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The tight coupling of shape transformation, stiffness tuning, and self‐sensing that biological organisms exhibit has long served as inspiration for next‐generation soft robots. However, most current soft robots rely on intrinsically soft materials for actuation, separately embedded sensors for sensing, and have fixed stiffness once fabricated. Large gaps remain between these soft robots and biological organisms where multifunctionality is realized within an integrated body. Herein, a new class of robotic structures from architectured particle assemblies is introduced. They combine three functions: shape changing, stiffness variation, and self‐sensing into one monolithic structure. Unlike traditional entirely soft robots, the design utilizes the geometric contacts of stiff, architectured particles under confining pressure to achieve these functions. The applications of these structures by designing smart self‐sensing architectures and soft grippers are demonstrated. The design provides a new paradigm of multifunctional robotic structures, with potential multiscale applications in adaptive robots, smart devices, and reconfigurable architectures.

The rapid development of the transportation industry has brought about the demand for massive data transmission. In order to make use of a large number of heterogeneous network resources in vehicular network, the research of applying network coding to multipath transmission has become a hot topic. Network coding can better solve the problems of packet reordering and low aggregation efficiency. The determination of coding scale is the key to network coding scheme. However, the existing research cannot adapt to the different characteristics of network resources in vehicular network, leading to larger decoding time cost and lower bandwidth aggregation efficiency. In this paper, we propose a network coding scheme called Delay Determined Group Size (DDGS), which could adaptively adjust the coding group according to the heterogeneous wireless networks state. The mathematical analysis and process design of the DDGS scheme are discussed in detail. Through a large number of simulations, we proved that the DDGS scheme is significantly superior to other coding group determination schemes in terms of decoding time cost and bandwidth aggregation efficiency.

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