# US 11,896,175 B2 · Method and apparatus for updating working map of mobile robot, and storage medium > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,896,175 B2 - Document ID: US11896175B2 - Status: Granted - Kind: B2 - Application number: 17/565,640 - Filed: 2021-12-30 - Published: 2022-04-21 - Granted: 2024-02-13 - Earliest claimed: 2019-07-02 - Assignees: Huawei Technologies Co., Ltd. - Applicants: Huawei Technologies Co., Ltd. - Inventors: Jingtao Xue; Yanong He - Web page: https://patentgrep.com/patent/US11896175B2 ## CPC - A47L 11/4011: {Regulation of the cleaning machine by electric means; Control systems and remote control systems therefor} - G01C 21/383: {Indoor data} - G01C 21/3837: {Data obtained from a single source} - G01C 21/3848: {Data obtained from both position sensors and additional sensors} - G01C 21/387: {Organisation of map data, e.g. version management or database structures} - G05D 1/0219: {ensuring the processing of the whole working surface} - G05D 1/0274: {using mapping information stored in a memory device (navigation using map-matching G01C21/30)} - G05D 1/246: using environment maps, e.g. simultaneous localisation and mapping [SLAM] - G05D 1/648: Performing a task within a working area or space, e.g. cleaning - G06V 10/809: {of classification results, e.g. where the classifiers operate on the same input data} - G06V 20/10: Terrestrial scenes (scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59) - G06V 20/653: {by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces} - A47L 2201/04: Automatic control of the travelling movement; Automatic obstacle detection - A47L: DOMESTIC WASHING OR CLEANING (brushes A46B; cleaning quantities of bottles or of other hollow articles of one kind B08B9/00; laundry D06F); SUCTION CLEANERS IN GENERAL (cleaning in general B08) - 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) - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract This application provides a method and an apparatus for updating a working map of a mobile robot, and a storage medium in the field of intelligent control technologies. The method includes: determining a plurality of detected environment maps based on object distribution information detected by the mobile robot in a moving process; merging the plurality of detected environment maps to obtain a merged environment map; and then performing weighting processing on the merged environment map and an environment layout map currently stored in the mobile robot, to obtain an updated environment layout map. The environment layout map stored in the mobile robot is updated by using the plurality of detected maps obtained by the mobile robot during working, so that the updated environment layout map can reflect a more detailed environment layout. This helps the mobile robot subsequently better execute a working task. ## Claims ### Claim 1 A method for controlling a mobile robot, comprising: obtaining M detected environment maps, wherein the M detected environment maps are determined based on object distribution information detected by the mobile robot in a moving process, and M is an integer greater than 1; merging the M detected environment maps to obtain a merged environment map; performing weighting processing on a pixel value of the merged environment map and a pixel value of a currently stored environment layout map to obtain an updated environment layout map, wherein the currently stored environment layout map is obtained by performing weighting processing on a previously merged environment map and a previously stored environment layout map and controlling the mobile robot around a workplace using the updated environment layout map. ### Claim 2 (depends on 1) The method according to claim 1, wherein when weighting processing is performed on the pixel value of the merged environment map and the pixel value of the currently stored environment layout map, a weight corresponding to the pixel value of the merged environment map and a weight corresponding to the pixel value of the currently stored environment layout map are respectively a first weight and a second weight, and values of the first weight and the second weight are determined based on a map update requirement of the mobile robot in operation. ### Claim 3 (depends on 2) The method according to claim 2, wherein determining that the values of the first weight and the second weight based on the map update requirement of the mobile robot comprises: the first weight is in a positive correlation with an environment layout map update frequency required when the mobile robot operates, and the second weight is in a negative correlation with the environment layout map update frequency required when the mobile robot operates. ### Claim 4 (depends on 1) The method according to claim 1 wherein merging the M detected environment maps to obtain the merged environment map comprises: determining N detected environment maps from the M detected environment maps, wherein consistency between any two of the N detected environment maps is greater than or equal to a first threshold, and N is a positive integer less than or equal to M; and merging the N detected environment maps to obtain the merged environment map. ### Claim 5 (depends on 1) The method according to claim 1, wherein the method further comprises: determining a current detected environment map based on current object distribution information, wherein the current object distribution information is object distribution information detected by the mobile robot in a preset interval or a preset distance, the preset interval being a time interval before the mobile robot reaches a current detection point, and the preset distance being a distance by which the mobile robot moves before the mobile robot reaches the current detection point; when consistency between the current detected environment map and the environment layout map is less than a second threshold, determining that the mobile robot is abnormal when detecting an ambient environment; and controlling the mobile robot to recover from an anomaly. ### Claim 6 (depends on 5) The method according to claim 5, wherein controlling the mobile robot to recover from the anomaly comprises: controlling the mobile robot to return from the current detection point to a first detection point, wherein a distance between the first detection point and the current detection point is the preset distance; and controlling the mobile robot to start to re-detect the ambient environment from the first detection point, to obtain new object distribution information. ### Claim 7 (depends on 5) The method according to claim 5, wherein the method further comprises: controlling the mobile robot to clear the current object distribution information. ### Claim 8 (depends on 1) The method according to claim 1, wherein the M detected environment maps all are located in a same coordinate system. ### Claim 9 (depends on 8) The method according to claim 8, wherein the M detected environment maps all are located in a reference coordinate system, and an origin of the reference coordinate system is at any one of the following locations: a location of a charging station of the mobile robot; a location at which the mobile robot stops after ending a task; or a location of a waste transfer station that goes with the mobile robot. ### Claim 10 (depends on 1) The method according to claim 1, wherein the M detected environment maps are determined based on object distribution information detected when the mobile robot executes a working task in the workplace. ### Claim 11 (depends on 10) The method according to claim 10, wherein the M detected environment maps are respectively determined based on M pieces of object distribution information, and the M pieces of object distribution information are respectively object distribution information detected when the mobile robot executes M working tasks. ### Claim 12 (depends on 1) A mobile robot, comprising: a memory, configured to store a program; and a processor, configured to execute the program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to perform the method according to claim 1. ### Claim 13 (depends on 1) A computer storage medium, wherein the computer storage medium stores program code, and the program code comprises instructions used to perform the steps in the method according to claim 1.