Weight estimation for noodle products in food layout of a home replacement meal

Abstract

There is a growing demand for automation by robots in the home replacement meal industry due to labor shortages in food factories and from the perspective of the SDGs[1]. In this research, we are developing autonomous work robots that can perform home replacement meal tasks and developing the technology for industrial food automation using Artificial Intelligence (AI) to improve productivity, security, and safety. In this paper, we perform weight estimation of the served object to identify the amount of spaghetti grasped by the robot. We created our dataset of spaghetti used for weight estimation. Spaghetti of varying weight is in different types of containers, placed at random positions in the robot workspace. The proposed model is shown to estimate the weight of spaghetti with an error of at most 10%.