Unconventional Cognitive Intelligent Robotic Control: Quantum Soft Computing Approach in Human Being Emotion Estimation -- QCOptKB Toolkit Application

TL;DR

This paper presents a novel quantum soft computing approach for enhancing cognitive robotic control, focusing on emotion estimation and robust hazard management using quantum fuzzy inference and neuro-interface integration.

Contribution

It introduces a quantum fuzzy inference gate design and demonstrates its application in cognitive control systems and neuro-interfaces for robots and vehicles.

Findings

Improved robustness of cognitive control in hazard situations

Successful implementation of quantum fuzzy inference in embedded systems

Potential for neuro-interface applications in vehicle control

Abstract

Strategy of intelligent cognitive control systems based on quantum and soft computing presented. Quantum self-organization knowledge base synergetic effect extracted from intelligent fuzzy controllers imperfect knowledge bases described. That technology improved of robustness of intelligent cognitive control systems in hazard control situations described with the cognitive neuro-interface and different types of robot cooperation. Examples demonstrated the introduction of quantum fuzzy inference gate design as prepared programmable algorithmic solution for board embedded control systems. The possibility of neuro-interface application based on cognitive helmet with quantum fuzzy controller for driving of the vehicle is shown.