人工神经网络
神经系统
人工智能
周围神经
神经科学
作者
Wang Wei Lee,Yu Jun Tan,Haicheng Yao,Si Li,Hian Hian See,Matthew Hon,Kian Ann Ng,Betty Xiong,John S. Ho,Benjamin C. K. Tee
出处
期刊:Science robotics
[American Association for the Advancement of Science (AAAS)]
日期:2019-07-17
卷期号:4 (32)
被引量:93
标识
DOI:10.1126/scirobotics.aax2198
摘要
The human sense of touch is essential for dexterous tool usage, spatial awareness, and social communication. Equipping intelligent human-like androids and prosthetics with electronic skins-a large array of sensors spatially distributed and capable of rapid somatosensory perception-will enable them to work collaboratively and naturally with humans to manipulate objects in unstructured living environments. Previously reported tactile-sensitive electronic skins largely transmit the tactile information from sensors serially, resulting in readout latency bottlenecks and complex wiring as the number of sensors increases. Here, we introduce the Asynchronously Coded Electronic Skin (ACES)-a neuromimetic architecture that enables simultaneous transmission of thermotactile information while maintaining exceptionally low readout latencies, even with array sizes beyond 10,000 sensors. We demonstrate prototype arrays of up to 240 artificial mechanoreceptors that transmitted events asynchronously at a constant latency of 1 ms while maintaining an ultra-high temporal precision of <60 ns, thus resolving fine spatiotemporal features necessary for rapid tactile perception. Our platform requires only a single electrical conductor for signal propagation, realizing sensor arrays that are dynamically reconfigurable and robust to damage. We anticipate that the ACES platform can be integrated with a wide range of skin-like sensors for artificial intelligence (AI)-enhanced autonomous robots, neuroprosthetics, and neuromorphic computing hardware for dexterous object manipulation and somatosensory perception.
科研通智能强力驱动
Strongly Powered by AbleSci AI