Abstract:
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.
Abstract:
An electronic device, capable of being placed on a cradle, may include a camera module configured to acquire an image, a sensor module configured to sense information regarding an orientation of the electronic device, a processor configured to determine a target orientation of the electronic device based on the acquired image and a communication module configured to transmit the information regarding the orientation of the electronic device and information regarding the target orientation of the electronic device to the cradle.
Abstract:
A robot cleaner and a method for controlling the same are disclosed. The robot cleaner includes a main body; a driver configured to move the main body; a storage configured to store a topological map and a grid map generated on the basis of a floor plan of a cleaning space; and a controller configured to control the driver in a manner that the main body travels in the cleaning space on the basis of the topological map and the grid map. The topological map and the grid map are generated prior to initial traveling of the cleaning space.
Abstract:
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.
Abstract:
A mobile robot configured to move on a ground. The mobile robot including a contact angle estimation unit estimating contact angles between wheels of the mobile robot and the ground and uncertainties associated with the contact angles, a traction force estimation unit estimating traction forces applied to the wheels and traction force uncertainties, a normal force estimation unit estimating normal forces applied to the wheels and normal force uncertainties, a friction coefficient estimation unit estimating friction coefficients between the wheels and the ground, a friction coefficient uncertainty estimation unit estimating friction coefficient uncertainties, and a controller determining the maximum friction coefficient from among the friction coefficients such that the maximum friction coefficient has an uncertainty less than a threshold and at a point of time when the torque applied to each of the wheels changes from an increasing state to a decreasing state, among the estimated friction coefficients.
Abstract:
An image processing apparatus for searching for a feature point by use of a depth image and a method thereof are provided. The image processing apparatus includes an input unit configured to input a three-dimensional image having depth information, a feature point extraction unit configured to obtain a designated point from an object image extracted from the depth image to obtain a feature point that is located at a substantially farthest distance from the designated point, and to obtain other feature points that are located at substantially farthest distances from feature points that are previously obtained as well as the designated point. The apparatus includes a control unit configured to control the input unit and the feature point extraction unit so that time in estimating a structure of the object is reduced, and a recognition result is enhanced.
Abstract:
A robot cleaner includes a traveling unit to move a main body, an obstacle sensing unit to sense an obstacle, a light reception unit to receive modulated light according to a control command of a user, and a controller to control the traveling unit so that the main body traces a light spot formed by the light. If an obstacle is detected, the controller controls the traveling unit such that the main body traces an outline of the obstacle according to the light spot position and the obstacle position.
Abstract:
A face recognition apparatus and face recognition method perform face recognition of a face by comparing an image of the face to be identified with target images for identification. The face recognition apparatus includes an image input unit to receive an image of a face to be identified, a sub-image production unit to produce a plurality of sub-images of the input face image using a plurality of different face models, a storage unit to store a plurality of target images, and a face recognition unit to set the sub-images to observed nodes of a Markov network, to set the target images to hidden nodes of the Markov network, and to recognize the presence of a target image corresponding to the face images to be identified using a first relationship between the observed nodes and the hidden nodes and a second relationship between the hidden nodes.
Abstract:
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.
Abstract:
A home robot device includes a memory, a movement module, and a processor. The processor is configured to execute a motion based on specified motion execution information stored in the memory, obtain feedback information of a user, generate modified motion execution information by modifying at least a portion of the specified motion execution information based on the feedback information of the user, where the modified motion execution information includes a movement value of at least one joint unit of the home robot device or at least one support linked to the at least one joint unit selected from a probability model of the specified motion execution information, and execute a motion of the home robot device based on the modified motion execution information.