Bioinspiration & Biomimetics

Since every flight ends in a landing and every landing is a potential crash, deceleration during landing is one of the most critical flying maneuvers. Here we implement a recently-discovered insect visual-guided landing strategy in which the divergence of optical flow is regulated in a step-wise fashion onboard a quadrotor for the task of visual servoing. This approach was shown to be a powerful tool for understanding challenges encountered by visually-guided flying systems. We found that landing on a relatively small target requires mitigation of the noise with adaptive low-pass filtering, while compensation for the delays introduced by this filter requires open-loop forward accelerations to switch from divergence setpoint. Both implemented solutions are consistent with insect physiological properties. Our study evaluates the challenges of visual-based navigation for flying insects. It highlights the benefits and feasibility of the switching divergence strategy that allows for faster and safer landings in the context of robotics.

Mammal-inspired quadruped robots excel in traversing diverse terrestrial terrains but often lack aquatic mobility, limiting their effectiveness in amphibious environments. To address this challenge, an amphibious robotic dog (ARD) was developed, integrating efficient paddling gait in water with trotting capabilities on land. A canine-inspired paddling trajectory was first developed for a two-segment leg, and validated through theoretical modeling and experimental measurements of hydrodynamic forces. A waterproof ARD was then fabricated, with careful consideration of center-of-gravity and center-of-buoyancy relationships to ensure stable aquatic movement. Three distinct paddling gaits were developed and tested to evaluate the ARD's swimming speed and stability: two lateral sequence paddling gaits (LSPG) featuring 25% and 33% power phases (PP), and one trot-like paddling gait (TLPG) featuring a 50% PP. Theoretical modeling and numerical calculations were conducted to analyze the stability of different paddling gaits. Static water experiments measured gait-specific hydrodynamic forces, followed by dynamic swimming tests demonstrating that LSPG delivers superior propulsion and speed, while TLPG offers enhanced stability. The ARD achieved a maximum water speed of 0.16 m s⁻¹ (0.54 BL s⁻¹) and a land speed of 0.35 m s⁻¹ (1.2 BL s⁻¹). These findings provide theoretical and practical guidance for the development of mammal-inspired amphibious quadruped robots, particularly in structural design and paddling gait planning.

Pinnipeds, with highly sensitive whiskers, can detect instantaneous spatial hydrodynamic disturbances, crucial for tracking wakes and their sources. However, no existing engineering solution replicates this for intelligent passive flow perception. To bridge this gap, we propose a low-cost, whisker-inspired sensor designed for use in arrays for underwater sensing and tracking. The sensor integrates metal foil strain gages within a polydimethylsiloxane soft base, coupled with a 3D-printed biomimetic seal whisker model. It exhibits low self-noise in undisturbed flow and high sensitivity in wake detection, identifying flow speeds as low as 0.5 mm s⁻¹—comparable to biological whiskers (∼0.25 mm s⁻¹). The dual strain gage design, placed on adjacent perpendicular sides, allows precise measurement of whisker bending amplitude and direction. The sensor shows excellent linearity, repeatability, fatigue life, short response time and superior dynamic performance in the low-frequency range (⩽35 Hz). Despite its high performance, it is cost-effective and easy to fabricate, requiring no specialized facilities or extensive training, making it ideal for large-scale array deployment. To demonstrate its potential, we tested a nine-sensor array capable of predicting dipole source locations using an artificial neural network model. This work demonstrates the feasibility of whisker-inspired sensing for robust spatial flow perception in underwater environments.

Birds, insects, bats and fish demonstrate exceptional locomotion efficiency through adaptive flapping motions, offering a wealth of inspiration for bio-inspired propulsion systems. However, traditional research often relies on simplified motion models with limited degrees of freedom, which may not fully capture the complexity, adaptability, and efficiency of natural movement. In this study, we propose an adaptive motion optimization framework based on reinforcement learning (RL), aiming to address the aforementioned challenges. By integrating high-fidelity numerical simulations with physical models of flapping wings, the framework dynamically adjusts motion patterns in real time, guided by flow field information. Departing from conventional methods that rely on pre-designed motion assumptions, this approach uncovers non-harmonic, quasi-periodic motion patterns through iterative exploration. The system refines behaviors to enhance propulsion performance, adapt to dynamic flow conditions, and reveal biologically relevant features, such as asymmetric oscillations, adaptive rhythmic formations, and progressive fine-tuning of motion strategies. These learned motions not only align with natural flapping characteristics but also surpass traditional optimization methods by expanding the search space to include more complex and effective movement patterns. This framework demonstrates the power of RL to discover sophisticated, bio-inspired motion dynamics, offering transformative potential for understanding natural flapping mechanisms and designing efficient, versatile propulsion systems for real-world applications.

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 1.5–1100 times less external power per unit mass. The remarkable efficiency of this bio-robot enhances its performance in tasks such as underwater cave exploration.

Biomimetic research has drawn inspiration from the knowledge acquired from the diverse morphologies and specialized functions of hymenopteran ovipositors. For example, the morphology of the honeybee stinger was used to create surgical needles that reduce insertion forces, minimize tissue damage, and increase precision. Similarly, the reciprocating drilling mechanisms observed in wood-boring hymenopterans inspired the development of steerable probes for neurosurgery, offering improved control and reduced trauma during penetration. Despite these advances, the ovipositors of sawflies, which promise intricate cutting mechanisms, have remained poorly studied in biomimetics. Unlike wood-boring species, most sawflies typically cut through soft plant tissues using their saw-like ovipositors, which could inspire new designs for precise cutting and sawing devices. This review advocates the need for further research into the structure, mechanical properties and functional principles of sawfly ovipositors to fully exploit their potential in bio-inspiration. We highlight the lack of detailed mechanical studies connecting ovipositor morphology to cutting efficiency and substrate interactions. Understanding these relationships could uncover new principles for engineering applications, such as medical or industrial cutting tools.

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.

In response to the urgent issues faced by current bionic undulating fin robot propulsion mechanisms, such as low working efficiency, insufficient swimming speed, ignoring thickness parameters, and the need for further improvement in biomimetic degree, this article extends the theory of surface elements to tetrahedral elements using d'Alembert's principle, making it better suited for the research of undulating fins with thickness. By employing computational fluid dynamics simulations and comparative studies, the article examines the influence of motion parameters on the hydrodynamic performance of undulating fins that have thickness. The results are more valuable for engineering applications. Further research on the dimensional parameters of undulating fins is carried out, proposing that the design of undulating fins should follow the priority order of "width first, then length, and finally thickness." Based on this, a bionic fin with variable thickness is designed, and the optimal range of comprehensive hydrodynamic performance for the variable thickness fin is obtained.

In nature, organisms have evolved diverse grasping mechanisms to perform vital functions such as hunting and self-defence. These time-tested biological structures, including the arms of octopuses and the trunks of elephants, offer valuable inspiration for designing multimodal soft grippers that can tackle diverse tasks in various environments. Similar to their biological counterparts, these grippers must adapt to dynamic working conditions to enhance their performance. This adaptation process involves multiple factors, including grasping mechanisms, structural design, materials, and application scenarios, with biomimetic strategies offering numerous innovative examples. Despite the significant potential of bio-inspired designs, it lacks comprehensive reviews that explore how these strategies can enhance the development of multimodal soft grippers. This review seeks to address this gap by providing a systematic review of how bioinspired approaches contribute to the advancement of multimodal grippers. It focuses on coupling strategies, integration methods, performance improvements, and application scenarios. Finally, the review explores how future biomimetic insights could address current challenges and further improve the functionality of multimodal grippers.

Turbulent boundary layer separation can be problematic in many engineering applications. However, nature may have a solution in the form of flexible shark scales found on the shortfin mako which have been proven to passively bristle under reversing flow conditions and control flow separation. An investigation of how these shark scales interact with reversing flow in the near-wall regions of the boundary layer is of interest to better understand the fluid-shark scale interactions. Enlarging the geometry and constructing 3D printed models of shark skin is the best route forward to developing a bio-inspired surface for aircraft applications. Using a rotating cylinder above a flat plate in a water tunnel setup, an adverse pressure gradient was induced creating a separated region over a tripped turbulent boundary layer. Flexible and rigid 3D printed shark scales that replicate passive bristling angles of 50 degrees are constructed with crown lengths of 3.6 mm, twenty times greater than on a real shark. In this experiment, the boundary layer grows to sizes great enough that the scale of the flow is increased, making it more measurable to DPIV and allowing for models to be sized to fit within the bottom 10% of the boundary layer. Studies show that at low reversing flow velocities, the flexible scales were seen to passively move and mix momentum in the lower boundary layer.

Target detection and localization are essential capabilities for underwater vehicles to perceive and understand the underwater environment. In turbid, dark and semi-enclosed waters, such as underwater caves, acoustic and optical sensing devices face serious problems of reverberation and attenuation of the detection range, respectively. Weakly electric fish use their electric organ (EO) in the tail to produce repetitive discharges, while their electric receptors in the head and trunk detect electrical signals. This enables them to locate targets, avoid predators and facilitate hunting. In this paper, a bio-inspired active underwater electrolocation method is proposed, in which an adaptive contour-ring based target localization method is applied to provide both robust and accurate localization results for vehicles. In particular, on the basis of the efficient generation of prior contour-ring maps with high confidence and high precision, a particle swarm optimization (PSO) theory-based adaptive threshold estimation (PATE) algorithm was proposed to overcome the problem of non-uniqueness in the traditional contour ring-based method, while an electrode array pattern that integrates positioning accuracy and number of electrodes is proposed. Tank experiments have demonstrated the positioning accuracy of the proposed method.

Since every flight ends in a landing and every landing is a potential crash, deceleration during landing is one of the most critical flying maneuvers. Here we implement a recently-discovered insect visual-guided landing strategy in which the divergence of optical flow is regulated in a step-wise fashion onboard a quadrotor for the task of visual servoing. This approach was shown to be a powerful tool for understanding challenges encountered by visually-guided flying systems. We found that landing on a relatively small target requires mitigation of the noise with adaptive low-pass filtering, while compensation for the delays introduced by this filter requires open-loop forward accelerations to switch from divergence setpoint. Both implemented solutions are consistent with insect physiological properties. Our study evaluates the challenges of visual-based navigation for flying insects. It highlights the benefits and feasibility of the switching divergence strategy that allows for faster and safer landings in the context of robotics.

Invertebrate research ethics has largely been ignored compared to the consideration of higher order animals, but more recent focus has questioned this trend. Using the robotic control of Aurelia aurita as a case study, we examine ethical considerations in invertebrate work and provide recommendations for future guidelines. We also analyze these issues for prior bioethics cases, such as cyborg insects and the 'microslavery' of microbes. However, biohybrid robotic jellyfish pose further ethical questions regarding potential ecological consequences as ocean monitoring tools, including the impact of electronic waste in the ocean. After in-depth evaluations, we recommend that publishers require brief ethical statements for invertebrate research, and we delineate the need for invertebrate nociception studies to revise or validate current standards. These actions provide a stronger basis for the ethical study of invertebrates, with implications for individual, species-wide, and ecological impacts, as well as for studies in science, engineering, and philosophy.

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 (C. 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.

Biomimetic research has drawn inspiration from the knowledge acquired from the diverse morphologies and specialized functions of hymenopteran ovipositors. For example, the morphology of the honeybee stinger was used to create surgical needles that reduce insertion forces, minimize tissue damage, and increase precision. Similarly, the reciprocating drilling mechanisms observed in wood-boring hymenopterans inspired the development of steerable probes for neurosurgery, offering improved control and reduced trauma during penetration. Despite these advances, the ovipositors of sawflies, which promise intricate cutting mechanisms, have remained poorly studied in biomimetics. Unlike wood-boring species, most sawflies typically cut through soft plant tissues using their saw-like ovipositors, which could inspire new designs for precise cutting and sawing devices. This review advocates the need for further research into the structure, mechanical properties and functional principles of sawfly ovipositors to fully exploit their potential in bio-inspiration. We highlight the lack of detailed mechanical studies connecting ovipositor morphology to cutting efficiency and substrate interactions. Understanding these relationships could uncover new principles for engineering applications, such as medical or industrial cutting tools.

Bio-inspired robot controllers are becoming more complex as we strive to make them more robust to, and flexible in, noisy, real-world environments. A stable heteroclinic network (SHN) is a dynamical system that produces cyclical state transitions using noisy input. SHN-based robot controllers enable sensory input to be integrated at the phase-space level of the controller, thus simplifying sensor-integrated, robot control methods. In this work, we investigate the mechanism that drives branching state trajectories in SHNs. We liken the branching state trajectories to decision-splits imposed into the system, which opens the door for more sophisticated controls–all driven by sensory input. This work provides guidelines to systematically define an SHN topology, and increase the rate at which desired decision states in the topology are chosen. Ultimately, we are able to control the rate at which desired decision states activate for input signal-to-noise ratios across six orders of magnitude.

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 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 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.

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.

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.

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.