Method and device for generating indoor environment map
An indoor environment and map technology, applied in the field of mobile robots, can solve the problems that the method of generating environmental maps cannot satisfy the problems of easy construction and area segmentation at the same time, and achieve the effect of low efficiency, large amount of calculation and high complexity of path planning
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Embodiment 1
[0076] A method for generating an indoor environment map, refer to figure 1 , the method includes:
[0077] S102. Determine a feasible area in the grid map, wherein the feasible area is an area accessible to the mobile robot, and the feasible area includes a door area;
[0078] In the embodiment of the present invention, the topological segmentation is performed on the constructed grid map (that is, in an offline state). The method for constructing the grid map can be constructed by adopting the method for constructing the grid map in the prior art, and the embodiment of the present invention does not repeat the description of the method for constructing the grid map.
[0079] In addition, the present invention is mainly aimed at the topological segmentation of the home environment map of the mobile robot, and may also be applicable to other indoor environment maps, which are not specifically limited in the embodiments of the present invention.
[0080] After obtaining the g...
Embodiment 2
[0174] A device for generating an indoor environment map, refer to Figure 7 , the device consists of:
[0175] A determining module 11, configured to determine a feasible region in the grid map, wherein the feasible region is the reachable region of the mobile robot, and the feasible region includes a door region;
[0176] The segmentation module 12 is used to divide the feasible region by the gate segmentation algorithm to obtain a plurality of sub-feasible regions, and the plurality of sub-feasible regions include: a first sub-feasible region and a second sub-feasible region, wherein the region of the first sub-feasible region The type is known, and the area type of the second sub-feasible area is unknown;
[0177]The processing module 13 is configured to process the second sub-feasible region through a spectral clustering algorithm to obtain a plurality of topological regions, wherein each topological region represents a region category;
[0178] The fusion module 14 is ...
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