# US 2023/0273620 A1 · Mapping method, computer-readable storage medium, and robot > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2023/0273620 A1 - Document ID: US20230273620A1 - Status: Published application - Kind: A1 - Application number: 18/143,596 - Filed: 2023-05-04 - Published: 2023-08-31 - Earliest claimed: 2020-11-06 - Assignees: Ubtech Robotics Corp Ltd - Applicants: Ubtech Robotics Corp Ltd - Inventors: Simin Zhang; Zhichao Liu - Web page: https://patentgrep.com/patent/US20230273620A1 ## CPC - G05D 1/0274: {using mapping information stored in a memory device (navigation using map-matching G01C21/30)} - G01C 21/206: {specially adapted for indoor navigation} - G01C 21/383: {Indoor data} - G01C 21/3837: {Data obtained from a single source} - G01S 17/89: for mapping or imaging - G01S 17/931: of land vehicles - G05D 1/0214: {in accordance with safety or protection criteria, e.g. avoiding hazardous areas (monitoring the location of vehicles within a certain area, e.g. forbidden or allowed areas, in traffic control systems for road vehicles G08G1/13)} - G05D 1/024: {in combination with a laser (lasers per se H01S)} - G05D 1/246: using environment maps, e.g. simultaneous localisation and mapping [SLAM] - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES ## Abstract A mapping method, a computer-readable storage medium, and a robot are provided. The method is applied to a robot including a first lidar and a second lidar, where the first lidar is installed at a position higher than that of the second lidar. The method includes: obtaining a first laser key frame; calculating a current pose of a robot based on the first laser key frame; updating a first probability map based on the current pose and the first laser key frame; obtaining a second laser key frame; updating a second probability map based on the current pose and the second laser key frame; and generating a fused grid map for navigating the robot based on the updated first probability map and the updated second probability map, thereby greatly improving the stability of positioning and navigation. ## Claims ### Claim 1 A computer-implemented mapping method for a robot having a first lidar and a second lidar, wherein the first lidar is installed higher than the second lidar; wherein the method comprises: collecting, by the first lidar, a current laser key frame to take as a first laser key frame; calculating a current pose of the robot based on the first laser key frame; updating a first probability map based on the current pose and the first laser key frame, wherein the first probability map is a probability map corresponding to the first lidar; collected, by the second lidar, a current laser key frame to take as a second laser key frame; updating a second probability map based on the current pose and the second laser key frame, wherein the second probability map is a probability map corresponding to the second lidar; generating a first grid map corresponding to the updated first probability map; generating a second grid map corresponding to the updated second probability map; obtaining a fused grid map by aligning the first grid map and the second grid map according to a preset relative pose conversion relationship between the first lidar and the second lidar; determining a grid in the fused grid map as a black grid, in response to the grid meeting a first preset condition that the grid corresponds to a black grid in the first grid map; determining the grid in the fused grid map as a white grid, in response to the grid meeting a second preset condition that the grid corresponds to a grid that is not a black grid in the first grid map but corresponds to a white grid in the second grid map; and determining the grid in the fused grid map as a gray grid, in response to the grid neither meeting the first preset condition nor meeting the second preset condition. ### Claim 2 (depends on 1) The method of claim 1, wherein generating the first grid map corresponding to the updated first probability map comprises: determining an occupancy probability of a target grid in the updated first probability map, wherein the target grid is any grid in the first grid map; and determining a grid type of the target grid according to the occupancy probability. ### Claim 3 (depends on 2) The method of claim 2, wherein determining the grid type of the target grid according to the occupancy probability comprises: determining the target grid as a black grid, in response to the occupancy probability being larger than or equal to a preset probability threshold; determining the target grid as a white grid, in response to the occupancy probability being smaller than the preset probability threshold; and determining the target grid as a gray grid, in response to the occupancy probability being null. ### Claim 4 (depends on 1) The method of claim 1, wherein the relative pose conversion relationship is determined by: obtaining a first ranging result of the first lidar for a target object and a second ranging result of the second lidar for the target object, wherein the target object is placed vertically; and determining the relative pose conversion relationship based on the first ranging result and the second ranging result. ### Claim 5 (depends on 1) The method of claim 1, wherein updating a first probability map according to the current pose and the first laser key frame comprises: updating a first count value and a second count value of each raytrace grid in the first probability map corresponding to the first laser key frame according to the current pose, wherein the raytrace grid is a grid of the first probability map where a ray from the first lidar to the obstacle passes, the first count value is an amount of times the grid being hit by the ray emitted from the first lidar, and the second count value is an amount of times the grid is the raytrace grid; and obtaining the updated first probability map by updating an occupancy probability of each link grid in the first probability map based on the updated first count value and the update second count value. ### Claim 6 (depends on 1) The method of claim 1, wherein the first lidar is installed higher than the second lidar so as to avoid detecting a movable object in an external environment where the robot is located, and the second lidar is configured to detect the movable object. ### Claim 7 A non-transitory computer-readable storage medium for storing one or more computer programs, wherein the one or more computer programs comprise: instructions for collecting, by a first lidar of a robot, a current laser key frame to take as a first laser key frame; instructions for calculating a current pose of the robot based on the first laser key frame; instructions for updating a first probability map based on the current pose and the first laser key frame, wherein the first probability map is a probability map corresponding to the first lidar; instructions for collected, by a second lidar of the robot, a current laser key frame to take as a second laser key frame, wherein the first lidar is installed higher than the second lidar; instructions for updating a second probability map based on the current pose and the second laser key frame, wherein the second probability map is a probability map corresponding to the second lidar; instructions for generating a first grid map corresponding to the updated first probability map; instructions for generating a second grid map corresponding to the updated second probability map; instructions for obtaining a fused grid map by aligning the first grid map and the second grid map according to a preset relative pose conversion relationship between the first lidar and the second lidar; instructions for determining a grid in the fused grid map for navigating the robot as a black grid, in response to the grid meeting a first preset condition that the grid corresponds to a black grid in the first grid map; instructions for determining the grid in the fused grid map as a white grid, in response to the grid meeting a second preset condition that the grid corresponds to a grid that is not a black grid in the first grid map but corresponds to a white grid in the second grid map; and instructions for determining the grid in the fused grid map as a gray grid, in response to the grid neither meeting the first preset condition nor meeting the second preset condition. ### Claim 8 (depends on 7) The storage medium of claim 7, wherein instructions for the generating the first grid map corresponding to the updated first probability map comprise: instructions for determining an occupancy probability of a target grid in the updated first probability map, wherein the target grid is any grid in the first grid map; and instructions for determining a grid type of the target grid according to the occupancy probability. ### Claim 9 (depends on 8) The storage medium of claim 8, wherein the instructions for determining the grid type of the target grid according to the occupancy probability comprise: instructions for determining the target grid as a black grid, in response to the occupancy probability being larger than or equal to a preset probability threshold; instructions for determining the target grid as a white grid, in response to the occupancy probability being smaller than the preset probability threshold; and instructions for determining the target grid as a gray grid, in response to the occupancy probability being null. ### Claim 10 (depends on 7) The storage medium of claim 7, wherein the relative pose conversion relationship is determined by: obtaining a first ranging result of the first lidar for a target object and a second ranging result of the second lidar for the target object, wherein the target object is placed vertically; and determining the relative pose conversion relationship based on the first ranging result and the second ranging result. ### Claim 11 (depends on 7) The storage medium of claim 7, wherein the instructions for updating a first probability map according to the current pose and the first laser key frame comprise: instructions for updating a first count value and a second count value of each raytrace grid in the first probability map corresponding to the first laser key frame according to the current pose, wherein the raytrace grid is a grid of the first probability map where a ray from the first lidar to the obstacle passes, the first count value is an amount of times the raytrace grid being hit by the ray emitted from the first lidar, and the second count value is an amount of times the raytrace grid is the ray trace grid; and instructions for obtaining the updated first probability map by updating an occupancy probability of each link grid in the first probability map based on the updated first count value and the update second count value. ### Claim 12 (depends on 7) The storage medium of claim 7, wherein the first lidar is installed higher than the second lidar so as to avoid a detecting movable object in an external environment where the robot is located, and the second lidar is configured to detect the movable object. ### Claim 13 A robot, comprising: a first lidar; a second lidar, wherein the first lidar is installed higher than the second lidar; a processor; a memory coupled to the processor; and one or more computer programs stored in the memory and executable on the processor; wherein, the one or more computer programs comprise: instructions for collecting, by the first lidar, a current laser key frame to take as a first laser key frame; instructions for calculating a current pose of the robot based on the first laser key frame; instructions for updating a first probability map based on the current pose and the first laser key frame, wherein the first probability map is a probability map corresponding to the first lidar; instructions for collected, by the second lidar, a current laser key frame to take as a second laser key frame; instructions for updating a second probability map based on the current pose and the second laser key frame, wherein the second probability map is a probability map corresponding to the second lidar; instructions for generating a first grid map corresponding to the updated first probability map; instructions for generating a second grid map corresponding to the updated second probability map; instructions for obtaining a fused grid map by aligning the first grid map and the second grid map according to a preset relative pose conversion relationship between the first lidar and the second lidar; instructions for determining a grid in the fused grid map for navigating the robot as a black grid, in response to the grid meeting a first preset condition that the grid corresponds to a black grid in the first grid map; instructions for determining the grid in the fused grid map as a white grid, in response to the grid meeting a second preset condition that the grid corresponds to a grid that is not a black grid in the first grid map but corresponds to a white grid in the second grid map; and instructions for determining the grid in the fused grid map as a gray grid, in response to the grid neither meeting the first preset condition nor meeting the second preset condition. ### Claim 14 (depends on 13) The robot of claim 13, wherein instructions for the generating the first grid map corresponding to the updated first probability map comprise: instructions for determining an occupancy probability of a target grid in the updated first probability map, wherein the target grid is any grid in the first grid map; and instructions for determining a grid type of the target grid according to the occupancy probability. ### Claim 15 (depends on 14) The robot of claim 14, wherein the instructions for determining the grid type of the target grid according to the occupancy probability comprise: instructions for determining the target grid as a black grid, in response to the occupancy probability being larger than or equal to a preset probability threshold; instructions for determining the target grid as a white grid, in response to the occupancy probability being smaller than the preset probability threshold; and instructions for determining the target grid as a gray grid, in response to the occupancy probability being null. ### Claim 16 (depends on 13) The robot of claim 13, wherein the relative pose conversion relationship is determined by: obtaining a first ranging result of the first lidar for a target object and a second ranging result of the second lidar for the target object, wherein the target object is placed vertically; and determining the relative pose conversion relationship based on the first ranging result and the second ranging result. ### Claim 17 (depends on 13) The robot of claim 13, wherein the instructions for updating a first probability map according to the current pose and the first laser key frame comprise: instructions for updating a first count value and a second count value of each ray trace grid in the first probability map corresponding to the first laser key frame according to the current pose, wherein the ray trace grid is a grid of the first probability map where a ray from the first lidar to the obstacle passes, the first count value is an amount of times the raytrace grid being hit by the ray emitted from the first lidar, and the second count value is an amount of times the ray trace grid is the raytrace grid; and instructions for obtaining the updated first probability map by updating an occupancy probability of each link grid in the first probability map based on the updated first count value and the update second count value. ### Claim 18 (depends on 13) The robot of claim 13, wherein the first lidar is installed higher than the second lidar so as to avoid detecting a movable object in an external environment where the robot is located, and the second lidar is configured to detect the movable object.