Unconventional Cognitive Intelligent Robotic Control: Quantum Soft Computing Approach in Human Being Emotion Estimation -- QCOptKB Toolkit Application
This work addresses hazard control in robotics and vehicles, but appears incremental as it builds on existing quantum and soft computing methods.
The paper tackles the problem of improving robustness in intelligent cognitive control systems for hazard situations by introducing a quantum soft computing approach, resulting in the development of a quantum fuzzy inference gate design and a neuro-interface for vehicle driving.
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.