Search Results (183)

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

Knee flexion refers to the relative motion between the tibia and femur including rolling and sliding (rollback motion). Notwithstanding the individual variations in knee motion, conventional wearable knee-assistive devices use hinge joints—resulting in nonnegligible mismatched movements, particularly during deep flexion. Therefore, we proposed a biomimetic knee joint (BKJ) that adapts to individual knee motion. A polycentric BKJ, integrating two gears with different radii, was designed to match the trajectory of the rotational axes of the knee. In this study, we developed a semi-active polycentric BKJ (SA-BKJ) incorporating an adjustable reaction-force mechanism (ARFM). In the ARFM, the combined spring constant can be adjusted using a shape-memory alloy actuator owing to its compact size, lightweight nature, and low energy consumption. In addition, the geared joint of the SA-BKJ (which integrates two gears with different radii) was designed to match the average trajectory of the rotational axes of the knee (of 22 healthy men). Applying the genetic algorithm, the radius of the femur and tibia gears were determined to be 25.5 and 40.0 mm. Misalignments of the designed SA-BKJ were measured in three healthy male participants. The error measurements averaged 20 degrees in the control device and 10 degrees in the optimized device. These results indicated that the optimized gears of the SA-BKJ totally reduced the misalignment. 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

Magnetic microrobots have emerged as a promising platform for drug delivery in recent years. By enabling remotely controlled motion and precise navigation under external magnetic fields, these systems offer new solutions to overcome the limitations of traditional drug delivery nanocarriers, such as inadequate tissue penetration and heterogeneous biodistribution. Over the past few years, significant advancements have been made in the structural design of magnetic microrobots, as well as in drug loading techniques and stimuli-responsive drug release mechanisms, thereby demonstrating distinct advantages in enhancing therapeutic efficacy and targeting precision. This review provides a comprehensive overview of magnetic drug delivery microrobots, which are categorised into biomimetic structural, bio-templated and advanced material-based types, and introduces their differences in propulsion efficiency and biocompatibility. Additionally, drug loading and release strategies are summarised, including physical adsorption, covalent coupling, encapsulation, and multistimuli-responsive mechanisms such as pH, enzyme activity and thermal triggers. Overall, these advancements highlight the significant potential of magnetic microrobots in targeted drug delivery and emphasise the key challenges in their clinical translation, such as biological safety, large-scale production and precise targeted navigation within complex biological environments. Full article

In major pineapple-producing regions of China, conventional manual harvesting is challenged by high labor intensity and cost. Existing mechanical harvesters, still largely in the research and development stage, often suffer from low efficiency and high susceptibility to fruit damage, failing to meet large-scale production demands. This study focuses on the Tainung 16 pineapple, determining that the tensile force required to separate the fruit stem at the calyx ranges from 100.42 N to 165.38 N. Drawing on the biomimetic principles of manual stem-breaking, we designed a harvesting device featuring a curved fixed baffle and a rotating unit. Using theoretical analysis and ADAMS simulation, a mechanical model of the device–stem interaction was established to simulate the force application, bending, and separation processes. This led to the identification of optimal operational parameters: a forward speed of 1.5 m/s, a harvesting unit rotational speed of 37 r/min, and a motion trajectory parameter of 1.3. Field tests demonstrated an average harvesting success rate of 81.23% with a fruit damage rate as low as 9.35%. The device thus effectively addresses the critical industry challenges of low efficiency and high damage. This work provides a direct technical reference and theoretical foundation for the engineering development, refinement, and standardized field operation of pineapple harvesters, facilitating the transition to mechanized large-scale harvesting. Full article

In response to the personalized and precise rehabilitation needs for motor injuries and stroke associated with population aging, this study proposes a design method for an intelligent rehabilitation trainer that integrates Bayesian information gain (BIG) and axis matching techniques. Grounded in the biomechanical characteristics of the human ankle joint, the design fully draws upon biomimetic principles, constructing a 3-PUU-R hybrid serial–parallel bionic mechanism. By mimicking the dynamic variation of the ankle’s instantaneous motion axis and its balance between stiffness and compliance, a three-dimensional digital model was developed, and multi-posture human factor simulations were conducted, thereby achieving a rehabilitation process more consistent with natural human movement patterns. Natural randomized disability grade experimental data were collected for 100 people to verify the validity of the design results. On this basis, a Bayesian information gain framework was established by quantifying the reduction of uncertainty in rehabilitation outcomes through characteristic parameters, enabling the dynamic optimization of training strategies for personalized and precise ankle rehabilitation. The rehabilitation process was modeled as a problem of uncertainty quantification and information gain optimization. Prior distributions were constructed using surface EMG (electromyography) signals and motion trajectory errors, and mutual information was used to drive the dynamic adjustment of training strategies, ultimately forming a closed-loop control architecture of “demand perception–strategy optimization–execution adaptation.” This innovative integration of probabilistic modeling and cross-joint bionic design overcomes the limitations of single-joint rehabilitation and provides a new paradigm for the development of intelligent rehabilitation devices. The deep integration mechanism-based dynamic axis matching and Bayesian information gain holds significant theoretical value and engineering application prospects for enhancing the effectiveness of neural plasticity training. 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

Direct ink writing (DIW) deposits viscous, shear-responsive inks at low temperature, enabling hydrogels and cell-laden bioinks for biomedical fabrication. Access to DIW remains limited by the cost of dedicated systems and the complexity of custom motion control. Repurposing fused deposition modeling (FDM) printers lowers these barriers by using accurate motion stages, open firmware, and familiar workflows while preserving build volume. In this study, three DIW actuator designs were implemented on an FDM frame. The first used a gear-and-rail transmission that converted stepper rotation to plunger travel. The second used a direct trapezoidal-screw pusher that increased force but reduced build-space clearance. The third relocated actuation to a remote piston-driven module that decoupled force generation from the printhead. The final architecture integrates the remote piston with partitioned control, where the printer executes motion and a programmable logic controller (PLC) manages extrusion. This arrangement reduces carried mass, preserves build space, and enables precise volumetric dosing with fast response. On a standard desktop frame, the system achieved controllable deposition of an agar/alginate ink using off-the-shelf electronics and modest modifications. This approach promotes sustainable and accessible innovation by repurposing existing FDM printers with open-source hardware and modular components. The resulting platform supports biomimetic biofabrication by combining mechanical efficiency, environmental responsibility, and cost-effective design. Full article

The field of experimental radiooncology and the quality assessment (QA) aimed at patient safety both profit from the utilisation of biomimetic principles. The work with phantoms based on biological structures of animals or humans, utilising the principles of anatomic mimicry, has a long tradition in radiotherapy research. When phantoms are produced from tissue-equivalent materials, they mimic the radiological properties of tissues and organs, allowing researchers and clinicians to study dose distribution and optimise treatment plans without exposing real patients to radiation. Biomechanical mimicry would take this a step further by creating phantoms that replicate the movement and deformation of organs during physiological movement, such as heartbeat or breathing, enabling a more accurate simulation of dynamic treatment scenarios. Bioinspired sensor technologies, such as artificial skin or integrated detectors, can be used to monitor radiation exposure, organ motion or temperature changes during therapy with high precision. The utility of such a phantom could be further enhanced by creating a realistic tumour microenvironment as an irradiation target, following the principles of microenvironmental biomimicry. Thus, biomimetic strategies can be exploited in the validation of radiotherapy technologies and open new perspectives for adaptive radiotherapy and real-time monitoring. 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

Recent advances in bionic intelligence are reshaping humanoid-robot design, demonstrating unprecedented agility, dexterity and task versatility. These breakthroughs drive an increasing need for large scale and high-quality data. Current data generation methods, however, are often expensive and time-consuming. To address this, we introduce Digital Twin Loong (DT-Loong), a digital twin system that combines a high-fidelity simulation environment with a full-scale virtual replica of the humanoid robot Loong, a bionic robot encompassing biomimetic joint design and movement mechanism. By integrating optical motion capture and human-to-humanoid motion re-targeting technologies, DT-Loong generates data for training and refining embodied AI models. We showcase the data collected from the system is of high quality. DT-Loong also proposes a Priority-Guided Quadratic Optimization algorithm for action retargeting, which achieves lower time delay and enhanced mapping accuracy. This approach enables real-time environmental feedback and anomaly detection, making it well-suited for monitoring and patrol applications. Our comprehensive framework establishes a foundation for humanoid robot training and further digital twin applications in humanoid robots to enhance their human-like behaviors through the emulation of biological systems and learning processes. Full article

Biomimetic knee exoskeletons often struggle to balance accurate replication of joint biomechanics with efficient torque transmission. This study presents a knee exoskeleton featuring a single-stage planetary gear set with three coupled interface gears to reproduce the coupled rolling–sliding motion of the human knee. By mapping rolling and sliding displacements into distinct gear-driven motions, the design achieves a near-linear relationship approximating the physiological J-shaped instantaneous center of rotation (ICR). Gear parameters were optimized under biomechanical and engineering constraints, producing a compact, manufacturable configuration with ICR deviation ≤ 5 mm (sliding distance). Performance experience demonstrates that the optimized joint reduced sliding misalignment of the contact point by 73.4%, delivered peak output torque in agreement with predictions, and maintained an average efficiency of 95.4% across operating speeds. These findings confirm that the proposed mechanism enhances kinematic fidelity and actuation performance, offering a promising solution for next-generation rehabilitation exoskeletons. Full article