Towards a minimal architecture for a printable, modular, and robust sensing skin

Towards a minimal architecture for a printable, modular, and robust sensing skin
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迈向可打印、模块化和坚固的传感皮肤的最小架构

DOI:
10.1109/iros.2012.6386210
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发表时间:
2012
期刊:
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
影响因子:
--
通讯作者:
R. Fearing
R. Fearing
中科院分区:
--
文献类型:
--
作者:
Austin D. Buchan;J. Bachrach;R. Fearing

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这项工作提出了一种低复杂度的模块化传感器网格架构,为非凸形状(如机器人身体和腿)提供智能皮肤。为了配置由任意切割和设计中的快速变化形成的感测皮肤,我们使用波前规划方法来生成柔性衬底有线网络上的连续的、规则布置的模块化感测单元的任意拓扑的最小深度生成树。一个有限状态机协议提取这种拓扑结构和传感器信息,是强大的破坏性传感器丢失,设备故障,和传输噪声。该架构被设计为在每个节点处要求尽可能少的状态复杂度,以最小化以可印刷半导体技术实现的这种网络的面积和成本。仿真数据显示恢复网络故障和扩展的架构,以更大的网络与任意几何形状,并验证架构逻辑的样本合成显示具有非常低的状态和组合逻辑的复杂性。在柔性基板上使用微控制器和光学接近传感器的架构的概念验证实现显示了与用于仿生Millirobots的缩放复合制造工艺的集成。
This work presents a low-complexity modular sensor grid architecture to provide a smart skin to non-convex shapes, such as a robot body and legs. To configure a sensing skin shaped by arbitrary cuts and rapid changes in designs, we use a wavefront planning approach to generate a minimum-depth spanning tree of an arbitrary topology of contiguous, regularly arranged modular sensing units on a flexible substrate wired network. A Finite State Machine protocol for extracting this topology and sensor information is shown that is robust to destructive sensor loss, device failure, and transmission noise. The architecture is designed to require as little state complexity at each node as possible to minimize the area and cost of such a network implemented in printable semiconductor technology. Simulation data show recovery from network failures and extension of the architecture to larger networks with arbitrary geometry, and a sample synthesis of the verified architecture logic is shown to have a very low state and combinational logic complexity. A proof-of-concept implementation of the architecture using microcontrollers and optical proximity sensors on a flexible substrate show integration with a Scaled Composite Manufacturing process used for Biomimetic Millirobots.
DOI: 10.1038/nmat1891
发表时间: 2007-05-01
期刊: NATURE MATERIALS
影响因子: 41.2
作者:
McAlpine, Michael C.;Ahmad, Habib;Heath, James R.
通讯作者: Heath, James R.