Memristor‐Based Intelligent Human‐Like Neural Computing

TLDR

Humanoid robots aim to emulate human form and function, yet von Neumann architectures limit energy efficiency, latency, and biomimicry, prompting a shift toward sensor‑rich, memristor‑based systems that emulate biological nervous systems. This review surveys biological and memristor‑based nervous systems, detailing their structures and functions. The authors conduct a comprehensive review of biological and memristor‑based nervous system architectures and functionalities. The review outlines current applications of memristor‑based nervous systems, identifies remaining challenges, and projects future developments to advance humanoid robotics.

Abstract

Abstract Humanoid robots, intelligent machines resembling the human body in shape and functions, cannot only replace humans to complete services and dangerous tasks but also deepen the own understanding of the human body in the mimicking process. Nowadays, attaching a large number of sensors to obtain more sensory information and efficient computation is the development trend for humanoid robots. Nevertheless, due to the constraints of von Neumann‐based structures, humanoid robots are facing multiple challenges, including tremendous energy consumption, latency bottlenecks, and the lack of bionic properties. Memristors, featured with high similarity to the biological elements, play an important role in mimicking the biological nervous system. The memristor‐based nervous system allows humanoid robots to obtain high energy efficiency and bionic sensing properties, which are similar properties to the biological nervous system. Herein, this article first reviews the biological nervous system and memristor‐based nervous system thoroughly, including the structures and also the functions. The applications of memristor‐based nervous systems are introduced, the difficulties that need to be overcome are put forward, and future development prospects are also discussed. This review can hopefully provide an evolutionary perspective on humanoid robots and memristor‐based nervous systems.