Dynamics‐Oriented Underwater Mechanoreception Interface for Simultaneous Flow and Contact Perception
The lack of a sufficient and efficient way to simultaneously perceive general underwater mechanical stimuli, physical contact, and fluidic flow has been a bottleneck for many aquatic applications. To address this challenge, dynamics‐oriented underwater mechanoreceptor interface (DOUMI), a bioinspired mechanoreception system that realizes simultaneous contact and flow perception using a single receptor, is introduced. This receptor, response‐elevated‐and‐expanded hair‐like tactile mechanoreceptor (REEM), is inspired by the mechanoreceptive mechanism of aquatic arthropods. REEM combines structural features from different mechanoreceptive sensilla, enabling it to capture a wide range of stimulus dynamics. Under different stimuli, REEM encodes stimuli dynamics as its oscillations with distinct spectral attributes. Those oscillations are efficiently transferred through mechanical processes and imaging, enabling vision‐based extraction and further analysis. Therefore, by evaluating the oscillation dynamics with tailored wavelet‐based indices, DOUMI can distinguish between contact‐ and flow‐induced oscillations at each receptor unit with 90.5% accuracy. Furthermore, DOUMI provides comprehensive 2D mechanoreception with a scalable array of REEMs, delivering capabilities like stimuli spatiotemporal visualization, flow trend detection, and scenario classification with an accuracy of 99.5%. With its robustness and operational efficiency in underwater environments, DOUMI can be easily adapted to existing applications using common materials and hardware, establishing a new, streamlined paradigm for underwater general mechanoreception.
Authors
- Cheng Yu (ORCID: https://orcid.org/0000-0003-1039-1300)
- Zheng Wang (ORCID: https://orcid.org/0000-0002-7726-0770)
- Jia Pan (ORCID: https://orcid.org/0000-0001-9003-2054)
- Wenping Wang (ORCID: https://orcid.org/0000-0002-2284-3952)
- Sicong Liu (ORCID: https://orcid.org/0000-0002-1872-5283)
- Hua Zhong (ORCID: https://orcid.org/0000-0003-2293-5168)
- Yaxi Wang (ORCID: https://orcid.org/0000-0003-2724-7233)
- Jiahao Xu (ORCID: https://orcid.org/0009-0007-4133-9384)
Institutions
- Southern University of Science and Technology (CN)
- University College London (GB)
- University of Hong Kong (HK)
- Texas A&M University (US)
Publication Details
- Journal
- Advanced Intelligent Systems
- Published
- 2024-10-20
- DOI
- https://doi.org/10.1002/aisy.202400492
- Citations
- 1
- Primary Topic
- Underwater Vehicles and Communication Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.34
Funders
- Science, Technology and Innovation Commission of Shenzhen Municipality
- Shenzhen Science and Technology Innovation Program
- Basic and Applied Basic Research Foundation of Guangdong Province