Samsung Electronics Co., Ltd.

Korea Advanced Institute of Science and Technology

Soonhyuk Hong

Minjeong Kang

Sejin Kwak

Junghwan Lee

Hyeon Koon Myeong

Haedong Yeo

Eunseo Kim

Daehun Kim

Seungwon Song

Jongmyeong Ban

Saeyoung Kim

Hansung Lee

Hyongjin Kim

Jieum Hyun

Shivam Garg

A method, performed by a cleaning robot, of performing a task, is provided. The method includes capturing an image of an object in a vicinity of the cleaning robot, determining a task to be performed by the cleaning robot, by applying the captured image to at least one trained artificial intelligence (AI) model, controlling a guard portion to descend from in front of an opened portion to a floor surface of the cleaning robot, according to the determined task, and driving towards the object so the object is moved by the descended guard portion.

Cleaning robot and method of performing task thereof

A task performing method for a cleaning robot, according to the disclosure, comprises the operations of: photographing an object in proximity to the cleaning robot includes obtaining recognition information of the object included in the photographed image, by applying the photographed image to a trained artificial intelligence model, obtaining, from among a plurality of sensors, additional information of the object by using a result obtained by detecting the object by at least one sensor selected, based on the recognition information of the object, and performing a task of the cleaning robot based on the additional information of the object. The trained artificial intelligence model, for example, a deep learning neural network model, in which a plurality of network nodes having weights are located in different layers so as to exchange data according to a convolution relationship, can be used, but is not limited to the aforementioned example.

Cleaning robot and task performing method therefor

The present invention relates to a robot and a control method therefor and, more particularly, to a robot and a control method therefor, the robot detecting peripheral obstacles and structures by using an image in front of same, thereby providing an efficient and safe moving path. A robot control method according to one embodiment of the present invention comprises the steps of: capturing an image; acquiring a first image of which the bottom surface is separated in the image; recognizing obstacles included in the image by using a learned first artificial intelligence model; allowing a robot to acquire and store a second image in order to perform a task on the basis of the information about the first image and the region including the recognized obstacles; and allowing the robot to move on the basis of the second image.

Robot and control method therefor

A method for performing a task of a cleaning robot is provided. The method according to an embodiment includes generating a navigation map for driving the cleaning robot using a result of at least one sensor detecting a task area in which an object is arranged, obtaining recognition information of the object by applying an image of the object captured by at least one camera to a trained artificial intelligence model, generating a semantic map indicating environment of the task area by mapping an area of the object included in the navigation map with the recognition information of the object, and performing a task of the cleaning robot based on a control command of a user using the semantic map. An example of the trained artificial intelligence model may be a deep-learning neural network model in which a plurality of network nodes having weighted values are disposed in different layers and exchange data according to a convolution relationship, but the disclosure is not limited thereto.

Cleaning robot and method for performing task thereof

Provided are a mobile robot device and a control method thereof. The mobile robot device comprises: a driving unit; an image sensor; a plurality of geomagnetic sensors; a memory for storing at least one instruction; and a processor for executing at least one instruction, wherein the processor may obtain, while the mobile robot device moves by means of the driving unit, a plurality of image data through the image sensor and obtain sensing data through the plurality of geomagnetic sensors, extract a feature point from the plurality of image data and obtain key nodes on the basis of the feature point, obtain a node sequence on the basis of the sensing data, generate a graph structure that estimates a position of the mobile robot device on the basis of the key nodes and the node sequence, and correct the graph structure based on the mobile failing in position recognition.

Mobile robot device for correcting position by fusing image sensor and plurality of geomagnetic sensors, and control method

The present disclosure relates to a tag and a method, performed by the tag, of transmitting a response signal to a tag search signal. Specifically, the disclosed method of transmitting a response signal includes operations of receiving, from at least one of a plurality of slave nodes, the tag search signal including identification data for identifying the tag, charging an energy storage element in the tag by using the received tag search signal, obtaining the identification data for identifying the tag from the received tag search signal, determining whether the obtained identification data matches identification information previously stored in the tag, and outputting a response signal to the tag search signal when the energy storage element is charged greater than a predetermined value and the obtained identification data matches the identification information previously stored in the tag.

Image-capturing device and method for controlling same

A method of controlling a robot includes obtaining a first image and a second image of a plurality of objects, the first and second image being captured from different positions; obtaining, from the first and second images, a plurality of candidate positions corresponding to each of the plurality of objects, based on a capturing position of each of the first and second images and a direction to each of the plurality of objects from each capturing position; obtaining distance information between each capturing position and each of the plurality of objects in the first and second images by analyzing the first and second images; and identifying a position of each of the plurality of objects from among the plurality of candidate positions based on the distance information.

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Suwon-si, South Korea

Soonhyuk Hong