The embodiment of the present disclosure provides a robot control method, a robot and a storage medium. In the embodiment of the present disclosure, the robot determines a position when the robot is released from being hijacked based on relocalization operation; determines a task execution area according to environmental information around the position when the robot is released from being hijacked; and afterwards executes a task within the task execution area. Thus, the robot may flexibly determine the task execution area according to the environment in which the robot is released from being hijacked, without returning to the position when the robot is hijacked, to continue to execute the task, then acting according to local conditions is realized and the user requirements may be met as much as possible.

Provided are a robot cleaner and a method for controlling the same, which are capable of determining the presence or absence of a liquid based on an image captured by a camera. The robot cleaner includes a cleaner body including a traveling part, a camera provided on one surface of the cleaner body and configured to acquire an image of surroundings of the cleaner body, and a controller provided in the cleaner body and configured to control the traveling part. The controller is configured to divide an image acquired by the camera into a plurality of images with respect to a reference line, and determine the presence or absence of a liquid based on two or more images among the plurality of divided images.

A docking station, a mobile robot, and a mobile robot management method for controlling a docking station and a mobile robot are provided. The mobile robot includes a management method wherein, in order to display information associated with a docking station to an output device of a mobile robot or transmit the information to a user terminal device connected to the mobile robot, the mobile robot transmits, to the user terminal device, information received from the docking station.

A robot cleaner according to an embodiment of the present disclosure includes: a light receiving sensor configured to measure a brightness of a floor surface; an illumination part configured to irradiate the floor surface with light; a rotation device connected to the illumination part and configured to adjust a rotational angle of the illumination part; an capturing part configured to capture an image of the floor surface; a memory part that stores the image of the floor surface captured by the capturing part; a driving part including an electric motor and wheels; a vacuum suction part configured to perform a vacuum suction by being supplied with power from the electric motor; and a control part. The control part determines an operation in a capturing mode in the capturing mode and a cleaning mode when a value input from the light receiving sensor is determined to be equal to or lower than a predetermined value.

The present disclosure provides a control method capable of, by using a current value of a nozzle, determining whether a nozzle is separated from a vacuum cleaner and whether the nozzle is reconnected to the vacuum cleaner after separation. To this end, a vacuum cleaner may comprise a nozzle connectable to a suction unit for suctioning dusts. The nozzle may comprise a rotary cleaning unit for applying pressure to a cleaning target surface so as to separate a foreign substance therefrom, and a nozzle motor for driving the rotary cleaning unit. In order to drive the nozzle, a voltage having been controlled by a pulse width modulation (PWM) method is applied, and a measurement unit included in the vacuum cleaner may measure a current value of the nozzle, the current value depending on the applied voltage.

An artificial intelligence (AI) mobile robot and a method of controlling the same for learning an obstacle are configured to capture an image while traveling through an image acquirer, to store a plurality of captured image data, to determine an obstacle from image data, to set a response motion corresponding to the obstacle, and to operate the set response motion depending on the obstacle, and thus, the obstacle is recognized through the captured image data, the obstacle is easily determined by repeatedly learning an image, and the obstacle is determined before the obstacle is detected or from a time point of detecting the obstacle to perform an operation of a response motion, and even if the same detection signal is input when a plurality of different obstacles is detected, the obstacle is determined through the image and different operations are performed depending on the obstacle to respond to various obstacles, and accordingly, the obstacle is effectively avoided and an operation is performed depending on a type of the obstacle.

An artificial intelligence (AI) cleaner according to an embodiment of the present invention may include a memory, a movement detect sensor, a driving unit configured to allow the AI cleaner to be moved, and a processor configured to control the movement sensor to sense a movement of the AI cleaner by a user and acquire a position to which the AI cleaner has moved while the AI cleaner operates at a first cleaning mode and control the driving unit to allow the AI cleaner to clean a priority cleaning area corresponding to the position at a second cleaning mode.

An optical beacon may include a housing, an optical emitter at least partially disposed within the housing, and an optical identifier generator optically coupled to the optical emitter. Light incident on the optical identifier generator may be shaped into at least one optical identifier. The optical identifier may be associated with an action capable of being carried out by a robotic cleaner such that detection of the optical identifier by the robotic cleaner causes the robotic cleaner to carry out the action.

Embodiments of the disclosure relate to a robot cleaner and a controlling method thereof, and more particularly, to a robot cleaner and a traveling algorithm of a robot cleaner having an improved structure. A robot cleaner of the disclosure includes a brush unit having a suction flow path, a body unit configured to have a driving device, and be coupled to the brush unit to be rotatable with respect to the brush unit and a redirection device configured to rotate the body unit relative to the brush unit, and the redirection device includes a rotation guide extending along an inner circumferential surface of the brush unit, a rotation driving source disposed in the body unit and generating power, and a power transmission member which moves along the rotation guide by the power transmitted from the rotation driving source and rotates the body unit with respect to the brush unit.

A floor processing device has a floor processing element, a detection device for detecting a surface parameter of the floor surface, and a data processing device. The data processing device has a data memory, which stores a recommended use belonging to a surface parameter of the floor surface for using a specific floor processing element. The data processing device retrieves the recommended use from the data memory and transmits it to a user via an interface. The data processing device compares the size of a first surface area that has a first surface parameter with the size of the remaining surface areas of the environment, which have a surface parameter that deviates from the first surface parameter, and retrieves the recommended use from the data memory corresponding to the surface parameter that corresponds to the largest surface portion from the entirety of the surface areas.