ニューラルネットワークを用いた流体の力覚提示

抄録

Fluid haptic rendering is expected to be applied in various fields, but it is difficult to implement in real-time. This paper proposes a method that uses Feedforward Neural Network (FNN) and Long Short-Term Memory (LSTM) to reproduce the fluid resistance. Although there were differences in the fluid flow between the two neural networks, it was confirmed that the reproducibility of the fluid was better with LSTM. The superiority of LSTM was also confirmed in terms of small error and useful long-term memory. In addition, compared to the conventional method, this proposed method has a higher sampling frequency of 500 Hz, which simplifies the real-time implementation.