Bioinspiration & Biomimetics

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.

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 25 mm in height, showcasing superior obstacle-crossing capabilities. In addition to moving straight (maximum speed: 0.41 BL s⁻¹) and turning on rigid surfaces (45° s⁻¹), the robot is capable of crawling on various complex terrains (cloth, sand, flat ground, and slope) as well as water planning. 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 in near-port areas 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. 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.

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.

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.

Human gait simulation plays a crucial role in providing insights into various aspects of locomotion, such as diagnosing injuries and impairments, assessing abnormal gait patterns, and developing assistive and rehabilitation technologies. To achieve more realistic gait simulation results, it is essential to use a comprehensive model that accurately replicates the kinematics and kinetics of human movement. Human skeletal models in OpenSim software provide anatomically accurate and anthropomorphic structures, enabling users to create personalized models that accurately replicate individual human behavior. However, these torque-driven models encounter challenges in stabilizing unactuated degree of freedom of pelvis tilt in forward dynamic simulations Adopting a bio-inspired strategy that ensures human balance with a minimized energy expenditure during walking, this paper addresses a gait controller for a torque-driven human skeletal model to achieve stable walking. The proposed controller employs a nonlinear model-based approach to calculate a balance-equivalent control torque and utilizes the hip-ankle strategy to distribute this torque across the lower-limb joints during the stance phase. To optimize the parameters of the trajectory tracking controller and the balance distribution coefficients, we developed a forward dynamic simulation interface established between MATLAB and OpenSim. The simulation results indicated that the torque-driven model achieves a natural gait, with joint torques closely aligning with the experimental data. The robustness of the bio-inspired gait controller was further evaluated by applying a range of external forces on the skeletal model. The robustness analysis demonstrated efficient balance recovery mechanism of the proposed bio-inspired gait controller in response to external disturbances.

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.

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.

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.

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.

Inspired by killer whale hunting strategies, this study presents a biomimetic algorithm for controlled subgroup fission in swarms. The swarm agents adopt the classic social force model with some practical modifications. The proposed algorithm consists of three phases: cluster selection phase via a constrained K-means algorithm, driven phase with strategic agent movement, including center pushing, coordinated oscillation, and flank pushing by specialized driven agents, and judgment phase confirming subgroup separation using the Kruskal algorithm. Simulation results confirm the algorithm’s high success rate and efficiency in subgroup division, demonstrating its potential for advancing swarm-based technologies.

Limited research exists on the 3D geometric models and as a consequence the aerodynamic characteristics of the grey-headed albatross (GHA). Despite existing methods for extracting bird wing cross-sections, few studies consider deflections due to aerodynamic pressure. With the GHA known for its exceptional flight speed and purported wing-lock mechanism, it offers a valuable subject for studying fixed-wing aerodynamics in nature. This study aims to develop and validate a numerical approach to estimate the GHA’s wing cross-section in flight. The PARSEC method is combined with a scanned 3D point cloud of a dried GHA wing to create a 3D model and analyse an averaged aerofoil section. Using a pseudo-2D computational fluid dynamics model, the study explores passive morphing of bird wings due to aerodynamic pressure. Results show that the aerofoil morphs to achieve maximum potential aerodynamic efficiency at a Reynolds number of 2×105, decreasing in camber. The maximum lift-to-drag ratio ( (CL/CD)max) increases from 3 to 44, primarily due to pressure drag reduction. However, the lack of comparison to true bird geometry in flight remains a limitation. Future research should compare the predicted morphing with actual bird specimens in flight.

Earthworm-like robots have excellent locomotion capability in confined environments. Central pattern generator (CPG) based controllers utilize the dynamics of coupled nonlinear oscillators to spontaneously generate actuation signals for all segments, which offer significant merits over conventional locomotion control strategies. There are a number of oscillators that can be exploited for CPG control, while their performance in controlling peristaltic locomotion has not been systematically evaluated. To advance the state of the art, this study comprehensively evaluates the performance of four widely used nonlinear oscillators—Hopf, Van der Pol (VDP), Matsuoka, and Kuramoto—in controlling the planar locomotion of metameric earthworm-like robots. Specifically, the amplitude and phase characteristics of the continuous control signals used by the robot for achieving rectilinear, sidewinding, and arcuate locomotion are first summarized. On this basis, the sufficient parametric conditions for the four oscillator networks to generate the corresponding control signals are derived. Using a six-segment earthworm-like robot prototype as a platform, experiments confirm that the signals output by these oscillator networks can effectively control the robot to achieve the specified planar motion. Furthermore, the effects of the output signal waveforms of different oscillator networks on locomotion trajectories and performance metrics, as well as the effects of transient dynamics on the smoothness of gait transitions when the parameters are varied, are analyzed. The results demonstrate that their applicability varies in terms of locomotion efficiency, trajectory modulation, and smooth gait transitions. The Matsuoka oscillator lacks explicit rules for parameter modulation, the VDP oscillator is advantageous in enhancing the average speed and turning efficiency, and the Hopf and Kuramoto oscillators are advantageous in terms of smooth gait transition. These findings provide valuable insights into the selection of appropriate oscillators in CPG-based controllers and lay the foundation for future CPG-based adaptive control of earthworm-like robots in complex environments.

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.

Resilience is a vital aspect of modern systems, especially in multi-agent systems, where faulted agents (agents who do not behave properly) can compromise system performance. In response to this need for resilience, we turn to biological inspiration. Eusocial insects are a subset of insects that have caste-based labor distribution and cooperative brood care. These insects face analogous challenges in maintaining and improving resilience to external threats, making them prime examples to find unique biological solutions to resilience problems. Thus, the central question of this work is: How can eusocial insect behavior be used to inspire new approaches to prevent or limit faulted agents from impacting the performance of multi-agent systems? Engineers, however, do not always have the necessary biological expertise to identify behaviors to mimic. This article seeks to fill the following identified gap in current research and resources: There is need to study the impact of biologically inspired behaviors on faulted agent resilience, but engineers may struggle to identify sources in the biological literature to translate into engineering applications. To address this question and the identified gap, we provide a guide identifying a large range of insect resilience behaviors and examples of possible implementation of these behaviors. This guide is a functional decomposition examining how eusocial insects prevent disease propagation that engineers can transfer to their systems when seeking to mitigate faulted agents. The presented functional decomposition is made of 148 identified functions across 7 levels, organized into 5 primary categories. This provides a guide for engineers to use when looking for sources of inspiration to improve system resilience. Additional discussion is also provided to offer potential implementations of these 148 functions, so as to encourage further work and usage of this work.

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.

When the beetle lands on the target, the hind wings fold regularly to form smaller wing packages and are hidden on the ventral side of the elytra due to the interaction between the elytra and abdomen. Its complex folding pattern is attributed to the flexibility of the hind wings, the super-elasticity of the folding joints, and the special geometric morphology of the veins. The corrugation and folding pattern of the hind wings can provide new insights for the design of folding anti-collision mechanisms and the improvement of aerodynamic performance of ornithopter. This paper first proposes a beetle-type ornithopter with foldable wings based on the folding mechanism and kinematic characteristics of the beetle’s hind wings. Subsequently, a series of numerical simulations were conducted on flapping wing robot to explore its flapping kinematics, folding stability, structural stiffness. Finally, the force generation of flapping wings was tested on the fabricated prototype.

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.

Skeletal muscle is the main actuator of various families of vertebrates (mammals, fish, reptiles). It displays remarkable robustness to micro-damage, that supposedly originates both from its redundant hierarchical structure and its nervous command. A bioinspired mock-up was designed and manufactured mimicking sarcomeres (micro-scale) and its series and parallel structure from fibre to muscle. First, the mechanical performances namely the force–velocity curve of the intact muscle mock-up were measured and modelled. Then, mimicking micro-damage by making some myosin heads inoperative, the mechanical performances were again measured to determine the resilience of the actuator. The mock-up is shown to be resilient: in the event of 10% damage of the mock-up, the mechanical performance of the mock-up was around 80% of the intact one. In this multi degrees of freedom actuator with hierarchical structure, the resilience is shown to be almost linear with the damage level for uniformly distributed damage (both maximal force and velocity decrease). Differently when micro-damage are clustered on a fibre, this decreases the maximal force with little effect on velocity.

Tomopterids are mesmerizing holopelagic swimmers. They use two modes of locomotion simultaneously: drag-based metachronal paddling and bodily undulation. Tomopteris has two rows of flexible, leg-like parapodia positioned on opposite sides of its body. Each row metachronally paddles out of phase to the other. Both paddling behaviors occur in concert with a lateral bodily undulation. However, when looked at independently, each mode appears in tension with the other. The direction of the undulatory wave is opposite of what one may expect for forward (FWD) swimming and appears to actively work act against the direction of swimming initiated by metachronal paddling. To investigate how these two modes of locomotion synergize to generate effective swimming, we created a self-propelled, fluid-structure interaction model of an idealized Tomopteris. We holistically explored swimming performance over a 3D mechanospace comprising parapodia length, paddling amplitude, and undulatory amplitude using a machine learning framework based on polynomial chaos expansions. Although undulatory amplitude minimally affected FWD swimming speeds, it helped mitigate the larger costs of transport that arise from either using more mechanically expensive (larger) paddling amplitudes and/or having longer parapodia.

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.