Integrating Neuromorphic Designs in Two-Wheeled Self-Balancing Robots

Abstract

This research aims to investigate the implementation of neuromorphic designs into two-wheeled self-balancing robots (TWSBRs) with the objective of improving their performance, power consumption and flexibility. The paper further looks at the evolution of TWSBRs, the problem of stability, and opportunities for neuromorphic computing. The integration is supposed to enhance the sensory acquisition and processing in real time, control adaptability, energy consumption, and insensitivity to external disturbances. Neural networks are implemented in the proposed neuromorphic TWSBR architecture with the use of Spiking neural networks (SNNs) and event-based sensors. This could make a lot of things better, such as self-driving delivery systems, industrial automation, and personal mobility.