Journal of Bionic Engineering最新文献

In developing and exploring extreme and harsh underwater environments, underwater robots can effectively replace humans to complete tasks. To meet the requirements of underwater flexible motion and comprehensive subsea operation, a novel octopus-inspired robot with eight soft limbs was designed and developed. This robot possesses the capabilities of underwater bipedal walking, multi-arm swimming, and grasping objects. To closely interact with the underwater seabed environment and minimize disturbance, the robot employs a cable-driven flexible arm for its walking in underwater floor through a bipedal walking mode. The multi-arm swimming offers a means of three-dimensional spatial movement, allowing the robot to swiftly explore and navigate over large areas, thereby enhancing its flexibility. Furthermore, the robot’s walking arm enables it to grasp and transport objects underwater, thereby enhancing its practicality in underwater environments. A simplified motion models and gait generation strategies were proposed for two modes of robot locomotion: swimming and walking, inspired by the movement characteristics of octopus-inspired multi-arm swimming and bipedal walking. Through experimental verification, the robot’s average speed of underwater bipedal walking reaches 7.26 cm/s, while the horizontal movement speed for multi-arm swimming is 8.6 cm/s.

Snake Optimizer (SO) is a novel Meta-heuristic Algorithm (MA) inspired by the mating behaviour of snakes, which has achieved success in global numerical optimization problems and practical engineering applications. However, it also has certain drawbacks for the exploration stage and the egg hatch process, resulting in slow convergence speed and inferior solution quality. To address the above issues, a novel multi-strategy improved SO (MISO) with the assistance of population crowding analysis is proposed in this article. In the algorithm, a novel multi-strategy operator is designed for the exploration stage, which not only focuses on using the information of better performing individuals to improve the quality of solution, but also focuses on maintaining population diversity. To boost the efficiency of the egg hatch process, the multi-strategy egg hatch process is proposed to regenerate individuals according to the results of the population crowding analysis. In addition, a local search method is employed to further enhance the convergence speed and the local search capability. MISO is first compared with three sets of algorithms in the CEC2020 benchmark functions, including SO with its two recently discussed variants, ten advanced MAs, and six powerful CEC competition algorithms. The performance of MISO is then verified on five practical engineering design problems. The experimental results show that MISO provides a promising performance for the above optimization cases in terms of convergence speed and solution quality.

Amplifying the intrinsic wettability of substrate material by changing the solid/liquid contact area is considered to be the main mechanism for controlling the wettability of rough or structured surfaces. Through theoretical analysis and experimental exploration, we have found that in addition to this wettability structure amplification effect, the surface structure also simultaneously controls surface wettability by regulating the wetting state via changing the threshold Young angles of the Cassie–Baxter and Wenzel wetting regions. This wetting state regulation effect provides us with an alternative strategy to overcome the inherent limitation in surface chemistry by tailoring surface structure. The wetting state regulation effect created by multi-scale hierarchical structures is quite significant and plays is a crucial role in promoting the superhydrophobicity, superhydrophilicity and the transition between these two extreme wetting properties, as well as stabilizing the Cassie–Baxter superhydrophobic state on the fabricated lotus-like hierarchically structured Cu surface and the natural lotus leaf.

Medical image segmentation has witnessed rapid advancements with the emergence of encoder–decoder based methods. In the encoder–decoder structure, the primary goal of the decoding phase is not only to restore feature map resolution, but also to mitigate the loss of feature information incurred during the encoding phase. However, this approach gives rise to a challenge: multiple up-sampling operations in the decoder segment result in the loss of feature information. To address this challenge, we propose a novel network that removes the decoding structure to reduce feature information loss (CBL-Net). In particular, we introduce a Parallel Pooling Module (PPM) to counteract the feature information loss stemming from conventional and pooling operations during the encoding stage. Furthermore, we incorporate a Multiplexed Dilation Convolution (MDC) module to expand the network's receptive field. Also, although we have removed the decoding stage, we still need to recover the feature map resolution. Therefore, we introduced the Global Feature Recovery (GFR) module. It uses attention mechanism for the image feature map resolution recovery, which can effectively reduce the loss of feature information. We conduct extensive experimental evaluations on three publicly available medical image segmentation datasets: DRIVE, CHASEDB and MoNuSeg datasets. Experimental results show that our proposed network outperforms state-of-the-art methods in medical image segmentation. In addition, it achieves higher efficiency than the current network of coding and decoding structures by eliminating the decoding component.

Herein, a control method based on the optimal energy efficiency of a hydraulic quadruped robot was proposed, which not only realizes the optimal energy efficiency of flying trot gait but also ensures the stability of high-speed movement. Concretely, the energy consumption per unit distance was adopted as the energy efficiency evaluation index based on the constant pressure oil supply characteristics of the hydraulic system, and the global optimization algorithm was adopted to solve the optimal parameters. Afterward, the gait parameters that affect the energy efficiency of quadruped were analyzed and the mapping relationship between each parameter and energy efficiency was captured, so as to select the optimum combination of energy efficiency parameters, which is significant to improve endurance capability. Furthermore, to ensure the stability of the high-speed flying trot gait motion of the hydraulic quadruped robot, the active compliance control strategy was employed. Lastly, the proposed method was successfully verified by simulations and experiments. The experimental results reveal that the flying trot gait of the hydraulic quadruped robot can be stably controlled at a speed of 2.2 m/s.

In rehabilitation training, it is crucial to consider the compatibility between exoskeletons and human legs in motion. However, most exoskeletons today adopt an anthropomorphic serial structure, which results in rotational centers that are not precisely aligned with the center of the hip joint. To address this issue, we introduce a novel exoskeleton called the Parallel Hip Exoskeleton (PH-Exo) in this paper. PH-Exo is meticulously designed based on the anisotropic law of output torque. Considering the friction of the drive components, a dynamic model of the human–machine complex is established. Simulation analysis demonstrates that PH-Exo not only exhibits outstanding torque performance but also achieves high controllability in both flexion/extension and adduction/abduction directions. Additionally, a robust controller is designed to address model uncertainty, friction, and external interference. Wearing experiments indicate that under the control of the robust controller, each motor achieves excellent tracking performance.

Energy issues have always been one of the most significant concerns for scientists worldwide. With the ongoing over exploitation and continued outbreaks of wars, traditional energy sources face the threat of depletion. Wind energy is a readily available and sustainable energy source. Wind farm layout optimization problem, through scientifically arranging wind turbines, significantly enhances the efficiency of harnessing wind energy. Meta-heuristic algorithms have been widely employed in wind farm layout optimization. This paper introduces an Adaptive strategy-incorporated Integer Genetic Algorithm, referred to as AIGA, for optimizing wind farm layout problems. The adaptive strategy dynamically adjusts the placement of wind turbines, leading to a substantial improvement in energy utilization efficiency within the wind farm. In this study, AIGA is tested in four different wind conditions, alongside four other classical algorithms, to assess their energy conversion efficiency within the wind farm. Experimental results demonstrate a notable advantage of AIGA.

This study, grounded in Waxman fusion method, introduces an algorithm for the fusion of visible and infrared images, tailored to a two-level lighting environment, inspired by the mathematical model of the visual receptive field of rattlesnakes and the two-mode cells' mechanism. The research presented here is segmented into three components. In the first segment, we design a preprocessing module to judge the ambient light intensity and divide the lighting environment into two levels: day and night. The second segment proposes two distinct network structures designed specifically for these daytime and nighttime images. For the daytime images, where visible light information is predominant, we feed the ON-VIS signal and the IR-enhanced visual signal into the central excitation and surrounding suppression regions of the ON-center receptive field in the B channel, respectively. Conversely, for nighttime images where infrared information takes precedence, the ON-IR signal and the Visual-enhanced IR signal are separately input into the central excitation and surrounding suppression regions of the ON-center receptive field in the B channel. The outcome is a pseudo-color fused image. The third segment employs five different no-reference image quality assessment methods to evaluate the quality of thirteen sets of pseudo-color images produced by fusing infrared and visible information. These images are then compared with those obtained by six other methods cited in the relevant reference. The empirical results indicate that this study's outcomes surpass the comparative results in terms of average gradient and spatial frequency. Only one or two sets of fused images underperformed in terms of standard deviation and entropy when compared to the control results. Four sets of fused images did not perform as well as the comparison in the Q^AB/F index. In conclusion, the fused images generated through the proposed method show superior performance in terms of scene detail, visual perception, and image sharpness when compared with their counterparts from other methods.

This article provides an overview of the application of bionic technology in marine cruising equipment, discussing its research progress and future development trends. Marine cruising is a crucial means of gaining insights into the marine environment and conducting scientific research. However, conventional marine cruising equipment faces numerous challenges when dealing with complex and ever-changing marine environments. Bionic technology, as a means of drawing inspiration from the structure and functions of living organisms, offers new approaches and methods to address the challenges faced by marine cruising equipment and has found widespread application. The article primarily focuses on the applications and historical developments of bionic technology in propulsion methods, drag reduction, and surface antifouling. It summarizes the design principles, manufacturing techniques, and optimization methods for marine biomimetic cruising equipment. Finally, this paper analyzes the achievements, challenges, and future directions of bionic technology in marine cruising equipment. The application of bionic technology in marine cruising equipment holds vast potential for development, enabling us to better confront the challenges of marine exploration and research by drawing wisdom from nature and driving advancements in marine science.

In-pipe robots have been widely used in pipes–with smooth inner walls. However, current in-pipe robots face challenges in terms of moving past obstacles and climbing in marine-vessel pipeline systems, which are affected by marine biofouling and electrochemical corrosion. This paper takes inspiration from the dual-hook structure of Trypoxylus dichotomus’s feet and gecko‑like dry adhesives, proposing an in-pipe robot that is capable of climbing on rough and smooth pipe inwalls. The combination of the bioinspired hook and dry adhesives allows the robot to stably attach to rough or smooth pipe inwalls, while the wheel-leg hybrid mechanism provides better conditions for obstacle traversal. The paper explores the attachment and obstacle-surmounting mechanisms of the robot. Moreover, motion strategies for the robot are devised based on different pipe structural features. The experiments showed that this robot can adapt to both smooth and rough pipe environments simultaneously, and its motion performance is superior to conventional driving mechanisms. The robot’s active turning actuators also enable it to navigate through horizontally or vertically oriented 90° bends.