Direction recognition capability is essential for intelligent systems to interact with the physical environment.However,current sensor systems often suffer from poor stability and response delays due to their complex ...Direction recognition capability is essential for intelligent systems to interact with the physical environment.However,current sensor systems often suffer from poor stability and response delays due to their complex circuit designs or multi-signal fusion algorithms.Inspired by the trichobothria on the tarsi of water striders,this study develops a bioinspired single-circuit multidirectional sensor(BSMS).By introducing an asymmetric mechanical structure with 20°directional tilt and 1/2-radius radial eccentricity,the design overcomes the axisymmetric limitations of conventional cantilever beams.By integrating a“wire-dot”heterodimensional composite conductive system,this approach achieves the resolution of multidirectional mechanical stimuli within a single sensing unit.The BSMS features an ingenious physical architecture that enables directional recognition using only a simple output circuit.The BSMS eliminates the need for multi-signal fusion algorithms while demonstrating outstanding overall performance.Its four-directional output signals exhibit 50%discrimination,along with excellent sensitivity across a wide range of 73.79-226.77 N^(-1).Moreover,the BSMS shows ultra-high response consistency(>98%)and rapid dynamic response(277.35%/s response rate and 89.47%/s recovery rate).Additionally,its stability is confirmed through 100-cycle testing.Inspired by the remarkable aquatic adaptability of water striders,we applied the BSMS to obstacle detection and directional recognition for remotely operated vessels.When integrated with deep learning algorithms,the BSMS achieved over 99%accuracy in both texture identification and directional sensing.This system offers a promising solution for autonomous obstacle avoidance,precision cargo delivery,and multi-vessel coordination in complex aquatic environments.It demonstrates potential for broader applications in flexible electronics and intelligent systems.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52175269)Innovative Research Group Project of the National Natural Science Foundation of China(Grant No.52021003)+2 种基金the Science and Technology Research Project of Education Department of Jilin Province(Grant Nos.JJKH20231146KJ,JJKH20241262KJ)Natural Science Foundation of Shandong Province(Grant No.ZR2024ME104)China Postdoctoral Science Foundation(Grant No.2024M751086)。
文摘Direction recognition capability is essential for intelligent systems to interact with the physical environment.However,current sensor systems often suffer from poor stability and response delays due to their complex circuit designs or multi-signal fusion algorithms.Inspired by the trichobothria on the tarsi of water striders,this study develops a bioinspired single-circuit multidirectional sensor(BSMS).By introducing an asymmetric mechanical structure with 20°directional tilt and 1/2-radius radial eccentricity,the design overcomes the axisymmetric limitations of conventional cantilever beams.By integrating a“wire-dot”heterodimensional composite conductive system,this approach achieves the resolution of multidirectional mechanical stimuli within a single sensing unit.The BSMS features an ingenious physical architecture that enables directional recognition using only a simple output circuit.The BSMS eliminates the need for multi-signal fusion algorithms while demonstrating outstanding overall performance.Its four-directional output signals exhibit 50%discrimination,along with excellent sensitivity across a wide range of 73.79-226.77 N^(-1).Moreover,the BSMS shows ultra-high response consistency(>98%)and rapid dynamic response(277.35%/s response rate and 89.47%/s recovery rate).Additionally,its stability is confirmed through 100-cycle testing.Inspired by the remarkable aquatic adaptability of water striders,we applied the BSMS to obstacle detection and directional recognition for remotely operated vessels.When integrated with deep learning algorithms,the BSMS achieved over 99%accuracy in both texture identification and directional sensing.This system offers a promising solution for autonomous obstacle avoidance,precision cargo delivery,and multi-vessel coordination in complex aquatic environments.It demonstrates potential for broader applications in flexible electronics and intelligent systems.
