论文标题
使用红外范围查找和大厅效果磁性传感的智能头盔的软机器人膀胱压缩估算
Estimation of Soft Robotic Bladder Compression for Smart Helmets using IR Range Finding and Hall Effect Magnetic Sensing
论文作者
论文摘要
这项研究的重点是用于监视和控制用户头部和智能头盔外壳之间的相互作用的软机器人膀胱。这些膀胱的压缩决定了影响耗散。因此，本文的重点是膀胱压缩的传感和估计。使用回归技术和神经网络评估基于IR测距仪的解决方案，以估计膀胱压缩。还检查了霍尔效应（HE）磁传感系统，其中传感器嵌入膀胱的底部，感觉磁铁在膀胱顶部的位置。该论文介绍了HE传感器阵列，HE电压数据的信号处理，然后介绍了用于预测膀胱压缩的神经网络（NN）。研究了不同培训数据集对NN性能的功效。检查了不同的NN配置，以确定一种配置，该配置提供了尽可能少的节点的准确估计值。评估了不同的膀胱压缩轮廓，以表征IR范围查找，并在应用程序方案中基于HE的技术。
This research focuses on soft robotic bladders that are used to monitor and control the interaction between a user's head and the shell of a Smart Helmet. Compression of these bladders determines impact dissipation; hence the focus of this paper is sensing and estimation of bladder compression. An IR rangefinder-based solution is evaluated using regression techniques as well as a Neural Network to estimate bladder compression. A Hall-Effect (HE) magnetic sensing system is also examined where HE sensors embedded in the base of the bladder sense the position of a magnet in the top of the bladder. The paper presents the HE sensor array, signal processing of HE voltage data, and then a Neural Network (NN) for predicting bladder compression. Efficacy of different training data sets on NN performance is studied. Different NN configurations are examined to determine a configuration that provides accurate estimates with as few nodes as possible. Different bladder compression profiles are evaluated to characterize IR range finding and HE based techniques in application scenarios.
