A Use of Fuzzy Logic Based Decision Making tree for Developing Smart Healthcare System

Abstract

in order to improve the flexibility and adaptation of the omnidirectional mobile robot in dynamic situations, this work provides a hierarchical control strategy with an emphasis on point stability. It is believed that in order for robotic systems to function well during the sense-plan-act cycle, they must be flexible and adaptable. The recommended control structure makes use of a behavior fuzzy decision tree (bt) that integrates high-level decision-making with continuous execution monitoring. Moreover, it incorporates non-linear model predictive control (nmpc) for point stabilization of the mobile robotic healthcare system. The robot’s architecture enables it to operate in many configurations inside the workspace, all the while adhering to input and state constraints, including obstacle avoidance and motor restrictions. The efficacy was confirmed in realistic simulation scenarios and with an industrial omni-directional mobile robot operating in an actual environment, executing point stabilization and obstacle avoidance.