Journal of Bionic Engineering最新文献

Researching the cooperative operation and functional expansion of multiple minirobot assemblies has the potential to bring about significant advancements in the practical applications of minirobots. In this study, we present a novel assembly system comprised of arc-shaped NdFeB magnetic minirobots. These minirobots can be individually utilized as assembly units, allowing for function expansion and comprehensive capability enhancement. We fabricate four Semicircular Arc Magnetic Minirobots (SAMM) arranged in different configurations and analyze their force and motion characteristics. Furthermore, by using this unit as a base, various expansion structures such as latches, petals, and rings can be assembled through reasonable combinations. We define the comprehensive reinforcement interval by comparatively analyzing changes in the unit’s motion characteristics and operational capabilities. Precise motion manipulation is employed to verify the rationality of the basic unit structure and the feasibility of the assembly scheme. Our proposed self-assembly scheme for magnetic minirobots exhibits great potential and may be used as a paradigm for future research on expanding the functionality of minirobots.

This study aims to develop a magnetorheological (MR) damper for semi-active knee prostheses to restore the walking ability of transfemoral amputees. The core dimensions of the MR damper were determined via theoretical magnetic field calculations, and the theoretical relationship between current and joint torque was derived through electromagnetic simulation. Then, a physical prototype of the semi-active prosthetic knee equipped with the MR damper was manufactured. Based on the data obtained from angle sensor, pressure sensor (loadcell), and inertial measurement unit (IMU) on the prosthesis, a matching control algorithm is developed. The joint torque of the MR damper can be adaptively adjusted according to the walking speed of the amputee, allowing the amputee to realize a natural gait. The effectiveness of the control program was verified by the ADAMS and MATLAB co-simulation. The results of the test and simulation show that the MR damper can provide sufficient torque needed for normal human activities.

In response to the shortcomings of Dwarf Mongoose Optimization (DMO) algorithm, such as insufficient exploitation capability and slow convergence speed, this paper proposes a multi-strategy enhanced DMO, referred to as GLSDMO. Firstly, we propose an improved solution search equation that utilizes the Gbest-guided strategy with different parameters to achieve a trade-off between exploration and exploitation (EE). Secondly, the Lévy flight is introduced to increase the diversity of population distribution and avoid the algorithm getting stuck in a local optimum. In addition, in order to address the problem of low convergence efficiency of DMO, this study uses the strong nonlinear convergence factor Sigmaid function as the moving step size parameter of the mongoose during collective activities, and combines the strategy of the salp swarm leader with the mongoose for cooperative optimization, which enhances the search efficiency of agents and accelerating the convergence of the algorithm to the global optimal solution (Gbest). Subsequently, the superiority of GLSDMO is verified on CEC2017 and CEC2019, and the optimization effect of GLSDMO is analyzed in detail. The results show that GLSDMO is significantly superior to the compared algorithms in solution quality, robustness and global convergence rate on most test functions. Finally, the optimization performance of GLSDMO is verified on three classic engineering examples and one truss topology optimization example. The simulation results show that GLSDMO achieves optimal costs on these real-world engineering problems.

This study investigates the friction and deformation behavior of the skin in contact with a rigid massage ball and its influencing factors. Pressing and stretching experiments were conducted using a collaborative robot experimental platform. The experiments encompassed a loading normal force range of 2 N to 18 N and a sliding speed range of 10 mm/s to 20 mm/s. The friction response curve exhibits two different stages: static stick state and dynamic stick-slip stage, both of which have been mathematically modeled. By analyzing the experimental data, we analyzed the effects of elastic modulus, sliding speed and normal loading force on skin tangential friction and tensile deformation. The results indicate that as the normal load increases, both friction and deformation exhibit an increase. Conversely, they decrease with an increase in elastic modulus. Notably, while deformation diminishes with higher sliding speed, friction force remains relatively unaffected by velocity. This observation can be attributed to the strain rate sensitivity resulting from the viscoelastic characteristics of the skin under substantial deformation. This study advances the understanding of friction and deformation behavior during skin friction, offering valuable insights to enhance the operational comfort of massage robots.

Legged robots show great potential for high-dynamic motions in continuous interaction with the physical environment, yet achieving animal-like agility remains significant challenges. Legged animals usually predict and plan their next locomotion by combining high-dimensional information from proprioception and exteroception, and adjust the stiffness of the body’s skeletal muscle system to adapt to the current environment. Traditional control methods have limitations in handling high-dimensional state information or complex robot motion that are difficult to plan manually, and Deep Reinforcement Learning (DRL) algorithms provide new solutions to robot motioncontrol problems. Inspired by biomimetics theory, we propose a perception-driven high-dynamic jump adaptive learning algorithm by combining DRL algorithms with Virtual Model Control (VMC) method. The robot will be fully trained in simulation to explore its motion potential by learning the factors related to continuous jumping while knowing its real-time jumping height. The policy trained in simulation is successfully deployed on the bio-inspired single-legged robot testing platform without further adjustments. Experimental results show that the robot can achieve continuous and ideal vertical jumping motion through simple training

Within the consistent daily rhythm of human life, intervertebral discs endure a variety of complex loads beyond the influences of gravity and muscle forces, leading to significant morphological changes (in terms of volume, area, and height) as well as biomechanical alterations, including an increase in disc stiffness and a decrease in intradiscal pressure. Remarkably, the discs demonstrate an ability to regain their original morphological and biomechanical characteristics after a period of nocturnal rest. The preservation of normal disc function is critically dependent on this recovery phase, which serves to forestall premature disc degeneration. This phenomenon of disc recovery has been extensively documented through numerous in vivo studies employing advanced clinical techniques such as Magnetic Resonance Imaging (MRI), stadiometry, and intradiscal pressure measurement. However, the findings from in vitro studies present a more complex picture, with reports varying between full recovery and only partial recuperation of the disc properties. Moreover, research focusing on degenerated discs in vitro has shed light on the quantifiable impact of degeneration on the disc ability to recover. Fluid dynamics within the disc are considered a primary factor in recovery, yet the disc intricate multiscale structure and its viscoelastic properties also play key roles. These elements interact in complex ways to influence the recovery mechanism, particularly in relation to the overall health of the disc. The objective of this review is to collate, analyze, and critically evaluate the existing body of in vivo and in vitro research on this topic, providing a comprehensive understanding of disc recovery processes. Such understanding offers a blueprint for future advancements in medical treatments and bionic engineering solutions designed to mimic, support, and enhance the natural recovery processes of intervertebral discs.

To better understand the aerodynamic reasons for highly organized movements of flying organisms, the three-flapping wing system in tandem formation was studied numerically in this paper. Different from previous relevant studies on the multiple flapping wings that are equally spaced, this study emphasizes the impact of unequal spacing between individuals on the aerodynamics of each individual wing as well as the whole system. It is found that swapping the distance between the first and second wing with the distance between the second wing and the rearmost wing does not affect the overall aerodynamic performance, but significantly changes the distribution of aerodynamic benefits across each wing. During the whole flapping cycle, three effects are at play. The narrow channel effect and the downwash effect can promote and weaken the wing lift, respectively, while the wake capture effect can boost the thrust. It also shows that these effects could be manipulated by changing the spacing between adjacent wings. These findings provide a novel way for flow control in tandem formation flight and are also inspiring for designing the formation flight of bionic aircraft.

Flexible attachment actuators are popular in a wide range of applications, owing to their flexibility and highly reliable attachment. However, their reversible adhesion performance depends on the actual effective contact area and peel angle during operation. Therefore, a good actuator must ensure a uniform and reliable pre-pressure load on an adhesive surface, to increase the effective contact area of the attached surface, thereby maximizing adhesion. This study was inspired by fusion bionics for designing a hierarchical attachment structure with vacuum-adsorption and dry-adhesion mechanisms. The designed structure used the normal force under the negative pressure of a suction cup as a stable source of a pre-pressure load. By optimizing the rigid and flexible structural layers of the attachment structure, a load was applied uniformly to the adhesion area; thus, reliable attachment was achieved by self-preloading. The structure achieved detachment by exploiting the large deformation of a pneumatic structure under a positive pressure. The hierarchical attachment structure achieved up to 85% of the optimal performance of the adhesive surface. Owing to its self-preloading and reliable attachment characteristics, the designed structure can be used as an attachment unit in various complex scenarios, such as small, lightweight climbing platforms and the transport of objects in long, narrow pipelines.

When a human lands from a high drop, there is a high risk of serious injury to the lower limbs. On the other hand, cats can withstand jumps and falls from heights without being fatally wounded, largely due to their impact-resistant paw pads. The aim of the present study was to investigate the biomechanism of impact resistance in cat paw pads, propose an optimal hierarchical Voronoi structure inspired by the paw pads, and apply the structure to bionic cushioning shoes to reduce the impact force of landing for humans. The microstructure of cat paw pads was observed via tissue section staining, and a simulation model was reconstructed based on CT to verify and optimize the structural cushioning capacity. The distribution pattern, wall thickness of compartments, thickness ratio of epidermis and dermis, and number of compartments in the model were changed and simulated to achieve an optimal composed structure. A bionic sole was 3D-printed, and its performance was evaluated via compression test and a jumping-landing experiment. The results show that cat paw pads are a spherical cap structure, divided from the outside to the inside into the epidermis, dermis, and compartments, each with different cushioning capacities. A finite element simulation of different cushioning structures was conducted in a cylinder with a diameter of 20 mm and a height of 10 mm, featuring a three-layer structure. The optimal configuration of the three layers should have a uniform distribution with 0.3–0.5 mm wall thickness, a 1:1–2 thickness ratio of epidermis and dermis, and 100–150 compartments. A bionic sole with an optimized structure can reduce the peak impact force and delay the peak arrival time. Its energy absorption rate is about 4 times that of standard sole. When jumping 80, 100, and 120 cm, the normalized ground reaction force is also reduced by 8.7%, 12.6% and 15.1% compared with standard shoes. This study provides theoretical and technical support for effective protection against human lower limb landing injuries.

This paper presents a learning-based control framework for fast (< 1.5 s) and accurate manipulation of a flexible object, i.e., whip targeting. The framework consists of a motion planner learned or optimized by an algorithm, Online Impedance Adaptation Control (OIAC), a sim2real mechanism, and a visual feedback component. The experimental results show that a soft actor-critic algorithm outperforms three Deep Reinforcement Learning (DRL), a nonlinear optimization, and a genetic algorithm in learning generalization of motion planning. It can greatly reduce average learning trials (to < 20(%) of others) and maximize average rewards (to > 3 times of others). Besides, motion tracking errors are greatly reduced to 13.29(%) and 22.36(%) of constant impedance control by the OIAC of the proposed framework. In addition, the trajectory similarity between simulated and physical whips is 89.09(%). The presented framework provides a new method integrating data-driven and physics-based algorithms for controlling fast and accurate arm manipulation of a flexible object.