Lg Electronics Inc.

Lg Etectronics Inc.

Seungwook Lim

Dongki Noh

Taekyeong Lee

Gyuho Eoh

Jaekwang Lee

Inbo Shim

Kahyung Choi

A controlling method for an artificial intelligence moving robot according to an aspect of the present disclosure includes: checking nodes within a predetermined reference distance from a node corresponding to a current position; determining whether there is a correlation between the nodes within the reference distance and the node corresponding to the current position; determining whether the nodes within the reference distance are nodes of a previously learned map when there is no correlation; and registering the node corresponding to the current position on the map when the nodes within the reference distance are determined as nodes of the previously learned map, thereby being able to generate a map in which the environment of a traveling section and environmental changes are appropriately reflected.

Controlling method for artificial intelligence moving robot

A method of controlling a mobile robot includes a first basic learning process of generating a first basic map based on environment information acquired in a traveling process, a second basic learning process of generating a second basic map based on environment information acquired in a separate traveling process, and a merging process of merging the first basic map and the second basic map to generate a merged map.

Method of controlling mobile robot

A mobile robot includes a traveling unit configured to move a main body, a LiDAR sensor configured to acquire geometry information, a camera sensor configured to acquire an image of the outside of the main body, and a controller. The controller generates odometry information based on the geometry information acquired by the LiDAR sensor. The controller determines a current location of the mobile robot by performing feature matching between images acquired by the camera sensor based on the odometry information. The controller combines the information obtained by the camera sensor and the LiDAR sensor to accurately determine the current location of the mobile robot.

Mobile robot and method of controlling the same

A mobile robot and a method of controlling the mobile robot are disclosed. The method includes acquiring an image of an inside of a traveling zone. The method further includes performing a point-based feature point extraction by extracting a first feature point from the acquired image. The method also includes performing a block-based feature point extraction by dividing the acquired image into blocks having a predetermined size and extracting a second feature point from each of the divided block-unit images. The method also includes determining the current location by performing a point-based feature point matching using the first feature point and performing a block-based feature point using the second feature point. The method also includes storing the determined current location in association with the first feature point and the second feature point in a map.

Mobile robot control method

A method of controlling a mobile robot includes a learning initial operation of acquiring images for respective points, generating descriptors that respectively correspond to a plurality of feature points extracted from the images, and generating nodes that correspond to the images acquired at the respective points, a label generation operation of generating a label descriptor based on the plurality of descriptors, a localization initial operation of acquiring a localization image when a jumping case occurs, and generating respective localization descriptors corresponding to a plurality of localization feature points extracted from the localization image, a comparison target selection operation of matching the label descriptor to each of the localization descriptors and selecting one or more comparison target nodes corresponding to the matched label descriptor, and a last node selection operation of selecting a node estimated as the current position among the one or more comparison target node.

A method of controlling a moving-robot includes creating a plurality of maps having different generation-time information through a plurality of driving processes; choosing any one of the plurality of maps according to a certain map choosing algorithm based on current time information and the generation-time information, and attempting location recognition based on the chosen map.

Moving robot and control method for the same

The present invention relates to a moving robot capable of recognizing a position on a map and a control method of the moving robot, and the moving robot according to the present invention includes: a travel drive unit configured to move a main body; an image acquisition unit configured to acquire images of surroundings; and a controller configured to recognize a current position. The controller is further configured to separate the travel area by the predetermined criterion into a plurality of large areas, into which the plurality of small areas is grouped; compute each large area feature distribution and the at least one recognition descriptor by a predetermined superordinate estimation rule to select a large area in which the current position is included; and compute the small area feature distribution and the at least one recognition descriptor by the predetermined estimation rule to select a small area, in which the current position is included, from among a plurality of small areas included in the selected large area. The control method according to the present invention includes: a learning process of learning a travel area to generate a map and separating the travel area into a plurality of small areas by a predetermined criterion; and a recognition process of selecting a current position on the map. The recognition process includes: a recognition descriptor generation process of acquiring an image of the current position, extract at least one recognition feature from the acquired image, and generating a recognition descriptor corresponding to the at least one recognition feature. The recognition process includes: a large area selection process of computing each large area feature distribution and the at least one recognition descriptor by a predetermined superordinate estimation rule to select a large area in which the current position is included.

Mobile robot and mobile robot control method

A control method for a robot cleaner includes acquiring a plurality of images of surroundings during travel of the robot cleaner in a cleaning area, estimating a plurality of room-specific feature distributions according to a rule defined for each of a plurality of rooms, based on the images acquired while acquiring the plurality of images, acquiring an image of surroundings at a current position of the robot cleaner, obtaining a comparison reference group including a plurality of room feature distributions by applying the rule for each of the plurality of rooms to the image acquired while acquiring the image at the current position, comparing the obtained comparison reference group with the estimated room-specific feature distributions, and determining a room from the plurality of rooms having the robot cleaner currently located therein.

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Seoul, South Korea

Seungwook Lim