Grippers with a single rigid or flexible state have corresponding limitations, such as poor safety of rigid grippers and low precision of flexible grippers, which require complex algorithms and additional sensors to perform tedious tasks. Here, we design a reconfigurable gripper based on three fingers that can switch among the rigid, rigid bending, and flexible states. This adaptability enables the gripper to perform in diverse application scenarios. The flexible joints are locked and released by the back-and-forth movement of a slider mechanism, thus enabling switches between the rigid and flexible states of the fingers. When the fingers are in the rigid state, the structure resembles a conventional rigid gripper; when the fingers are in the flexible state, the spring-supported joints are driven by four cables. We have developed the mathematical models for the three states, tested the performance of different grasping configurations, analyzed the factors that influence horizontal grasping errors, and finally explored the application of rigid-flexible cooperative operations. Numerical and empirical experimental results clearly demonstrate the viability of the proposed gripper and its wide adaptability to different tasks.

When the beetle lands on the target, the hind wings fold regularly to form smaller wing packages and are hidden on the ventral side of the elytra due to the interaction between the elytra and abdomen. Its complex folding pattern is attributed to the flexibility of the hind wings, the super-elasticity of the folding joints, and the special geometric morphology of the veins. The corrugation and folding pattern of the hind wings can provide new insights for the design of folding anti-collision mechanisms and the improvement of aerodynamic performance of ornithopter. This paper first proposes a beetle-type ornithopter with foldable wings based on the folding mechanism and kinematic characteristics of the beetle’s hind wings. Subsequently, a series of numerical simulations were conducted on flapping wing robot to explore its flapping kinematics, folding stability, structural stiffness. Finally, the force generation of flapping wings was tested on the fabricated prototype.

Venous blood collection is a widely used medical diagnostic technique, and with rapid advancements in robotics, robotic venous blood collection has the potential to replace traditional manual methods. The success of this robotic approach is heavily dependent on the quality of vein imaging. In this paper, we develop a vein imaging device based on the simulation analysis of vein imaging parameters and propose a U-Net+ResNet18 neural network for vein image segmentation. The U-Net+ResNet18 neural network integrates the residual blocks from ResNet18 into the encoder of the U-Net to form a new neural network. ResNet18 is pre-trained using the Bootstrap Your Own Latent (BYOL) framework, and its encoder parameters are transferred to the U-Net+ResNet18 neural network, enhancing the segmentation performance of vein images with limited labelled data. Furthermore, we optimize the AD-Census stereo matching algorithm by developing a variable-weight version, which improves its adaptability to image variations across different regions. Results show that, compared to U-Net, the BYOL+U-Net+ResNet18 method achieves an 8.31% reduction in Binary Cross-Entropy (BCE), a 5.50% reduction in Hausdorff Distance (HD), a 15.95% increase in Intersection over Union (IoU), and a 9.20% increase in the Dice coefficient (Dice), indicating improved image segmentation quality. The average error of the optimized AD-Census stereo matching algorithm is reduced by 25.69%, and the improvement of the image stereo matching performance is more obvious. Future research will explore the application of the vein imaging system in robotic venous blood collection to facilitate real-time puncture guidance.

The beetle, of the order Coleoptera, possesses outstanding flight capabilities. After completing flight, they can fold their hindwings under the elytra and swiftly unfold them again when they take off. This sophisticated hindwing structure is a result of biological evolution, showcasing the strong environmental adaptability of this species. The beetle’s hindwings can provide biomimetic inspiration for the design of flapping-wing micro air vehicles (FWMAVs). In this study, the Asian ladybird (Harmonia axyridis Pallas) was chosen as the bionic research object. Various kinematic parameters of its flapping flight were analyzed, including the flight characteristics of the hindwings, wing tip motion trajectories, and aerodynamic characteristics. Based on these results, a flapping kinematic model of the Asian ladybird was established. Then, three bionic deployable wing models were designed and their structural mechanical properties were analyzed. The results show that the structure of wing vein bars determined the mechanical properties of the bionic wing. This study can provide a theoretical basis and technical reference for further bionic wing design.