Abstract: The present disclosure provides a location information acquisition method of a computing device, including the steps of: acquiring first location information at which an electro-optical topographic surveying device is located in response to a received satellite Global Navigation Satellite System (GNSS) signal; acquiring photography information for positioning of a target object photographed by a drone while the drone is flying in a GNSS shadow area from the drone equipped with a survey prism that reflects light waves from the surveying device; calculating absolute coordinates of the target object corresponding to the surveying device based on reflective metering of the survey prism and the photography information for positioning; and calculating GNSS based second location information as location information of the target object using the absolute coordinates and the first location information.

Abstract: The present disclosure relates to an operation method of a computing device for performing a method for producing precise indoor maps using loop closing, including the steps of moving a robot to a first location, wherein the robot collects images and sensor data for precise map production by using a sensor module including at least one of a LiDAR sensor, an IMU sensor; forming a first closed-loop trajectory with an optimized pose graph by odometry estimation from the first location to create a first map using the movement of the robot; updating at least part of a second map generation trajectory and sensor data corresponding to a current trajectory of the robot by using at least one of trajectory information and sensor data of the first closed-loop trajectory; and outputting an updated second map based on the updated second map generation trajectory and sensor data.

Abstract: The present disclosure relates to a method for assessing the degree of damage to objects at disaster sites using skeletonization techniques, including the steps of moving a position of an investigation robot for information analysis of facility in a disaster site space to a first location by using a sensor module equipped in the investigation robot and including at least one of a LiDAR sensor, an IMU sensor or at least one vision sensor; acquiring sensing information corresponding to the first location based on SLAM; identifying a facility segment of a first space based on the sensing information; acquiring visual crack identification information corresponding to the facility segment, analyzed from vision image information of the sensing information, and unit crack information corresponding to the visual crack identification information; determining a crack expansion risk corresponding to the unit crack information.

Abstract: The present disclosure provides a location information acquisition method of a computing device, including the steps of: acquiring first location information at which an electro-optical topographic surveying device is located in response to a received satellite Global Navigation Satellite System (GNSS) signal; acquiring photography information for positioning of a target object photographed by a drone while the drone is flying in a GNSS shadow area from the drone equipped with a survey prism that reflects light waves from the surveying device; calculating absolute coordinates of the target object corresponding to the surveying device based on reflective metering of the survey prism and the photography information for positioning; and calculating GNSS based second location information as location information of the target object using the absolute coordinates and the first location information.