Lg Electronics Inc.

Joongtae Park

JungSik Kim

Hyoungrock Kim

Gyuho Eoh

Dong Ki Noh

Sunho Yang

Seungmin Baek

Namjin Kim

Sookhyun Yang

Disclosed herein are a method of updating a map in fusion SLAM and a robot implementing the same, the robot, which updates a map in fusion SLAM using two types of sensors, configured to update a first map with first type information acquired by a first sensor and to estimate a current position of the robot using second type information acquired by a second sensor.

Method of updating map in fusion SLAM and robot implementing same

Disclosed herein is a robot generating a map based on multi sensors and artificial intelligence and moving based on the map, the robot according to an embodiment including a controller generating a pose graph that includes a LiDAR branch including one or more LiDAR frames, a visual branch including one or more visual frames, and a backbone including two or more frame nodes registered with any one or more of the LiDAR frames or the visual frames, and generating orodometry information that is generated while the robot is moving between the frame nodes.

Robot generating map based on multi sensors and artificial intelligence and moving based on map

A mobile robot operation method according to an aspect of the present invention includes: a step for receiving a guidance destination input; a step for generating a global path to the received guidance destination; a step for generating a left travel guideline and a right travel guideline on the left side and the right side of the generated global path; and a step for generating a local path within a travelable range between the left travel guideline and the right travel guideline. Accordingly, the robot operation method may generate a safe and optimal guidance path when providing a guidance service.

Mobile robot operation method and mobile robot

Disclosed herein are a robot that generates a map and configures a correlation of nodes, based on multi sensors and artificial intelligence, and that moves based on the map, and a method of generating a map, and the robot according to an embodiment generates a pose graph comprised of LiDAR branch, visual branch, and backbone, and the LiDAR branch includes one or more of the LiDAR frames, the visual branch includes one or more of the visual frames, and the backbone includes two or more frame nodes registered with any one or more of the LiDAR frames or the visual frames, and to generate a correlation between nodes in the pose graph.

Robot generating map and configuring correlation of nodes based on multi sensors and artificial intelligence, and moving based on map, and method of generating map

Disclosed herein are a method of localization by synchronizing multi sensors and a robot implementing the same. The robot according to an embodiment includes a controller that, when a first sensor acquires first type information, generates first type odometry information using the first type information, that, at a time point when the first type odometry information is generated, acquires second type information by controlling a second sensor and then generates second type odometry information using the second type information, and that the robot by combining the first type odometry information and the second type odometry information.

Method of localization by synchronizing multi sensors and robot implementing same

Disclosed herein are a method of localization using multi sensors and a robot implementing the same, the method including sensing a distance between an object placed outside of a robot and the robot and generating a first LiDAR frame by a LiDAR sensor of the robot while a moving unit moves the robot, capturing an image of an object placed outside of the robot and generating a first visual frame by a camera sensor of the robot, and comparing a LiDAR frame stored in a map storage of the robot with the first LiDAR frame, comparing a visual frame registered in a frame node of a pose graph with the first visual frame, determining accuracy of comparison's results of the first LiDAR frame, and calculating a current position of the robot by a controller.

Method of localization using multi sensor and robot implementing same

Disclosed herein are a robot navigating based on obstacle avoidance and a navigation method. In the robot or the navigation method of the robot according to an embodiment, a navigation route may be generated on the basis of position information on a waypoint and on objects sensed by a sensor, such that the robot may move via one or more waypoints.

Robot navigating through waypoints based on obstacle avoidance and method of robot's navigation

Provided are a method for drawing a map of a specific area, a robot and an electronic device that implement such a method. According to the present disclosure, the method, the robot, and the electronic device improve quality of the drawn map by moving the robot so that loop closing is performed many times when the map is drawn. To this end, an accumulated moving distance from a first position and a second position of the robot moving in the specific area is measured, and when the loop closing is not performed at the second position, whether the loop closing is required at the second position is determined based on the measured accumulated moving distance and information on matching of feature points at the second position, and a movement of the robot is controlled based on a result of the determination.

Method for drawing map of specific area, robot and electronic device implementing thereof

A method and a robot of redefining a position of a robot using artificial intelligence are disclosed, and the robot that redefines a position using artificial intelligence separately stores an entrance-allowable area and an entrance-unallowable area in a space in which the robot moves as a map and stores locating posts that are required for the robot to restore a position thereof.

Method of redefining position of robot using artificial intelligence and robot of implementing thereof

A mobile terminal can include a display unit; a wireless communication unit configured to wireless communicate with a drone; a sensing unit; and a controller configured to sense a first touch signal of touching at least one partial area of map content displayed by the display unit, the first touch signal including a drag touch signal of moving along a first path with a first pressure and a first speed, in which the controller is further configured to set a moving path of the drone including a departure point of the drone and an arrival point of the drone based on the first path of the drag touch signal, set a moving speed of the drone based on the first speed of the drag touch signal, set a moving altitude of the drone based on the first pressure of the drag touch signal, and control the wireless communication unit to transmit a control signal based on at least one of the set moving path, the set moving speed or the set moving altitude of the drone.

Mobile terminal and control method therefor

Disclosed is a drone. The present invention includes a plurality of propellers creating a lift to prevent inclination and overturn of the drone due to a lift difference generated from uneven ground, a power driving unit providing a rotation power to each of a plurality of the propellers, a ground sensing unit measuring a distance to a first region of the ground and a shape of the first region, and a controller controlling the power driving unit to differentiate rotation ratios of a plurality of the propellers based on the measured distance and shape if receiving an input signal for landing at the first region.

Growing community of inventors

Seoul, South Korea

Joongtae Park