The hardness of rigid electronic devices limits its application scope. People use flexible scheme to improve it, so the design of flexible circuit structure is very important. Some special structures, such as island bridge structure, mesh structure and serpentine structure, can make the circuit have the ability of deformation. However, people cannot get good results from using a single structure, but the multi-level structures may improve the flexibility. Inspired by the softness of the net in our life, combined with the honeycomb structure, we design a 2-D honeycomb mesh structure. When the mesh is stretched, the 2-D hole is deformed by stress, and the local large strain converts to the small strain of the whole structure to avoid fracture. The stretch-ability of the single-level honeycomb mesh structure is 6.77%. Then, in order to further improve the flexibility, the serpentine structure is applied to the edge of the honeycomb structure to form a two-level structure. When the primary-level honeycomb structure is stretched, the second-level serpentine structure is also appropriately stretched to improve the flexibility. Finite element analysis shows the stretch-ability is 8.3%, which is better than single-level structure. Next, we also simulate the bending angle and twist angle of the structure, which has 120 degree bending (bending radius 1.55mm), 54 degree twisting and no plastic deformation occurs. It is clear that the multi-level microstructure has better flexibility, which provides a new scheme for the fabrication of flexible electronic devices and circuit microstructure design.
Nowadays many tasks such as medical correlation, surgery and so on almost depend on manpower. Because of occlusions and environmental impacts, artificial intelligence method can help little. For this situation, we design a multicamera stereo vision system which can be used in poor situation to catch and reconstruct certain object. To reduce the environmental impact, infrared devices like cameras, complement lamps and infrared reflection target balls are selected. The system reconstructs object through detecting target balls set on the key position of object instead of directly detect the whole object. When working, the self-adaptive system can choose all or part cameras due to occlusion and lighting conditions to capture pictures containing target spheres. To verify the feasibility and positioning accuracy of this system, we design a 4-DOF mechanical arm and arrange a set of experiments shown in this paper. The whole system can be applied as a real-time and precise auxiliary approach to many object detection tasks such as surgery navigation, position detection and object tracking.
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