Biomimetic Robot Research Articles

Influence of hydrofoil motion patterns on the hydrodynamic performance of undulating fin for biomimetic underwater robots

The undulatory propulsion of aquatic organisms like the black ghost knifefish offers high manoeuvrability and motion stability, making it a promising model for developing advanced biomimetic underwater robots. However, these robots are frequently hindered by limitations in speed and propulsion efficiency. Inspired by the energy benefits observed in fish schooling, this study introduces a cooperative propulsion system integrating the hydrofoil with the undulating fin to enhance propulsion performance through an investigation of their interaction across various motion patterns. Specifically, we investigate the effects of static, pitching, heaving, and their combination (pitching + heaving) of the hydrofoil on the hydrodynamic performance of the undulating fin. Our results indicate that a static hydrofoil slightly increases the fin's average thrust, while pure pitching marginally reduces it. The high-speed vortices generated by the hydrofoil during pure heaving significantly suppress the fin's thrust. In contrast, the combined motion of pitching and heaving substantially enhances propulsion performance. Thus, the combined motion of the hydrofoil can better enhance the hydrodynamic performance of the undulatory propulsion robot. This study provides a theoretical foundation for the optimized design of high-speed and stable undulating fin propulsion systems, offering valuable insights for developing underwater robots with improved operational capabilities.

Modeling and precise tracking control of spatial bending pneumatic soft actuators

In recent years, a variety of pneumatic soft actuators (PSAs) have been proposed due to the development of soft robots in biomimetic robots, medical devices, etc. At the same time, the modeling and control of PSAs remains an open question. In this paper, a spatial bending pneumatic soft actuator (SBPSA) modeling method based on the Prandtl–Ishlinskii (PI) model is proposed, and the inverse model is designed to compensate for hysteresis nonlinearity. Furthermore, an adaptive feedback controller combined with a hysteresis compensator is proposed for the precise control and tracking of SBPSAs. Finally, an experimental platform is built, and experimental results demonstrate the effectiveness of the proposed method for precise tracking.

Driving-sensing integrated magnetic soft robots via laser thermal printing

The integration of driving and sensing can effectively promote the intelligence and miniaturization of magnetic soft robots. A highly adaptable, efficient, and flexible method for constructing functional structures of composites is crucial for magnetic soft robots with sensing capabilities. In this work, a novel laser thermal printing (LTP) process is proposed to flexibly and efficiently prepare thermosetting composite based magnetic soft robots with integrated sensing capabilities. By cleverly utilizing the laser photothermal effect, CNTs (Carbon Nanotubes) photothermal absorbers and PDMS (Polydimethylsiloxane) thermosetting properties, LTP process effectively achieves rapid thermoforming of thermosetting resin PDMS. On this basis, we present the first-ever application of the process for the synthesis of butterfly-shaped, inchworm-shaped and claw-shaped magnetic soft robots. Due to NdFeB magnetic microparticles within PDMS matrix and a CNTs conductive layer on PDMS surface, the obtained biomimetic robots achieve seamless integration of driving and sensing capabilities. In applications such as circuit repair and object grasping, real-time and in-situ changes in sensing signals provide feedback on the posture changes and motion processes of these robots, highlighting their intelligent features. Therefore, LTP process provides a novel approach for the efficient fabrication of miniaturized, intelligent soft robots.

Animation, Automata, Biomimesis

The animation-effect of the movement-image constitutes not only a form of life but also a machinic analogue for Husserl's and Kant's accounts of temporality, engendering what Bernard Stiegler calls ‘a cinematography of consciousness’. If autonomous movement is the hallmark of the living being as well as the inanimate mechanism, the movement-image likewise subtends scenes of human and artificial intelligence. Pairing a cybernetic reading of Lacan's mirror stage essay with reflections on the self-recognition dance of Machina Speculatrix (an early example of a biomimetic robot), this essay considers how exosomatic feedback loops enable a kind of ipseity for machinic life as well as the human being as technical being. Despite adopting Derrida's ideas of originary prostheticity and automaticity, rendering living beings as always-already machinic life, Stiegler sets arche-cinema against arche-writing.

Human short-latency reflexes show precise short-term gain adaptation after prior motion.

The central nervous system adapts the gain of short-latency reflex loops to changing conditions. Experiments on biomimetic robots showed that reflex modulation could substantially increase energy efficiency and stability of periodic motions if, unlike known mechanisms, the reflex modulation both acted precisely on the muscles involved and lasted after the motion. This study tests the presence of such a mechanism by having participants repeatedly rotate either their right elbow or shoulder joint, before perturbing either joint. The results demonstrate a mechanism that modulates short-latency reflex gains after prior motion with joint-specific precision. Enhanced gains were observed hundreds of milliseconds after movement cessation, a time scale well-suited to quickly adapt overall periodic motion cycles. A serotonin antagonist significantly decreased these post-movement gains diffusely across joints. But blocking serotonin did not affect the joint-specificity of the gain scaling more than a placebo, suggesting that serotonin sets the overall reflex gain across joints after movement by an effect that is modulated in a joint-specific manner by an unidentified neural circuit. These results confirm the existence of a new, joint-specific, fast, persistent adaptation of short-latency reflex loops induced by motion in human arms.

Soft robots and soft bodies: biological insights into the structure and function of fluidic soft robots.

Over the last two decades, robotics engineering has witnessed rapid growth in the exploration and development of soft robots. Soft robots are made of deformable materials with mechanical properties or other features that resemble biological structures. These robots are often inspired by living organisms or mimic their locomotion, such as crawling and swimming. This paper aims to assist researchers in robotics and engineering to design soft robots incorporating or inspired by biological systems with a more informed perspective on biological models and functions. We address the characteristics of fluidic soft robots inspired by or mimicking biological examples, establish a method to categorize soft robots from a functional biological perspective, and provide a wider range of organisms to inspire the development of soft robotics. The actuation mechanisms in bioinspired and biomimetic soft robotics would benefit from a clearer understanding of the underlying principles, organization, and function of biological structures.

Agile robotic fish based on direct drive of continuum body

Fish-like agile movements, such as fast swimming and rapid turning, are essential for biomimetic underwater robots but challenging to achieve simultaneously. We present a self-contained robotic fish capable of swimming at a speed of 6.3 body length per second and pivot turning at an angular speed of 1450° per second. These fast motions, comparable to real fish, are realized by directly oscillating a flexible body using an electromagnetic motor, eliminating the need for transmission parts and simplifying the structure. This direct-drive (DD) method improves mechanical robustness and generates fish-like deformations and subsequent rapid swimming. The Strouhal and swimming numbers of the robot match typical values observed in nature. Moreover, the observed frequency peaks in swimming are similar to computed values using a model, which guides the design of the robot. These results illustrate the DD method as a promising framework for the creation of highly versatile biomimetic underwater robots.

Harnessing Deep Learning of Point Clouds for Morphology Mimicking of Universal 3D Shape‐Morphing Devices

Shape‐morphing devices, a crucial branch in soft robotics, hold significant application value in areas like human–machine interfaces, biomimetic robotics, and tools for biological systems. To achieve 3D programmable shape morphing (PSM), the deployment of array‐based actuators is essential. However, a critical knowledge gap in 3D PSM is controlling the complex systems formed by these soft actuator arrays to mimic the morphology of the target shapes. This study, for the first time, represents the configuration of shape‐morphing devices using point cloud data and employing deep learning to map these configurations to control inputs. Shape Morphing Net (SMNet), a method that realizes the regression from point cloud to high‐dimensional control input vectors, is proposed. It has been applied to 3D PSM devices with three different actuator mechanisms, demonstrating its universal applicability to inversely reproduce the target shapes. Further, applied to previous 2D PSM devices, SMNet significantly enhances control precision from 82.23% to 97.68%. In the demonstrations of morphology mimicking, 3D PSM devices successfully replicate arbitrary target shapes obtained either through 3D scanning of physical objects or via 3D modeling software. The results show that within the deformable range of 3D PSM devices, accurate reproduction of the desired shapes is achievable.

A non-contact thermocapillary driving system at the gas-liquid interface

Non-contact driving technology is widely utilized in various fields due to its advantages of being non-contact, wear-free, and low noise. Thermocapillary driving is an effective approach for non-contact driving at gas-liquid interfaces. When a temperature gradient exists at the gas-liquid interface, it generates a surface tension gradient, which drives the movement of micro-objects at the interface. This research proposes a system that utilizes an array of thermoelectric coolers (TECs) as a heat source, which changes the local temperature at the gas-liquid interface and generates surface tension gradients for driving the movement of interface objects. Experimental results demonstrate that foam particles with a diameter of 0.5 mm can achieve a maximum moving speed of 2.1 mm/s. Furthermore, the system can control multiple micro-objects at the gas-liquid interface for self-assembly. We have also developed a miniature biomimetic water strider robot, this system can drive the robot to perform linear and turning movements at the gas-liquid interface. This system provides a novel approach for non-contact driving of gas-liquid interfaces.

A biomimetic fruit fly robot for studying the neuromechanics of legged locomotion

For decades, the field of biologically inspired robotics has leveraged insights from animal locomotion to improve the walking ability of legged robots. Recently, 'biomimetic' robots have been developed to model how specific animals walk. By prioritizing biological accuracy to the target organism rather than the application of general principles from biology, these robots can be used to develop detailed biological hypotheses for animal experiments, ultimately improving our understanding of the biological control of legs while improving technical solutions. In this work, we report the development and validation of the robot Drosophibot II, a meso-scale robotic model of an adult fruit fly,Drosophila melanogaster. This robot is novel for its close attention to the kinematics and dynamics ofDrosophila, an increasingly important model of legged locomotion. Each leg's proportions and degrees of freedom have been modeled afterDrosophila3D pose estimation data. We developed a program to automatically solve the inverse kinematics necessary for walking and solve the inverse dynamics necessary for mechatronic design. By applying this solver to a fly-scale body structure, we demonstrate that the robot's dynamics fit those modeled for the fly. We validate the robot's ability to walk forward and backward via open-loop straight line walking with biologically inspired foot trajectories. This robot will be used to test biologically inspired walking controllers informed by the morphology and dynamics of the insect nervous system, which will increase our understanding of how the nervous system controls legged locomotion.

Bioinspired Artificial Intelligent Nociceptive Alarm System Based on Fibrous Biomemristors.

With the advancement of modern medical and brain-computer interface devices, flexible artificial nociceptors with tactile perception hold significant scientific importance and exhibit great potential in the fields of wearable electronic devices and biomimetic robots. Here, a bioinspired artificial intelligent nociceptive alarm system integrating sensing monitoring and transmission functions is constructed using a silk fibroin (SF) fibrous memristor. This memristor demonstrates high stability, low operating power, and the capability to simulate synaptic plasticity. As a result, an artificial pressure nociceptor based on the SF fibrous memristor can detect both fast and chronic pain and provide a timely alarm in the event of a fall or prolonged immobility of the carrier. Further, an array of artificial pressure nociceptors not only monitors the pressure distribution across various parts of the carrier but also provides direct feedback on the extent of long-term pressure to the carrier. This work holds significant implications for medical support in biological carriers or targeted maintenance of electronic carriers.

Self-Localization of a Biomimetic Robotic Shark Using Tightly Coupled Visual-Acoustic Fusion

Self-Localization of a Biomimetic Robotic Shark Using Tightly Coupled Visual-Acoustic Fusion

Evaluating Stacked Dielectric Elastomer Actuators as Soft Motor Units for Forming Artificial Muscles in Biomimetic Rehabilitation Robots

The recent commercial availability of stacked dielectric elastomer actuators (SDEAs) has unlocked new opportunities for their application as “artificial skeletal muscles” in rehabilitation robots and powered exoskeletons. Composed of multiple layers of thin, elastic capacitors, these actuators present a lightweight, soft, and acoustically noiseless alternative to traditional DC motor actuators commonly used in rehabilitation robotics, thereby enhancing the natural feel of such systems. Building on our previous research, this study aimed to evaluate the most recent version of commercial SDEAs to assess their potential for mechanizing rehabilitation robots. We quantified the stress and strain behavior and stiffness of these actuators in both single and 1 × 3 configurations (with three SDEAs connected in series). The actuators demonstrated the capability to generate up to 25 N of force and 115 KPa, a value surpassing human biceps, with a longitudinal strain measured at about 11%. The significant increase in force generation from 10 N in the previous version to 25 N and displacement from 3.3% to 11% substantially enhances the applicability of this actuator in rehabilitation robotics. SDEAs’ high force generation capability, combined with their strain and stress characteristics comparable to that of human biological muscles, make them ideal alternative actuators for biomimetic robots and applications where actuators must operate in the vicinity of the human body.

Comparison Study of Hydrodynamic Characteristics in Different Swimming Modes of Carassius auratus

This study utilized particle image velocimetry (PIV) to analyze the kinematic and hydrodynamic characteristics of juvenile goldfish across three swimming modes: forward swimming, burst and coast, and turning. The results demonstrated that C-shaped turning exhibited the highest speed, enabling rapid and agile maneuvers for predator evasion. Meanwhile, forward swimming was optimal for sustained locomotion, and burst-and-coast swimming was suited for predatory behaviors. A vorticity analysis revealed that vorticity around the tail fin was the primary source of propulsive force, corroborating the correlation between vorticity magnitude and propulsion found in previous research. The findings emphasize the crucial role of the tail fin in swimming efficiency and performance. Future research should integrate ethology, biomechanics, and physiology to deepen the understanding of fish locomotion, potentially informing the design of efficient biomimetic underwater robots and contributing to fish conservation efforts.

2-dimensional impact-damping electrostatic actuators with elastomer-enhanced auxetic structure

Biomimetic robots yearn for compliant actuators that are comparable to biological muscle in both functions and structural properties. For that, electrostatic actuators have been developed to imitate bio-muscle in features of fast response, high power, energy-efficiency, etc. However, those actuators typically lack impact damping performance, making them vulnerable and unstable in real applications. Here, we present auxetic electrostatic actuators that address this issue and demonstrate muscle-like performance by using elastomer-enhanced auxetics and electrostatic zipping mechanism. The proposed actuators contract linearly on applied voltage, producing large actuation strength (15 N) and contraction ratio (59%). Fabricated from readily available materials, our prototypes can quickly attenuate vibrations caused by impacts and absorb shock energy in 0.3 s. Furthermore, leveraging their 2-dimensional working mode and self-locking mechanism, a stiffness-changing muscle for a robotic arm and an active tensegrity device exemplify the potential applications of auxetic electrostatic actuators to a wide range of bionic robots.

Brain-inspired biomimetic robot control: a review.

Complex robotic systems, such as humanoid robot hands, soft robots, and walking robots, pose a challenging control problem due to their high dimensionality and heavy non-linearities. Conventional model-based feedback controllers demonstrate robustness and stability but struggle to cope with the escalating system design and tuning complexity accompanying larger dimensions. In contrast, data-driven methods such as artificial neural networks excel at representing high-dimensional data but lack robustness, generalization, and real-time adaptiveness. In response to these challenges, researchers are directing their focus to biological paradigms, drawing inspiration from the remarkable control capabilities inherent in the human body. This has motivated the exploration of new control methods aimed at closely emulating the motor functions of the brain given the current insights in neuroscience. Recent investigation into these Brain-Inspired control techniques have yielded promising results, notably in tasks involving trajectory tracking and robot locomotion. This paper presents a comprehensive review of the foremost trends in biomimetic brain-inspired control methods to tackle the intricacies associated with controlling complex robotic systems.

Regulating the microstructure and hydrophilicity of cellulose nanofibers using taurine and the application in humidity sensor and actuator

Exploring the interrelationships between microstructure, hydrophilicity, humidity response, and material stability through molecular structure design and low-cost preparation, and manufacturing sensing and driving materials with a perfect balance between structures and properties is crucial for biomimetic robots and intelligent devices. Herein, inspired by the capillary phenomenon, the cellulose nanofiber (CNF) was grafted by using taurine to form the “micro cilia” microstructure on its surface (CNF-TAU). By controlling the cilia density and symmetry, the hydrophilicity of the materials was adjusted, and the water was allowed to quickly separate from the inside of the materials, which led to improving the humidity sensitivity and stability of materials. Concretely, compared with CNF, the puncture load, tearing strength, and elongation at break of the CNF-TAU-1.0 were improved by 11.95 times, 2.16 times, and 15.6 %, respectively, and excellent tensile strength was presented. Moreover, the hydrophilicity of CNF-TAU was first weakened and then enhanced with TAU content increasing. At last, the CNF-TAU-1.0 (WCA 55.43°) was selected and blended with single-layer graphene oxide (GO) to prepare CNF-TAU/GO composite films by vacuum filtration. The results indicated that the composite film had excellent mechanical (room and high humidity), humidity responsiveness, and humidity gradient-driven properties. In detail, the CNF-TAU/GO-10 % composite film had the generated stable induced voltage (68.4 mV), the fast response/recovery time (0.3 s/0.9 s), the large max. bending angle (178.4°), and the drive cycle stability (1000 cycles). Moreover, the composite film could be applied to produce biomimetic soft robots, such as human fingers and butterfly-shaped robots.

Cellulose nanofibers-based composite film with broadening MXene layer spacing and rapid moisture separation for humidity sensing and humidity actuators

Based on the basic idea of expanding the interlayer spacing of MXene, utilizing the effect of gallic acid-modified cellulose nanofibers for rapid moisture separation, the flexible sensing and driving composite film with a perfect balance among humidity signal response and mechanical properties was prepared. Inspired by the stacking of autumn fallen leaves, the cellulose nanofibers-based composite films were formed by self-assembly under vacuum filtration of blending gallic acid-modified cellulose nanofibers with MXene. The enhanced mechanical properties (tensile strength 131.1 MPa, puncture load 0.88 N, tearing strength 165.55 N/mm, and elongation at break 16.14 %), humidity sensing (the stable induced voltage 63.7 mV and response/recovery time 3.2/5.1 s), and humidity driving (154.7° bending angle) properties were observed. The synergistic effect of hydrogen bonds, the “pinning effect” arising from the side chains, and the hierarchical layered microstructure contributed to the enhanced performance. This work exemplifies the application of green natural product for preparing intelligent sensing, wearable devices, and biomimetic robots.

Implementing dog-like quadruped robot turning motion based on key movement joints extraction

For biomimetic robots to be used in the real world, it is very important to have animal-like turning motion. Excellent turning ability can help quadruped robots navigate more complex obstacle terrain. To solve this problem, we conducted the corresponding study by collecting multiple sets of data on different movements of Marinua dogs. First, we extracted the key movement joints of dogs and captured the motion trajectories of the key joints by a reduced order model. Then, on the basis of systematic analysis and mathematical modeling of the experimental dog’s turning motion, we propose an N-step turning strategy to enable the quadruped robot to realize a wide range of multi-angle movements. Meanwhile, based on the extracted joint trajectory and considering the influence of the actual turning speed, radius and stability of the quadruped robot, the more reasonable biomimetic turning trajectory is obtained through optimization. In terms of motion control, we propose a virtual spine control method to realize turning motion, and plan the foothold adjustment according to different speeds. Finally, experiments show that the proposed method can effectively realize multi-angle turning and U-turn and O-circle turning motion of quadruped robot, which proves the effectiveness of the proposed method. At the same time, the biomimetic turning control method proposed in this paper can be easily extended to other biomimetic robot movements inspired by other organisms.

Ionic fuel-powered hydrogel actuators for soft robotics

HypothesisHydrogel actuators powered by chemical fuels are pivotal in autonomous soft robotics. Nevertheless, chemical waste accumulation caused by chemical fuels hampers the development of programmable and reusable hydrogel actuating systems. We propose the concept of ionic fuel-powered soft robotics which are constructed by programmable salt-responsive actuators and use waste-free ionic fuels. ExperimentsHerein, soft hydrogel actuators were developed by orchestrating the Janus bilayer hydrogels’ capacity for swelling and shrinking. Decomposable and easily removable ionic fuels were applied to power the actuators. Swelling tests were used to evaluate the deformability of the hydrogels. Tensile tests were performed to investigate the modulus of the hydrogels. The bonded interface composed of the interpenetrating polymer chains from both hydrogel layers bilayer was evidenced by the optical microscopy and scanning electron microscopy. The ionic conductivities of solutions were determined by a conductivity meter. Furthermore, a range of biomimetic soft robots with various shapes and asymmetrical structures have been designed and fabricated to execute complex functions. FindingsThe programmable actuators powered by ionic fuel exhibit adjustable bending orientations, amplitudes, and durations, along with consistent cyclic actuations enabled by replenishment of the fuel without noticeable loss in performance. Many life-like programmable soft robotic systems were designed, indicating spatiotemporally controllable functions.