Samsung Electronics Co., Ltd.

Korea Advanced Institute of Science and Technology

Sung Hwan Ahn

Suk June Yoon

Kyung Shik Roh

Seung Yong Hyung

Hyo Seok Hwang

No San Kwak

Young Do Kwon

Won Jun Hwang

Soon Yong Park

Young Bo Shim

Suk Hoon Jung

Dong Soo Han

Byeong Cheol Moon

Woong Kwon

Soon Ryong Park

Hyun Kyu Kim

Hyung Sok Yeo

So Hee Lee

Ji Hyo Lee

Min Yong Choi

Sang Il Hong

Seong Yong Hyung

Young Pil Jeon

Sang Ll Hong

A server may include a communication circuit communicating with a user terminal, storage including a fingerprint DB storing fingerprints corresponding to a plurality of points and a signal fluctuation probability DB, and a processor electrically connected to the communication circuit and the storage. The processor may be configured to store similarity between first signal strength and second signal strength, which are determined based on a probability that a pair of the first signal strength and the second signal strength received from a first AP occurs with respect to fingerprints corresponding to a first point, in the signal fluctuation probability DB, to obtain a fingerprint including signal strength received from the first AP, from the user terminal, and to determine a location of the user terminal based on the obtained fingerprint and the signal fluctuation probability DB.

Method for providing location information and apparatus therefor

Disclosed herein are a movable object and a movable object control method. The movable object control method may include acquiring an image of a movable object's surroundings, acquiring a signal having strength changing depending on a location of the movable object, generating a map on the basis of the signal and the image of the surroundings of the movable object, and applying the map to an algorithm to acquire a learned algorithm.

Movable object and control method thereof

Embodiments of the present disclosure relate to a movable object and a method for controlling the same. A method for controlling a movable object may include acquiring virtual data representing distances between each of a plurality of positions within an area and surfaces in the area, in a plurality of directions, respectively, based on a map of the area. An algorithm, such as a machine learning algorithm, may be executed that outputs positions corresponding to the virtual data. Actual distance data between the movable object and a plurality of surfaces in the vicinity of the movable object may be acquired. An actual position of the movable object may then be estimated corresponding to the actual distance data by executing the algorithm using the actual distance data. The movable object may be controlled based on the estimated actual position.

Movable object and method for controlling the same

A robot for performing hand-eye calibration is provided. The robot includes a robot arm including a plurality of joints, a plurality of arm sections, and an end effector, a communication interface, and a control circuit. The control circuit controls the robot arm to place the external object on a worktable after the external object is grasped by the end effector, acquires coordinates of a central point of the external object in a coordinate system of the camera from an image of the external object, and calculates a calibration parameter for defining a relation between a coordinate system of the end effector and the coordinate system of the camera, based on coordinates of the end effector in a base coordinate system of the robot and coordinates of the central point of the external object in the coordinate system of the camera when the external object is placed on the worktable.

Robot and electronic device for performing hand-eye calibration

Disclosed herein are an endoscope system and a control method thereof. The control method includes acquiring plural omnidirectional images of the surroundings of an endoscope using a stereo omnidirectional camera mounted on the endoscope, calculating distances between the endoscope and an object around the endoscope using the acquired plural omnidirectional images, and executing an operation to avoid collision between the endoscope and the object around the endoscope based on the calculated distances, thus facilitating safe operation of the endoscope.

Endoscope system and control method thereof

Surgical trocars, and image acquisition method using the same, include a body having a passage configured to receive at least one surgical instrument, and at least one camera movably coupled to an outer wall of the body.

Surgical trocars and image acquisition method using the same

Provided are a walk-assistive robot and a method of controlling the same. The method of controlling the walk-assistive robot includes: obtaining ground information that is information regarding ground a walking direction; determining control patterns of the walk-assistive robot by analyzing the obtained ground information; and controlling the walk-assistive robot based on the determined control patterns.

Walk-assistive robot and method of controlling the same

A control method of a walking assist robot, may include: estimating a wearer's location on a map including walking environment information; determining a walking environment in a direction in which the wearer moves; and selecting a control mode for assisting the wearer's walking according to the walking environment.

Walking assist robot and control method thereof

Disclosed herein is a control method of a robot including: calculating hardness information about the ground on which a wearer moves; and controlling the robot according to the calculated hardness information.

Robot and control method thereof

A mobile apparatus and a localization method thereof which perform localization of the mobile apparatus using a distributed filter system including a plurality of local filters independently operated and one fusion filter integrating results of localization performed through the respective local filters, and additionally apply accurate topological absolute position information to the distributed filter system to improve localization performance (accuracy, convergence and speed in localization, etc.) of the mobile apparatus on a wide space. The mobile apparatus includes at least one sensor, at least one first distribution filter generating current relative position information using a value detected by the at least one sensor, at least one second distribution filter generating current absolute position information using the value detected by the at least one sensor, and a fusion filter integrating the relative position information and the absolute position information to perform localization.

Mobile apparatus and localization method thereof

A method of recognizing stairs in a 3D data image includes an image acquirer that acquires a 3D data image of a space in which stairs are located. An image processor calculates a riser height between two consecutive treads of the stairs in the 3D data image, identifies points located between the two consecutive treads according to the calculated riser height, and detects a riser located between the two consecutive treads through the points located between the two consecutive treads. Then, the image processor calculates a tread depth between two consecutive risers of the stairs in the 3D data image, identifies points located between the two consecutive risers according to the calculated tread depth, and detects a tread located between the two consecutive risers through the points located between the two consecutive risers.

Method of recognizing stairs in three dimensional data image

A robot and a method for creating a robot path. The method for planning the robot path includes generating a depth map including a plurality of cells by measuring a distance to an object, dividing a boundary among the plurality of cells into a plurality of partitions according to individual depth values of the cells, and extracting a single closed loop formed by the divided boundary, obtaining a position and shape of the object located at a first time through the extracted single closed loop, calculating a probability that the object is located at a second time after t seconds on the basis of the obtained position and shape of the object located at the first time, and creating a moving path simultaneously while avoiding the object according to the calculated probability, thereby creating an optimum path without colliding with the object.

Robot and method for creating path of the robot

A moving robot and a method to build a map for the same, wherein a 3D map for an ambient environment of the moving robot may be built using a Time of Flight (TOF) camera that may acquire 3D distance information in real time. The method acquires 3D distance information of an object present in a path along which the moving robot moves, accumulates the acquired 3D distance information to construct a map of a specific level and stores the map in a database, and then hierarchically matches maps stored in the database to build a 3D map for a set space. This method may quickly and accurately build a 3D map for an ambient environment of the moving robot.

Moving robot and method to build map for the same

A method of controlling a mobile apparatus includes acquiring a first original image and a second original image, extracting a first feature point of the first original image and a second feature point of the second original image, generating a first blurring image and a second blurring image by blurring the first original image and the second original image, respectively, calculating a similarity between at least two images of the first original image, the second original image, the first blurring image, and the second blurring image, determining a change in scale of the second original image based on the calculated similarity, and controlling at least one of an object recognition and a position recognition by matching the second feature point of the second original image to the first feature point of the first original image based on the change in scale.

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Anyang-si, South Korea

Sung Hwan Ahn