Modelling Neural Dynamics with Optics: A New Approach to Simulate Spiking Neurons through an Asynchronous Laser

Abstract

In this paper, we propose a novel approach for implementing spiking neurons through an optical system. Spiking neurons are a new approach to emulate the neural processes that occur in the brain, known as the third generation of artificial neural networks. They have been successfully used to build a new technology called neuromorphic engineering, which looks for a better performance than traditional computing in tasks usually performed by AI-based systems. Our optical system consists of a low-cost laser source, based on a microcontroller and a continuous-wave laser diode; the microcontroller allows producing synchronous or asynchronous pulses with complex time profiles. Here, through said system we have successfully reproduced most of the neural dynamics observed in biological neurons. These dynamics have been reproduced using a very simple optical array with a great potential for the development of neuromorphic systems. The optical system has been experimentally validated.

Development of a New Robust Stable Walking Algorithm for a Humanoid Robot Using Deep Reinforcement Learning with Multi-Sensor Data Fusion

“…While humanoid robots are known for their ease and flexibility to move around a wide range of terrain, the main concern is stability as they have a high-dimensional and nonlinear system. Over the years, many control scientists have developed an interest in finding a solution to the stability issue with the bipedal gait system [3].…”