Command Feedback System Based on Context Awareness for Minimizing Control Error in Human-Robot Interaction

The advancement in Artificial Intelligence has made it possible to control the robots through intuitive interfaces such as speech and gestures. A robotic control system for human-robot interaction has been developed, enabling robot control using human speech or hand gestures. Speech and gesture recognition technology has become a part of robotic control systems, acting as a bridge for interaction between humans and robots. However, simple robotic control systems process control commands independently, without considering the situation in which the robot is located. This leads to collision risks and a decline in control reliability. This paper introduces a Command Feedback System based on Context Awareness (CFS-CA) to minimize control errors by integrating real-time situational analysis with user commands. The system provides context-aware feedback, enabling more accurate and efficient robotic control. Experiments performed in a virtual environment with seven participants demonstrated that CFS-CA significantly reduces control errors and improves performance across key metrics, including the number of commands, driving time, collisions, and path efficiency, ensuring safer and more reliable robotic control.