A control method for a robot using an artificial intelligence model, the control method comprising: acquiring user data related to at least one user; training the artificial intelligence model to acquire an emotional state for each of the at least one user by inputting the user data related to the at least one user to the artificial intelligence model as learning data, the user data comprising at least one image data including a user; wherein the training of the emotional state includes clustering a plurality of learning data into a plurality of clusters by inputting the plurality of learning data into the artificial intelligence model; and labeling the emotional state corresponding to each of the plurality of clusters; determining, based on acquiring first user data related to a first user, a first labeled emotional state of the first user by inputting the first user data to the trained artificial intelligence model; controlling the robot to output a first representative reaction based on the first emotional state; determining a character of the robot based on a character area of a character model including a first axis indicating whether an emotion of the robot is positive or negative and a second axis indicating an activity of the robot, wherein the character area of the character model is determined based on a feedback of the first user for the first representative reaction, the number of times the user and the robot have interacted, the first emotional state for a robot reaction, and the degree of completion of the robot reaction for the user reaction; determining, based on acquiring second user data related to the first user, a second labeled emotional state of the first user by inputting the second user data to the trained artificial intelligence model; and controlling the robot to output a second representative reaction based on the second emotional state and the character of the robot. acquiring user data related to at least one user; training the artificial intelligence model to acquire an emotional state for each of the at least one user by inputting the user data related to the at least one user to the artificial intelligence model as learning data, the user data comprising at least one image data including a user; wherein the training of the emotional state includes clustering a plurality of learning data into a plurality of clusters by inputting the plurality of learning data into the artificial intelligence model; and labeling the emotional state corresponding to each of the plurality of clusters; determining, based on acquiring first user data related to a first user, a first labeled emotional state of the first user by inputting the first user data to the trained artificial intelligence model; controlling the robot to output a first representative reaction based on the first emotional state; determining a character of the robot based on a character area of a character model including a first axis indicating whether an emotion of the robot is positive or negative and a second axis indicating an activity of the robot, wherein the character area of the character model is determined based on a feedback of the first user for the first representative reaction, the number of times the user and the robot have interacted, the first emotional state for a robot reaction, and the degree of completion of the robot reaction for the user reaction; determining, based on acquiring second user data related to the first user, a second labeled emotional state of the first user by inputting the second user data to the trained artificial intelligence model; and controlling the robot to output a second representative reaction based on the second emotional state and the character of the robot.