Bio-inspired autonomous navigation system for logistics mobile robots with inertial AHRS

Abstract

Implementing the neural mechanism of animal cognition in mobile robots control is a natural way to make the development of bio-inspired autonomous robots with more robust functionality. The neuroscience researches confirm that grid cells play a special role in animals' spatial navigation. This paper presents a design scheme that implements the continuous attractor neural network model of grid cells in mobile robots' navigation control with an attitude and heading reference systems (AHRS) sensor as self-motion sensing component. Based on the design, the autonomous mobile robots could work robustly and well in more flexible and unstructured environments.