neural perception to accomplish these tasks. By studying the detection mechanisms of biological sonar and developing bionic models, the target detection capabilities of underwater sonar systems can be enhanced. Inspired by Hipposideros Pratti., this paper designs a bat bio-sonar model for underwater target detection and provides theoretical derivations for various target parameters detection. A biomimetic sonar multi-harmonic signal waveform is designed based on multi-carrier modulation theory. Through the combination of different subcarrier components, the signal's penetration power is optimized, environmental noise interference is reduced, and target resolution and recognition accuracy are enhanced. The proposed waveform's excellent anti-reverberation performance is demonstrated through evaluations in underwater reverberation scenarios. For signal processing, this paper designs a parallel hierarchical processing architecture that can simultaneously handle different harmonic components sensing speed, distance, and azimuth information, significantly improving recognition accuracy and signal processing efficiency. To enhance the intelligence of bionic sonar systems, a parallel intelligent perception network model based on dilated convolution is proposed. It leverages feature maps of different harmonic groups to reduce the number of features required for extraction, improving the model's training efficiency and achieving intelligent perception of the sonar system. Simulation results indicate that the combination of different harmonic components can effectively perceive variations in target speed, distance, and direction, exhibiting strong anti-reverberation capability. Neural network recognition results show that the combination of different harmonics achieves an accuracy rate of over 95% for speed, distance, and azimuth recognition, verifying that the designed model has strong capabilities in underwater target perception.

Animal-robot interaction (ARI) is an emerging field that uses biomimetic robots to replicate biological cues, enabling controlled studies of animal behavior. This study investigates the potential for ARI systems to induce local enhancement (e.g., where animals are attracted to areas based on the presence or actions of conspecifics) in the Mediterranean fruit fly, Ceratitis capitata, a major agricultural pest. We developed biomimetic agents that mimic C. capitata in morphology and color, to explore their ability to trigger local enhancement. The study employed three categories of artificial agents: Full Biomimetic Agent (FBA), Partial Biomimetic Agent (PBA), and Non-Biomimetic Agent (NBA), in both motionless and moving states. Flies exposed to motionless FBAs showed a significant preference for areas containing these agents compared to areas with no agents. Similarly, moving FBAs also attracted more flies than stationary agents. Time spent in the release section before making a choice and the overall experiment duration were significantly shorter when conspecifics or moving FBAs were present, indicating that C. capitata is highly responsive to biomimetic cues, particularly motion. These results suggest that ARI systems can be effective tools for understanding and manipulating local enhancement in C. capitata, offering new opportunities for sustainable pest control in agricultural contexts. Overall, this research demonstrates the potential of ARI as an innovative, sustainable approach to insect population control, with broad applications in both fundamental behavioral research and integrated pest management.

One of the most ancient and evolutionarily conserved behaviors in the animal kingdom involves utilizing wind-borne odor plumes to track essential elements such as food, mates, and predators. Insects, particularly flies, demonstrate a remarkable proficiency in this behavior, efficiently processing complex odor information encompassing concentrations, direction, and speed through their olfactory system, thereby facilitating effective odor-guided navigation. Recent years have witnessed substantial research explaining the impact of wing flexibility and kinematics on the aerodynamics and flow field physics governing the flight of insects. However, the relationship between the flow field and olfactory functions remains largely unexplored, presenting an attractive frontier with numerous intriguing questions. One such question pertains to whether flies intentionally manipulate the flow field around their antennae using their wing structure and kinematics to augment their olfactory capabilities. To address this question, we first reconstructed the wing kinematics based on high-speed video recordings of wing surface deformation. Subsequently, we simulated the unsteady flow field and odorant transport during the forward flight of blue bottle flies (Calliphora vomitoria) by solving the Navier–Stokes equations and odorant advection–diffusion equations using an in-house computational fluid dynamics solver. Our simulation results demonstrated that flexible wings generated greater cycle-averaged aerodynamic forces compared to purely rigid flapping wings, underscoring the aerodynamic advantages of wing flexibility. Additionally, flexible wings produced 25% greater odor intensity, enhancing the insect's ability to detect and interpret olfactory cues. This study not only advances our understanding of the intricate interplay between wing motion, aerodynamics, and olfactory capabilities in flying insects but also raises intriguing questions about the intentional modulation of flow fields for sensory purposes in other behaviors.

Most walking organisms tend to have relatively light limbs and heavy bodies in order to facilitate rapid limb motion. However, the limbs of brittle stars (Class Ophiuroidea) are primarily comprised of dense skeletal elements, with potentially much higher mass and density compared to the body disk. To date, little is understood about how the relatively unique distribution of mass in these animals influences their locomotion. In this work, we use a brittle star inspired soft robot and computational modeling to examine how the distribution of mass and density in brittle stars affects their movement. The soft robot is fully untethered, powered using embedded shape memory alloy (SMA) actuators, and designed based on the morphology of a natural brittle star. Computational simulations of the brittle star model are performed in a differentiable robotics physics engine in conjunction with an iterative linear quadratic regulator (iLQR) to explore the relationship between different mass distributions and their optimal gaits. The results from both methods indicate that there are robust physical advantages to having the majority of the mass concentrated in the limbs for brittle star-like locomotion, providing insight into the physical forces at play.

Animals have to navigate complex environments and perform intricate swimming maneuvers in the real world. To conquer these challenges, animals evolved a variety of motion control strategies. While it is known that many factors contribute to motion control, we specifically focus on the role of stretch sensory feedback. We investigate how stretch feedback potentially serves as a way to coordinate locomotion, and how different stretch feedback topologies, such as networks spanning varying ranges along the spinal cord, impact the locomotion. We conduct our studies on a simulated robot model of the lamprey consisting of an articulated spine with eleven segments connected by actuated joints. The stretch feedback is modeled with neural networks trained with deep reinforcement learning. We find that the topology of the feedback influences the energy efficiency and smoothness of the swimming, along with various other metrics characterizing the locomotion, such as frequency, amplitude and stride length. By analyzing the learned feedback networks, we highlight the importances of very local, caudally-directed, as well as stretch derivative information. Our results deliver valuable insights into the potential mechanisms and benefits of stretch feedback control and inspire novel decentralized control strategies for complex robots.

Animal-robot interaction (ARI) is an emerging field that uses biomimetic robots to replicate biological cues, enabling controlled studies of animal behavior. This study investigates the potential for ARI systems to induce local enhancement (e.g., where animals are attracted to areas based on the presence or actions of conspecifics) in the Mediterranean fruit fly, Ceratitis capitata, a major agricultural pest. We developed biomimetic agents that mimic C. capitata in morphology and color, to explore their ability to trigger local enhancement. The study employed three categories of artificial agents: Full Biomimetic Agent (FBA), Partial Biomimetic Agent (PBA), and Non-Biomimetic Agent (NBA), in both motionless and moving states. Flies exposed to motionless FBAs showed a significant preference for areas containing these agents compared to areas with no agents. Similarly, moving FBAs also attracted more flies than stationary agents. Time spent in the release section before making a choice and the overall experiment duration were significantly shorter when conspecifics or moving FBAs were present, indicating that C. capitata is highly responsive to biomimetic cues, particularly motion. These results suggest that ARI systems can be effective tools for understanding and manipulating local enhancement in C. capitata, offering new opportunities for sustainable pest control in agricultural contexts. Overall, this research demonstrates the potential of ARI as an innovative, sustainable approach to insect population control, with broad applications in both fundamental behavioral research and integrated pest management.

Interlocking metasurfaces (ILMs) are patterned arrays of mating features that enable the joining of bodies by constraining motion and transmitting force. They offer an alternative to traditional joining solutions such as mechanical fasteners, welds, and adhesives. This study explores the development of bio-inspired ILMs using a problem-driven bioinspired design (BID) framework. We develop a taxonomy of attachment solutions that considers both biological and engineered systems and derive conventional design principles for ILM design. We conceptualize two engineering implementations to demonstrate concept development using the taxonomy and ILM conventional design principle through the BID framework: one for rapidly assembled bridge truss members and another for modular microrobots. These implementations highlight the potential of BID to enhance performance, functionality, and tunability in ILMs.

Due to the complexity of deformations in soft manipulators, achieving precise control of their orientation is particularly challenging, especially in the presence of external disturbances and human interactions. Inspired by the decentralized growth mechanism of plant gravitropism, which enables plants' roots and stems to grow in the direction of gravity despite complex environmental interactions, this study proposes a decentralized control strategy for robust orientation control of multi-segment soft manipulators. This gravitropism-inspired decentralized controller was validated through simulations for convergence and robustness, and benchmarked against the traditional inverse Jacobian-based controller on a large-scale multi-segment soft manipulator. Experimental results demonstrate that the decentralized controller achieves comparable convergence and better control precision to the inverse Jacobian-based controller, while significantly outperforming it in disturbance rejection. Even in the presence of partial damage and human interaction, the decentralized controller provides robust control. This study provides a robust new approach for managing disturbances in complex environments, laying the foundation for further exploration of decentralized control strategies in soft robotics.

A transverse ledge brachiation robot is designed to move transversely along a ledge on a vertical wall by generating energy from the swinging motion of its lower limbs. This method reduces the force required by the upper limbs to propel the robot forward. However, previously developed robots often encounter a common issue: lateral posture deviation, which is typically caused by slippage when the grippers grasp the ledge. Without compensation, this deviation can increase the risk of falling during continuous brachiation cycles. To address this problem, we propose an active wrist joint mechanism utilizing a feedback control approach as the compensator to effectively correct gripper position deviations. In our robot design, we develop a motion control strategy that coordinates the upper and lower limbs in order to maintain the swing energy that can be transferred to the subsequent cycles. Then we propose a potential energy-based phase switching condition in the motion control strategy in order to simplify the computation process. Simulation results demonstrate that the optimized parameter for compensation effectively maintains the gripper's position relative to the ledge throughout 55 brachiation cycles. Furthermore, experiment validation shows that this posture compensation reduces deviation by one-third compared to results without compensation. This study has demonstrated a 68% improvement in energy consumption efficiency for continuous transverse brachiation compared to the previous generation, as well as a 37% improvement over transverse ricochetal brachiation locomotion.

Biomimetics as the transdisciplinary field leveraging biologically inspired solutions for technical and practical challenges has gained traction in recent decades. Despite its potential for innovation, the complexity of its process requires a deeper understanding of underlying tasks, leading to the development of various tools to aid this process. This study identified an inventory of 104 tools used in biomimetics, of which 24 have been classified as fully accessible, functional, and ready-to-use biomimetic tools. Additionally, it provides definitions and evaluation criteria for biomimetic tools, offering a structured approach to tool assessment. The 24 tools have been assessed based on ten criteria in a qualitative and quantitative analysis yielding an overview of their typology, accessibility, stage of development, and other key characteristics. Patterns of the typology development of tools over time revealed a trend towards integrating computational methods and artificial intelligence, thereby enhancing the tool's functionality and user engagement. However, gaps in tool functionality and maturity, such as the lack of tools designed to support technical processes, the absence of tools tailored for solution-based approaches, and insufficient evidence of successful tool application, highlight areas for future research. The study results underscore the need for empirical validation of tools, and research into the effectiveness of holistic tools covering multiple stages of the biomimetic process. By addressing these gaps and leveraging existing strengths, the field of biomimetics can continue to advance, providing innovative solutions inspired by biological models.

Among the components of a humanoid robot, a humanoid torso plays a vital role in supporting a humanoid robot to complete the desired motions. In this paper, a new LARMbot torso is developed to obtain better working performance based on biological features. By analyzing the anatomy of a human torso and spine, a parallel cable-driven mechanism is proposed to actuate the whole structure using two servo motors and two pulleys. Analysis is conducted to evaluate the properties of the proposed parallel cable-driven mechanism. A closed-loop control system is applied to control the whole LARMbot torso. Experiments are performed using the manufactured prototype in three modes to evaluate the characterizations of the proposed design. Results show that the proposed LARMbot can complete the desired motions properly, including two general human-like motions and a full rotation motion. When completing two general human-like motions, the maximum bending angle is 40 degrees. The maximum cable tension is 0.68 N, and the maximum required power is 18.3 W. In full rotation motion, the maximum bending angle is 30 degrees. The maximum cable tension is 0.75 N, and the maximum power required is 20.5 W. The proposed design is simplified and lightweight, with low energy consumption and flexible spatial motion performance that can meet the requirements of the humanoid robot torso's application in complex scenarios and commercial requirements.

Flying insects have developed two distinct adaptive strategies to minimize wing damage during collisions. One strategy includes an elastic joint at the leading edge, which is evident in wasps and beetles, while another strategy features an adaptive and deformable leading edge, as seen in bumblebees and honeybees. Inspired by the latter, a novel approach has been developed for improving collision recovery in micro aerial vehicles (MAVs) by mimicking the principle of stiffness anisotropy present in the leading edges of these insects. This study introduces a passive, flexible, folding wing design with adaptive leading edges. The impact of these adaptive folding leading edges on the flight performance of flapping-wing MAVs was systematically evaluated. Variations in lift generation and obstacle-crossing capabilities between rigid wings and adaptive deformable wings were quantified. Additionally, the mechanical stiffness of the wings was assessed to validate their functional effectiveness. The proposed mechanism was incorporated into the wings of a dual-layer flapping-wing robot, which demonstrated successful flight recovery after collision. The experimental results indicate that a robot with a 30 cm wingspan can effectively traverse a gap of 16.2 cm during flight, thereby demonstrating its enhanced ability to overcome collision challenges. These findings underscore the potential of adaptive wing designs in enhancing the resilience and performance of MAVs in dynamic environments.