Abstract: A method for detecting small obstacles includes: acquiring a first 3D point cloud corresponding to image data acquired by a cleaning robot; extracting, from the first 3D point cloud, a second 3D point cloud of a ground region; extracting, from the second 3D point cloud, a third 3D point cloud having a height value in a set height range; calculating a ground projection point cloud of the third 3D point cloud; and, determining morphologically-connected regions in the ground projection point cloud, and using a morphologically-connected region having an area less than a preset value as a region where a small obstacle is located. By effectively recognizing the ground, acquiring the ground projection point cloud and processing the point cloud by image processing, accuracy and timeliness of the algorithm can be improved compared with directly processing discrete 3D point clouds.

Abstract: A method for obtaining localization information, includes: obtaining image information and related information of the image information, wherein the related information includes a depth map, a point cloud map, and relocation postures and relocation variance after relocation; obtaining three-dimensional coordinates of spatial obstacle points based on the depth map; obtaining target postures and environmental three-dimensional coordinates corresponding to each of the target postures based on the relocation postures, the relocation variance, and the point cloud map; scanning and matching the three-dimensional coordinates of the spatial obstacle points with the environmental three-dimensional coordinates to obtain matching result information; and obtaining localization information based on the relocation postures and the relocation variance when the matching result information satisfies a predetermined condition.

Abstract: A method for detecting small obstacles includes: acquiring a first 3D point cloud corresponding to image data acquired by a cleaning robot; extracting, from the first 3D point cloud, a second 3D point cloud of a ground region; extracting, from the second 3D point cloud, a third 3D point cloud having a height value in a set height range; calculating a ground projection point cloud of the third 3D point cloud; and, determining morphologically-connected regions in the ground projection point cloud, and using a morphologically-connected region having an area less than a preset value as a region where a small obstacle is located. By effectively recognizing the ground, acquiring the ground projection point cloud and processing the point cloud by image processing, accuracy and timeliness of the algorithm can be improved compared with directly processing discrete 3D point clouds.

Abstract: A method includes: acquiring a second initial pose according to obstacle region information and geometric scale information of an indoor architectural structure drawing and a first initial pose; acquiring a first feature point location, a locating error and a first pose through a VSLAM algorithm during movement; acquiring a second pose according to the first pose, first initial pose and second initial pose; acquiring a distance to an obstacle according to the second pose, indoor architectural structure drawing and a ray casting algorithm; acquiring a third pose according to the distance, first feature point location, locating error, first pose and a filtering algorithm; acquiring a second feature point location according to the third pose and VSLAM algorithm; and creating an indoor environment map according to the second feature point location and a key frame set.

Abstract: A method includes: acquiring a second initial pose according to obstacle region information and geometric scale information of an indoor architectural structure drawing and a first initial pose; acquiring a first feature point location, a locating error and a first pose through a VSLAM algorithm during movement; acquiring a second pose according to the first pose, first initial pose and second initial pose; acquiring a distance to an obstacle according to the second pose, indoor architectural structure drawing and a ray casting algorithm; acquiring a third pose according to the distance, first feature point location, locating error, first pose and a filtering algorithm; acquiring a second feature point location according to the third pose and VSLAM algorithm; and creating an indoor environment map according to the second feature point location and a key frame set.