###### Abstract  
Various meal-assistance robot (MAR) systems are being studied, and several products have already been commercialized to alleviate the imbalance between the rising demand and diminishing supply of meal care services. However, several challenges remain. First, most of these services can serve limited types of western food using a predefined route. Additionally, their spoon or fork sometimes makes it difficult to acquire Asian food that is easy to handle with chopsticks. In addition, their limited user interface, requiring physical contact, makes it difficult for people with severe disabilities to use MARs alone. This paper proposes an MAR system that is suitable for the diet of Asians who use chopsticks. This system uses Mask R-CNN to recognize the food area on the plate and estimates the acquisition points for each side dish. The points become target points for robot motion planning. Depending on which food the user selects, the robot uses chopsticks or a spoon to obtain the food. In addition, a non-contact user interface based on face recognition was developed for users with difficulty physically manipulating the interface. This interface can be operated on the user's Android OS tablet without the need for a separate dedicated display. A series of experiments verified the proposed system's effectiveness and feasibility. meal-assistance robot; deep learning; instance segmentation; human-robot interaction; face recognition 20231332163202313216320231321  
task that requires a lot of time and effort [3]. This situation is similar for those requiring care, who often feel sorry when they receive meal assistance from their family members or caregivers. The fact that they cannot feed themselves can make cause them to feel depressed and not independent. Therefore, if the disabled and the elderly can eat independently, without the help of others, they would maintain their self-esteem and improve their quality of life [4; 5]. In this situation, robots offer alternative solutions to meet the demands of daily problems in various fields [6; 7]. In particular, meal-assistance robots (MARs) have emerged as a solution to replace human caregivers for patients in the field of meal assistance, leading to the development of numerous commercial products and related research. In this work, we would like to introduce a new portable MAR system to alleviate these issues (see Figure 1). This MAR system was invented so that the patient can eat on their own with the help of a robot, only requiring the caregivers to help with the initial setting and finishing of the meal. The MAR has 7-degrees-of-freedom (DOF), which includes a robot arm and controller, food tray, and tablet user interface. For ease of portability, we fabricated the hardware with a total weight of 4.90 kg and designed the system to be suitable for Korean-style meals in hospitals or sanatoriums. We developed software to obtain food acquisition points based on deep learning instance segmentation. Furthermore, we implemented a tablet PC user interface based on face recognition for the severely disabled. Utilizing this MAR system is expected to help ameliorate the lack of caregivers, reduce their burden regarding meal care, and improve caretakers' self-esteem and quality of life by providing better assistance. The various types of MARs that have been presented to date are often operated in a limited laboratory environment or are non-portable. In addition, even commercialized products cannot provide high-quality services due to their functionally low performance and high prices. Furthermore, they do not consider various types of user disabilities and provide only limited user interfaces. These previous studies and their limitations will be dealt with in more detail in the next section, and our proposed MAR system has several points of difference. The major contributions of this article are summarized as follows:  
* Development of a compact and portable meal assistance robot system capable of both food recognition and robot control without external computing.