Multimodal Sensors Integration in Robotic Mastication Simulator for Comprehensive Food Texture Analysis

Recent improvements in robotic mastication simulator technology have significantly advanced the replication of human oral food processing. However, their sensory capabilities remain limited, with most systems only relying on elementary motion and force measurements. This research proposes the development and integration of a comprehensive multimodal sensory system for an established robotic mastication simulator. By incorporating acoustic, visual, moisture, and thermal sensors with conventional force measurements, the system aims to achieve sophisticated bionic sensory perception of food oral processing. The proposed system enables simultaneous acquisition of multiple data streams during mastication, enabling holistic texture characterization via multidimensional analysis. This improvement represents a significant advancement toward more intelligent robotic mastication simulators with applications in oral processing technology and food texture science. The methodology includes sensor integration, temporal synchronization, and validation. This research addresses a critical gap between mechanical and sensory capabilities in mastication simulators.