Search Results (308)

Biomimetic quadruped robots, inspired by the musculoskeletal systems of animals, employ pneumatic artificial muscles (PAMs) as compliant actuators to achieve flexible, efficient, and adaptive locomotion. This study focuses on a pneumatic artificial muscle (PAM)-driven biomimetic leg joints system. First, its kinematic and dynamic models are established. Next, to address the challenges posed by the strong nonlinearities and complex time-varying uncertainties inherent in PAMs, an adaptive robust control algorithm is proposed by employing the Udwadia controller. Rigorous theoretical analysis of the adaptive robust control algorithm is verified via the Lyapunov stability method. Finally, numerical simulations and hardware experiments are conducted on the PAM-driven biomimetic leg joints system under desired trajectories, where the adaptive robust control algorithm is systematically compared with three conventional control algorithm to evaluate its control performance. The experimental results show that the proposed controller achieves a maximum tracking error of within 0.05 rad for the hip joint and within 0.1 rad, highlighting its strong potential for practical deployment in real-world environments. Full article

To enhance the flexibility and adaptability of underwater robots in complex environments, this paper designs an octopus-inspired soft underwater robot capable of both bipedal walking and multi-arm swimming. The robot features a rigid–flexible coupling structure consisting of a head module and eight rope-driven soft tentacles and integrates buoyancy adjustment and center-of-gravity balancing systems to achieve stable posture control in both motion modes. Based on the octopus’s bipedal walking and multi-arm swimming mechanisms, this study formulates gait generation strategies for each mode. In walking mode, the robot achieves underwater linear movement, turning, and in-place rotation through coordinated tentacle actuation; in swimming mode, flexible three-dimensional propulsion is realized via synchronous undulatory gaits. Experimental results demonstrate the robot’s peak thrust of 14.1 N, average swimming speed of 8.6 cm/s, and maximum speed of 15.1 cm/s, validating the effectiveness of the proposed structure and motion control strategies. This research platform offers a promising solution for adaptive movement and exploration in unstructured underwater environments. Full article

This study outlines the design and evaluation of a biomimetic robotic hand tailored for Human–Robot Interaction (HRI), focusing on improvements in tactile fidelity driven by material choice. Thermoplastic polyurethane (TPU) was selected over polylactic acid (PLA) based on its reported elastomeric characteristics and mechanical compliance described in prior literature. Rather than directly matching human skin properties, TPU was perceived as providing a softer and more comfortable tactile interaction compared to rigid PLA. The robotic hand was anatomically reconstructed from an open-source model and integrated with AX-12A and MG90S actuators to simplify wiring and enhance motion precision. A custom PCB, built around an ATmega2560 microcontroller, enables real-time communication with ROS-based upper-level control systems. Angular displacement analysis of repeated gesture motions confirmed the high repeatability and consistency of the system. A repeated-measures user study involving 47 participants was conducted to compare the PLA- and TPU-based prototypes during interactive tasks such as handshakes and gesture commands. The TPU hand received significantly higher ratings in tactile realism, grip satisfaction, and perceived responsiveness (p < 0.05). Qualitative feedback further supported its superior emotional acceptance and comfort. These findings indicate that incorporating TPU in robotic hand design not only enhances mechanical performance but also plays a vital role in promoting emotionally engaging and natural human–robot interactions, making it a promising approach for affective HRI applications. Full article

Space exploration is a major global focus, advancing knowledge and exploiting new resources beyond Earth. Bioinspired design—drawing principles from nature—offers systematic pathways to increase the capability and intelligence of space robots. Prior reviews have emphasized on-orbit manipulators or lunar rovers, while a comprehensive treatment across application domains has been limited. This review synthesizes bioinspired capability and intelligence for space exploration under varied environmental constraints. We highlight four domains: adhesion and grasping for on-orbit servicing; terrain-adaptive mobility on granular and rocky surfaces; exploration intelligence that couples animal-like sensing with decision strategies; and design methodologies for translating biological functions into robotic implementations. Representative applications include gecko-like dry adhesives for debris capture, beetle-inspired climbers for truss operations, sand-moving quadrupeds and mole-inspired burrowers for granular regolith access, and insect flapping-wing robots for flight under Martian conditions. By linking biological analogues to quantitative performance metrics, this review highlights how bioinspired strategies can significantly improve on-orbit inspection, planetary mobility, subsurface access, and autonomous decision-making. Framed by capability and intelligence, bioinspired approaches reveal how biological analogues translate into tangible performance gains for on-orbit inspection, servicing, and long-range planetary exploration. Full article

To address the path planning challenges for land–air amphibious biomimetic robots in unstructured environments, this study proposes a global path planning algorithm based on an Improved Proximal Policy Optimization (IPPO) framework. Unlike traditional single-domain navigation, amphibious robots face significant kinematic discontinuities when switching between terrestrial and aerial modes. To mitigate this, we integrate a Gated Recurrent Unit (GRU) module into the policy network, enabling the agent to capture temporal dependencies and make smoother decisions during mode transitions. Furthermore, to enhance exploration efficiency and stability, we replace the standard Gaussian noise with Ornstein–Uhlenbeck (OU) noise, which generates temporally correlated actions aligned with the robot’s physical inertia. Additionally, a Multi-Head Self-Attention mechanism is introduced to the value network, allowing the agent to dynamically prioritize critical environmental features—such as narrow obstacles—over irrelevant background noise. The simulation results demonstrate that the proposed IPPO algorithm significantly outperforms standard PPO baselines, achieving higher convergence speed, improved path smoothness, and greater success rates in complex amphibious scenarios. Full article

We presented a biomimetic approach to designing robot-to-human handover of objects in a collaborative assembly task. We developed a human–robot hybrid cell where a human and a robot collaborated with each other to perform the assembly operations of a product in a flexible manufacturing setup. Firstly, we investigated human psychology and biomechanics (kinetics and kinematics) for human-to-robot handover of an object in the human–robot collaborative set-up in three separate experimental conditions: (i) human possessed high trust in the robot, (ii) human possessed moderate trust in the robot, and (iii) human possessed low trust in the robot. The results showed that human psychology was significantly impacted by human trust in the robot, which also impacted the biomechanics of human-to-robot handover, i.e., human hand movement slowed down, the angle between human hand and robot arm increased (formed a braced handover configuration), and human grip forces increased if human trust in the robot decreased, and vice versa. Secondly, being inspired by those empirical results related to human psychology and biomechanics, we proposed a novel robot-to-human object handover mechanism (strategy). According to the novel handover mechanism, the robot varied its handover configurations and motions through kinematic redundancy with the aim of reducing potential impulse forces on the human body through the object during the handover when robot trust in the human was low. We implemented the proposed robot-to-human handover mechanism in the human–robot collaborative assembly task in the hybrid cell. The experimental evaluation results showed significant improvements in human–robot interaction (HRI) in terms of transparency, naturalness, engagement, cooperation, cognitive workload, and human trust in the robot, and in overall performance in terms of handover safety, handover success rate, and assembly efficiency. The results can help design and develop human–robot handover mechanisms for human–robot collaborative tasks in various applications such as industrial manufacturing and manipulation, medical surgery, warehouse, transport, logistics, construction, machine shops, goods delivery, etc. Full article

Stroke is a leading cause of disability, often resulting in motor, cognitive, and language deficits, with significant impact on upper-limb function. Robotic therapy (RT) has emerged as an effective strategy, providing intensive, repetitive, and adaptable practice to optimize functional recovery. This pilot study aimed to describe and evaluate the effects of robotic rehabilitation as a complement to conventional therapy, using a biomimetic activities-of-daily-living (ADL)-based protocol, on upper-limb function in post-stroke patients. Three participants (aged 30–80 years) undergoing occupational and/or physiotherapy received individualized robotic training with a lightweight cable-driven upper-limb exoskeleton, m-FLEX™, twice a week for ten weeks (30 min per session). Movements were designed to mimic natural upper-limb actions, including elbow flexion-extension, forearm pronation-supination, tripod pinch, and functional tasks such as grasping a cup. Assessments included the Fugl-Meyer (FM) scale, the Functional Independence Measure (FIM), and device satisfaction, performed at baseline, mid-intervention, and post-intervention. Descriptive analysis of the tabulated data revealed improvements in range of motion and functional outcomes. These findings suggest that biomimetic protocol of robotic rehabilitation, when combined with conventional therapy, can enhance motor and functional recovery in post-stroke patients. Full article

Unmanned underwater vehicles (UUVs) capable of agile, high-speed maneuvering in complex environments require propulsion systems that can dynamically modulate three-dimensional forces. The California sea lion (Zalophus californianus) provides an exceptional biological model, using its foreflippers to achieve rapid turns and powerful propulsion. However, the specific kinematic mechanisms that govern instantaneous force generation from its powerful foreflippers remain poorly quantified. This study experimentally characterizes the time-varying thrust and lift produced by a bio-robotic sea lion foreflipper to determine how flipper twist, sweep, and phase overlap modulate propulsive forces. A three-degree-of-freedom bio-robotic flipper with a simplified, low-aspect-ratio planform and single compliant hinge was tested in a circulating flow tank, executing parameterized power and paddle strokes in both isolated and combined-phase trials. The time-resolved force data reveal that the propulsive stroke functions as a tunable hybrid system. The power phase acts as a force-vectoring mechanism, where the flipper’s twist angle reorients the resultant vector: thrust is maximized in a broad, robust range peaking near 45°, while lift increases monotonically to 90°. The paddle phase operates as a flow-insensitive, geometrically driven thruster, where twist angle (0° optimal) regulates thrust by altering the presented surface area. In the full stroke, a temporal-phase overlap governs thrust augmentation, while the power-phase twist provides robust steering control. Within the tested inertial flow regime (Re ≈ 10⁴–10⁵), this control map is highly consistent with propulsion dominated by geometric momentum redirection and impulse timing, rather than circulation-based lift. These findings establish a practical, experimentally derived control map linking kinematic inputs to propulsive force vectors, providing a foundation for the design and control of agile, bio-inspired underwater vehicles. Full article

Reversible adhesives enable temporary yet robust bonding between surfaces, allowing controlled detachment without structural or interfacial damage. This capability is gaining increasing recognition as a crucial requirement for sustainable technologies, where repairability, reusability, and minimal waste are key objectives. Among the diverse strategies explored for reversible adhesion (including supramolecular assemblies, bioinspired dry adhesives, and stimuli-responsive polymers), hydrogel-based systems have emerged as particularly versatile candidates due to their tunable mechanics, elasticity, and intrinsic biocompatibility. Recent studies highlight the use of renewable or biodegradable polymers to develop sustainable, water-rich hydrogel networks with controllable adhesive properties, minimizing environmental impact while maintaining performance. Despite these advances, significant challenges still hinder full implementation: biopolymer-based systems such as chitosan or starch often exhibit strong but poorly controllable adhesion, compromising reversibility and reusability. This review provides a comprehensive overview of strategies for developing hydrogel-based reversible adhesives, focusing on sustainable material selection, molecular design principles, and the underlying mechanisms of bonding and debonding. Furthermore, characterization methodologies, from conventional mechanical testing to surface-sensitive and dynamic techniques, are discussed in detail to establish structure–property–function relationships. Finally, emerging directions and application opportunities are outlined, offering a framework for the rational design of next-generation, sustainable adhesive systems. Full article

The development of human-robot interfaces that support daily social interaction requires biomimetic innovation inspired by the sensory receptors of the five human senses (tactile, olfactory, gustatory, auditory, and visual) and employing soft materials to enable natural multimodal sensing. The receptors have a structure formulated by variegated shapes; therefore, the morphological mimicry of the structure is critical. We proposed a spring-like structure which morphologically mimics the roll-type structure of the Meissner corpuscle, whose haptic performance in various dynamic motions has been demonstrated in another study. This study demonstrated the gustatory performance by using the roll-type Meissner corpuscle. The gustatory iontronic mechanism was analyzed using electrochemical impedance spectroscopy with an inductance-capacitance-resistance meter to determine the equivalent electric circuit and current-voltage characteristics with a potentiostat, in relation to the hydrogen concentration (pH) and the oxidation-reduction potential. In addition, thermo-sensitivity and tactile responses to shearing and contact were evaluated, since gustation on the tongue operates under thermal and concave-convex body conditions. Based on the established properties, the roll-type Meissner corpuscle sensor enables the iontronic behavior to provide versatile multimodal sensitivity among the five senses. The different condition of the application of the electric field in the production of two-types of A and B Meissner corpuscle sensors induces distinctive features, which include tactility for the dynamic motions (for type A) or gustation (for type B). Full article

Highly sensitive bioinspired cutaneous receptors are essential for realistic human-robot interaction. This study presents a biomimetic tactile sensor morphologically modeled after the Meissner corpuscle, designed for high dynamic sensitivity achieved using a coiled configuration. Our proposed electrolytic polymerization technique with magnet-responsive hybrid fluid (HF) was employed to fabricate soft, elastic rubber sensors with embedded coiled electrodes. The coiled configuration, optimized by electrolytic polymerization, exhibited high responsiveness to dynamic motions including pressing, pinching, twisting, bending, and shearing. The mechanism of the haptic property was analyzed by electrochemical impedance spectroscopy (EIS), revealing that reactance variations define an equivalent electric circuit (EEC) whose resistance (R_p), capacitance (C_p), and inductance (L_p) change with applied force; these changes correspond to mechanical deformation and the resulting variation in the sensor’s built-in voltage. The roll-type Meissner-inspired sensor demonstrated fast-adapting behavior and broadband vibratory sensitivity, indicating its potential for high-performance tactile and auditory sensing. These findings confirm the feasibility of electrolytically polymerized hybrid fluid rubber as a platform for next-generation bioinspired haptic interfaces. Full article

Artificial muscles translate the biological principles of motion into soft, adaptive, and multifunctional actuation. This review accordingly highlights research into natural actuation strategies, such as skeletal muscles, muscular hydrostats, spider silk, and plant turgor systems, to reveal the principles underlying energy conversion and deformation control. Building on these insights, polymer-based artificial muscles based on these principles, including pneumatic muscles, dielectric elastomers, and ionic electroactive systems, are described and their capabilities for efficient contraction, bending, and twisting with tunable stiffness and responsiveness are summarized. Furthermore, the abilities of carbon nanotube composites and twisted yarns to amplify nanoscale dimensional changes through hierarchical helical architectures and achieve power and work densities comparable to those of natural muscle are discussed. Finally, the integration of these actuators into soft robotic systems is explored through biomimetic locomotion and manipulation systems ranging from jellyfish-inspired swimmers to octopus-like grippers, gecko-adhesive manipulators, and beetle-inspired flapping wings. Despite rapid progress in the development of artificial muscles, challenges remain in achieving long-term durability, energy efficiency, integrated sensing, and closed-loop control. Therefore, future research should focus on developing intelligent muscular systems that combine actuation, perception, and self-healing to advance progress toward realizing autonomous, lifelike machines that embody the organizational principles of living systems. Full article

Efficient coordination among software modules is essential for biomimetic robotic systems, much like the interaction among organs in a biological organism. However, implementing inter-process or inter-module communication in autonomous systems remains a complex and time-consuming task, particularly for new researchers. Simplifying inter-module communication is the central focus of this study. To address this challenge, we propose the DigitalTwinPort framework, a novel communication abstraction inspired by the port-based connectivity of embedded hardware systems. Unlike middleware-dependent solutions such as ROS, the proposed framework provides a lightweight, object-oriented structure that enables unified and scalable communication between software modules and networked devices. The concept is implemented in C++ and validated through an autonomous surface vehicle (ASV) developed for the RobotX Challenge. Results demonstrate that the DigitalTwinPort simplifies the development of distributed systems, reduces configuration overhead, and enhances synchronization between digital and physical components. This work lays the foundation for future digital twin architectures in embodied Internet systems, where software and hardware can interact seamlessly through standardized digital ports. Full article

To address the challenge of head stability in a biomimetic robotic dolphin during self-propulsion, this study systematically investigates the passive stabilization mechanism of a bio-inspired caudal keel. A combined experimental and computational fluid dynamics (CFD) approach was employed to evaluate four keel geometries across a tail oscillation frequency range of 0.5–2 Hz. The experimental results demonstrate that the optimal keel configuration reduced the standard deviation of the head pitch angle by 20.9% at 2 Hz. CFD analysis revealed a dual stabilization mechanism: an effective keel not only attenuates the intensity of the primary disturbance moment at the driving frequency but, more critically, also enhances the spectral purity of the signal by suppressing high-frequency harmonics and broadband stochastic noise through the systematic reorganization of caudal vortices. A systematic investigation of keel geometry identified non-dimensional height (h/c) as the dominant parameter, with its stabilizing effect exhibiting diminishing returns beyond an optimal range. Furthermore, a quantifiable design trade-off was established, showing an approximate 9.1% increase in the Cost of Transport (CoT) for the most stable configuration. These findings provide quantitative design principles and a deeper physical insight into the passive stabilization of biomimetic underwater vehicles, highlighting the importance of both disturbance intensity and spectral quality. Full article

In recent years, humanoid robots have made substantial advances in motion control and multimodal interaction. However, full-size humanoid robots face significant technical challenges due to their inherent geometric and physical properties, leading to large inertia of humanoid robots and substantial driving forces. These characteristics result in issues such as limited biomimetic capabilities, low control efficiency, and complex system integration, thereby restricting practical applications of full-size humanoid robots in real-world settings. To address these limitations, this paper incorporates a biomimetic design approach that draws inspiration from biological structures and movement mechanisms to enhance the robot’s human-like movements and overall efficiency. The platform introduced in this paper, Loong, is designed to overcome these challenges, offering a practically viable solution for full-size humanoid robots. The research team has innovatively used highly biomimetic joint designs to enhance Loong’s capacity for human-like movements and developed a multi-level control architecture along with a multi-master high-speed real-time communication mechanism that significantly improves its control efficiency. In addition, Loong incorporates a modular system integration strategy, which offers substantial advantages in mass production and maintenance, which improves its adaptability and practical utility for diverse operational environments. The biomimetic approach not only enhances Loong’s functionality but also enables it to perform better in complex and dynamic environments. To validate Loong’s design performance, extensive experimental tests were performed, which demonstrated the robot’s ability to traverse complex terrains such as 13 cm steps and 20° slopes and its competence in object manipulation and transportation. These innovations provide a new design paradigm for the development of full-size humanoid robots while laying a more compatible foundation for the development of hardware platforms for medium- and small-sized humanoid robots. This work makes a significant contribution to the practical deployment of humanoid robots. Full article