A method, device and sweeping robot for solidifying sub-images

Abstract

The present application discloses a sub-image curing method, device and sweeping robot. The method includes: obtaining a grid map of the current environment corresponding to the sweeping robot; obtaining all lines in the grid map, the lines including curves and A line segment; starting from one end of any one of the lines, searching all the lines to find a maximum closed area; solidifying the maximum closed area into a subgraph. During the cleaning process, the sweeping robot determines that it is a closed area, and solidifies the map corresponding to the closed area as soon as possible, that is, the sub-map, instead of solidifying the entire map after the thorough cleaning is completed, because as time goes by, the cleaning area increases. , the error of the data measured by the sensor has been accumulating, and the more the error accumulates, the larger it is. Therefore, solidifying the submap as soon as possible can avoid error accumulation as much as possible, thereby reducing the error, thereby improving the cleaning effect, and making the sweeping robot clean as fully as possible.

Description

technical field [0001] The present application relates to the technical field of smart home appliances, in particular to a method and device for solidifying a submap and a sweeping robot. Background technique [0002] With the popularity of smart home appliances, more and more families choose sweeping robots for cleaning. The sweeping robot needs to build a map and locate at the same time during the cleaning process (SLAM, Simultaneous Localization and Mapping). [0003] However, in the SLAM process, due to the accuracy of the sensor, there are cumulative errors in the map construction process, such as inertial measurement unit (IMU, Inertial Measurement Unit), code wheel odometer slipping, etc. All of these will affect the construction of the map, resulting in errors between the constructed map and the actual cleaning scene, resulting in insufficient cleaning. Contents of the invention [0004] The present application provides a sub-image solidification method, device a...

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Problems solved by technology

[0003] However, in the SLAM process, due to sensor accuracy, there are cumulative errors in the map construction process, for example, inertial measurement unit (IMU, Inertial Measurement Unit), code wheel odometer slipping, etc.

All of these will affect the construction of the map, resulting in errors between the constructed map and the actual cleaning scene, resulting in insufficient cleaning

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