A Chewing Robot to Assist Quantitative Food Analysis: Kinematics and Fuzzy Scheduling Control

Quantifying mastication using parameters of chewing movement, such as teeth trajectories and phase durations, has drawn substantial attention in food science. A number of chewing robots have been developed to assist scientists in carrying out this investigation objectively and efficiently. However, a life-sized jaw structure and complex spatial jaw motion are not practical for the purpose of comminuting food samples, while the mechanisms with practical functions to deal with the food have to compromise the similarity of human jaw and oral anatomy. For a robot to analyze food, a relatively simple but reliable structure is often adopted to perform repetitive chewing, but it has limited motion flexibility and thus fails to mimic human chewing where a lot of chewing features are required. A newly designed chewing robot, based on an adjustable linkage mechanism, can provide molar crushing and grinding on food while allowing the users to customize the molar movement. This article discusses the robot's movement with user-specified molar paths and chewing phase durations. Two types of movements are planned for the operation of the robot, one that chooses the molar paths from a library and specifies the durations, whereas the other one using a measured human chewing profile as a reference to come up with the robot's movement. In order to carry out robotic chewing, the kinematics of the adjustable linkage is developed to express the relationship between the actuators and the robot's molar movement. An adaptive fuzzy scheduling control is proposed to reduce the error of crank movement during the operation. Experiments are carried out to validate the effectiveness of the planning and control.

Automated summary

This article introduces a chewing robot based on an adjustable linkage mechanism, which can provide crushing and grinding capability on food and allows users to customize the movement of the molars. The article discusses the robot's movement and two different operation modes, and validates the effectiveness of the planning and control through experiments.