Gait Pattern Generation of Hexapod-Type Microrobot Using Interstitial Cell Model Based Hardware Neural Networks IC

Abstract

The authors are studying a robot controlling system using hardware neural networks (HNN). Previously, the authors succeeded to locomote the quadruped-type and the hexapod-type microrobot systems using the HNN integrated circuit (IC). The HNN IC outputs four-phase pulse waveforms to drive both microrobot systems. However, gait patterns need 1.0 s pulse period which requires large capacitors. A large capacitor could not mount on IC; therefore, the external capacitors mounted on the circuit board. The further miniaturization of the HNN IC needs to minimize the capacitors. In this paper, the authors constructed HNN which can generate a large pulse period without using large capacitors. The interstitial cell model is used as a basic element of the HNN to generate a large time constant. The authors designed two types of HNN which can generate a tripod gait pattern and a ripple gait pattern which are typical walking patterns of insects. As a result, designed HNN can generate gait patterns without using external capacitors. The capacitors could construct inside the IC using the interstitial cell model.