Autonomous driving paper index
Contact-induced continuous electricity generation by ion-electron positive feedback coupled transport for self-powered ionic touch panel
One-line summary
Ionic touch panels are regarded as a key platform for future human-computer interaction and meta-universe due to their stretchable, transparent and skin-fitting properties.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充:本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Ionic touch panels are regarded as a key platform for future human-computer interaction and meta-universe due to their stretchable, transparent and skin-fitting properties. Inspired by the fact that human skin relies on ionic current to sense contact position information, we have investigated an ionogel based closed-loop electrical system that also converts contact into ionic current to form a self-powered single-layer ionic touch panel. Benefiting from the slowed charge transfer dynamics, the positive feedback coupling of the electrical double layer, and the high-density charge characteristics, the device generates an approximately steady-state electrical signal when touched. It is clearly different from the pulsed electrical phenomenon of conventional contact electrification devices. When a finger touches the touch panel, the voltage/current signal amplitude at each corner electrode of the ionogel has been proven to express the touch position. The continuity of the electrical signal ensures high-resolution recognition of the touch trajectory without the need for further contact separation. With the advantages of good transparency, large stretchability, self-power, single-layer structure, fast response and high resolution, we expect this emerging ionic touch panel to be an ideal candidate for a variety of human-computer interaction applications.
Links and sources
Need this topic turned into a technical roadmap?
Full Self Driving can prepare a custom autonomous driving literature review, code map, dataset map, and B2B technology assessment.
Request B2B research
Comments