A Bio Inspired Control Strategy for a Mecanum-Wheeled Robot Position Control

Abstract

As a type of AVG, Mecanum wheel-based mobile robots are used in various logistics areas including factories, medical facilities, and warehouses. Many studies have been conducted to improve the control performance of AGVs such as their perception, localization, path planning and navigation, and motion control systems. Among this broad area of mobile robot research, this paper focuses on a bio-inspired control strategy of brain limbic system-based control that is utilized to control the position of a Mecanum wheel-based mobile robot. The working principle of the brain limbic system-based control strategy is learning from proper connection processes between emotion as the stimulus and behavior as the reaction. After describing the BLS control in greater depth, the application of a BLS controller to a Mecanum wheel robot is suggested. The control parameters of the BLS controller are optimized via a genetic algorithm. Numerical simulations are conducted for comparison with a conventional mobile robot position control algorithm to demonstrate the suggested control method’s performance.