Lg Electronics Inc.

Dong Ki Noh

Gyuho Eoh

JungSik Kim

Hyoungrock Kim

Joongtae Park

Minjung Kim

Seungmin Baek

Yeonsoo Kim

Hyoung Seok Kim

Sookhyun Yang

Jeong Sik Choi

Kang Uk Kim

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

Disclosed is a moving robot capable of recognizing a waiting line and a method for controlling the same. One embodiment provides a method for operating a moving robot, the method comprising: starting moving from a predefined moving start point toward a predefined moving end point; acquiring a waiting line region image by photographing a predefined waiting line region during the moving; searching for an end point of a waiting line formed in the waiting line region using the waiting line region image; terminating the moving when the end point of the waiting line is detected; setting an operation mode based on a length of the waiting line calculated using the end point of the waiting line; and operating in the set operation mode while returning to the moving start point.

Mobile robot for recognizing queue and operating method of 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

A main server for controlling laser irradiation of a movement path of a robot, the main server including a communication unit configured to communicate with a camera module and a laser irradiation module; and a controller configured to: receive, via the communication unit, an image of a robot captured by the camera module, identify a location of the robot in the image captured by the camera module, generate a movement path of the robot based on sensing information, and transmit, via the communication unit, movement path information to the laser irradiation module for outputting the movement path to a vicinity of the robot with a laser for the robot to follow, in which the sensing information includes first information about an obstacle sensed by the camera module or second information about the obstacle sensed by the laser irradiation module.

Server and method for controlling laser irradiation of movement path of robot, and robot that moves based thereon

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.

Growing community of inventors

Seoul, South Korea

Dong Ki Noh