Abstract: A robot control method and a robot are disclosed. The robot control method and the robot configured to perform the method may communicate with other electronic devices and a server in a 5G communication environment, and determine an operator to assist in performance of a subtask according to a difficulty level of the subtask.

Abstract: The present disclosure provides a method for controlling a robot cleaner including a travel operation in which the robot cleaner travels, a recognition operation in which when the robot cleaner contacts an obstacle during the travel, the robot cleaner determines whether the obstacle is pushed by the robot cleaner and slides, and an obstacle bypass operation in which upon determination that the obstacle is the pushed-and-sliding obstacle, the robot cleaner stops the travel and then bypasses the pushed-and-sliding obstacle.

Abstract: A cart robot analyzing a hand motion of a user is disclosed. The cart robot comprises a code input interface obtaining a product identification code, a sensor detecting a hand motion of a user, a weight measuring device measuring a weight of one or more products contained in a product loading space, and a controller. When there is no change in weight of the loaded products, the cart robot updates a shopping list with respect to the products loaded in the product loading space in real time by analyzing the hand motion of the user. Therefore, the convenience of the user is enhanced.

Abstract: A robot system includes a robot arm configured to tilt a fry basket in a first direction or in a second direction different from the first direction or lift up or lower the fry basket and a controller configured to perform a residue removal mode in which the robot arm rotates and moves the fry basket to a set residue removal path in which residue in a fryer is sifted out.

Abstract: Disclosed is a robot and a control method thereof. The robot includes: a camera configured to acquire a depth image of a specific area; a processor configured to create an elevation map for the specific area based on the depth image, and determine whether a head of a person is in the specific area based on the elevation map. The processor, when determining whether the head of the person is in the specific area, is further configured to partition pixels of the elevation map into floor pixels corresponding to a floor area and non-floor pixels corresponding to a non-floor area using elevation values of the elevation map, set paths through the elevation map with a subset of the non-floor pixels as starting points for the paths, and determine whether the head of the person is in the specific area based on whether the paths converge.