Abstract: 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.

Abstract: A 3D object tracking method and apparatus in which a model of an object to be tracked is divided into a plurality of polygonal planes and the object is tracked using texture data of the respective planes and geometric data between the respective planes to enable more precise tracking. The 3D object tracking method includes modeling the object to be tracked to generate a plurality of planes, and tracking the plurality of planes, respectively. The modeling of the object includes selecting points from among the plurality of planes, respectively, and calculating projective invariants using the selected points.

Abstract: An apparatus and method for detecting movement errors due to the wheel slip or transient current generated while a mobile robot is traveling. The movement error detecting method includes: detecting movement of the wheels in a sensor part according to a movement command input to a drive motor, and outputting an actual output value from the sensor part; calculating an ideal output value for output from the sensor part as the wheels are moved according to the movement command; and comparing the actual output value with the ideal output value to determine and residual fault and detect movement errors.

Abstract: A method of extracting a three-dimensional (3D) edge is based on a two-dimensional (2D) intensity image and a depth image acquired using a time of flight (TOF) camera. The 3D edge extraction method includes acquiring a 2D intensity image and a depth image using a TOF camera, acquiring a 2D edge image from the 2D intensity image, and extracting a 3D edge using a matched image obtained by matching the 2D intensity image and the depth image.

Abstract: An image-based localization feature point registration apparatus includes a camera to capture an image, a feature point extractor to extract a feature point from the captured image, a calculator to calculate depth information about the feature point according to whether the feature point is one of two-dimensional (2D) and a three-dimensional (3D) corner, and a feature point register to register 3D coordinates of the feature point based on the depth information about the feature point and image coordinates of the feature point.

Abstract: An augmented reality (AR) service apparatus includes a camera to capture an actual image, a controller to receive feature point information about the captured image from at least one of a plurality of base stations (BSs), detect a location of the camera by matching data of feature points with data of the image, and provide location-based information in a same direction as the captured image according to the location of the camera, and a display to realize an AR service by combining the captured image with the location-based information under control of the controller.

Abstract: Two-dimensional image information and three-dimensional image information of a subject are acquired, facial recognition is performed using the two-dimensional image information to determine whether a recognized face is a registered user's face, an elliptical model of the user is matched to the three-dimensional image information to calculate an error if it is determined that the recognized face is the user's face, and it is determined whether the user's face is improperly used based on the error. The subject's face is determined using the two-dimensional image information and the three-dimensional image information of the subject and it is determined whether the recognized face is improperly used, thereby improving facial recognition reliability. Thus, information security is improved.

Abstract: Disclosed herein are a markerless augmented reality system and method for extracting feature points within an image and providing augmented reality using a projective invariant of the feature points. The feature points are tracked in two images photographed while varying the position of an image acquisition unit, a set of feature points satisfying a plane projective invariant is obtained from the feature points, and augmented reality is provided based on the set of feature points. Accordingly, since the set of feature points satisfies the plane projective invariant even when the image acquisition unit is moved and functions as a marker, a separate marker is unnecessary. In addition, since augmented reality is provided based on the set of feature points, a total computation amount is decreased and augmented reality is more efficiently provided.

Abstract: Disclosed herein is a computer-readable medium and method of a mobile platform detecting and tracking dynamic objects in an environment having the dynamic objects. The mobile platform acquires a three-dimensional (3D) image using a time-of-flight (TOF) sensor, removes a floor plane from the acquired 3D image using a random sample consensus (RANSAC) algorithm, and individually separates objects from the 3D image. Movement of the respective separated objects is estimated using a joint probability data association filter (JPDAF).

Abstract: Disclosed herein are a method and apparatus for extracting feature points using hierarchical image segmentation and an image based localization method using the extracted feature points. An image is segmented using an affinity degree obtained using information observed during position estimation, new feature points are extracted from segmented areas in which registered feature points are not included, and position estimation is performed based on the new feature points. Accordingly, stable and reliable localization may be performed.

Abstract: Disclosed herein are a feature point used to localize an image-based robot and build a map of the robot and a method of extracting and matching an image patch of a three-dimensional (3D) image, which is used as the feature point. It is possible to extract the image patch converted into the reference image using the position information of the robot and the 3D position information of the feature point. Also, it is possible to obtain the 3D surface information with the brightness values of the image patches to obtain the match value with the minimum error by a 3D surface matching method of matching the 3D surface information of the image patches converted into the reference image through the ICP algorithm.

Abstract: Disclosed herein is a method of building a map of a mobile platform moving in a dynamic environment and detecting an object using a 3D camera sensor, e.g., an IR TOF camera sensor, for localization. A localization technology to separate and map a dynamic object and a static object is applied to a mobile platform, such as an unmanned vehicle or a mobile robot. Consequently, the present method is capable of accurately building map information based on the static object in a dynamic environment having a large number of dynamic objects and achieving a dynamic object avoidance or chasing function using position information acquired to build the map.

Abstract: A method and apparatus to build a 3-dimensional grid map and a method and apparatus to control an automatic traveling apparatus using the same. In building a 3-dimensional map to discern a current location and a peripheral environment of an unmanned vehicle or a mobile robot, 2-dimensional localization and 3-dimensional image restoration are appropriately used to accurately build the 3-dimensional grid map more rapidly.

Abstract: An apparatus and a method of locating a moving robot are disclosed. The apparatus includes a storage unit storing information on straight lines of wall on a map, a state quantity detection unit detecting quantity of state of the robot running along the wall, and a control unit estimating an interior position of the robot by obtaining straight line information based on the detected state quantity and matching the obtained straight line information with the stored straight line information.

Abstract: Disclosed are a robot, which builds a map using a surface data of a three-dimensional image, from which a dynamic obstacle is removed, and a method of building a map for the robot. The method includes sequentially acquiring first and second surface data of a route on which the robot moves; matching the first and second surface data with each other to calculate a difference between the first and second surface data; detecting a dynamic obstacle from the first and second surface data according to the difference between the first and second surface data; generating a third surface data by removing the dynamic obstacle from at least one of the first and second surface data; and matching the third surface data and any one of the first and second surface data with each other to build the map.

Abstract: An apparatus and method for detecting movement errors due to the wheel slip or transient current generated while a mobile robot is traveling. The movement error detecting method includes: detecting movement of the wheels in a sensor part according to a movement command input to a drive motor, and outputting an actual output value from the sensor part; calculating an ideal output value for output from the sensor part as the wheels are moved according to the movement command; and comparing the actual output value with the ideal output value to determine and residual fault and detect movement errors.