Abstract: A method executable by an autonomous mobile device includes moving in a work environment, obtaining environmental data acquired by a sensing device, and determining whether the sensing device is in a suspected ineffective state based on the environmental data. The method also includes based on a determination that the sensing device is in the suspected ineffective state, rotating at a same location for a first predetermined spin angle. The method also includes obtaining an estimated rotation angle based on one or more motion parameters acquired by a dead reckoning sensor, comparing the estimated rotation angle with the first predetermined spin angle, and based on a determination that a difference between the estimated rotation angle and the first predetermined spin angle is greater than a first predetermined threshold value, executing escape instructions to move backwardly for a first predetermined distance and move along a curve or a folded line.

Abstract: A method includes acquiring an image through a visual sensor during a movement of a mobile device. The method includes matching the image with key frames stored in a key frame database. The key frames are created based on two-dimensional coordinates of feature points included in a plurality of images previously acquired through the visual sensor. The method also includes computing a visual relative pose based on two-dimensional coordinates of matching feature points included in both of the image and the one or more key frames that have been matched with the image. The method also includes computing relevant information of the visual relative pose based on the two-dimensional coordinates of the matching feature points. The method further includes updating an absolute pose of the mobile device and a map based on the relevant information of the visual relative pose and relevant information of a dead reckoning based relative pose.

Abstract: A method executable by an autonomous mobile device includes moving in a work environment, obtaining environmental data acquired by a sensing device, and determining whether the sensing device is in a suspected ineffective state based on the environmental data. The method also includes based on a determination that the sensing device is in the suspected ineffective state, rotating at a same location for a first predetermined spin angle. The method also includes obtaining an estimated rotation angle based on one or more motion parameters acquired by a dead reckoning sensor, comparing the estimated rotation angle with the first predetermined spin angle, and based on a determination that a difference between the estimated rotation angle and the first predetermined spin angle is greater than a first predetermined threshold value, executing escape instructions to move backwardly for a first predetermined distance and move along a curve or a folded line.

Abstract: A method includes acquiring an image through a visual sensor during a movement of a mobile device. The method includes matching the image with key frames stored in a key frame database. The key frames are created based on two-dimensional coordinates of feature points included in a plurality of images previously acquired through the visual sensor. The method also includes computing a visual relative pose based on two-dimensional coordinates of matching feature points included in both of the image and the one or more key frames that have been matched with the image. The method also includes computing relevant information of the visual relative pose based on the two-dimensional coordinates of the matching feature points. The method further includes updating an absolute pose of the mobile device and a map based on the relevant information of the visual relative pose and relevant information of a dead reckoning based relative pose.

Abstract: A VSLAM method includes receiving an image obtained by a visual sensor. The method also includes retrieving a key frame from a pre-established key frame database, and after the key frame is retrieved, matching the image with the retrieved key frame. The method also includes computing relevant information of a visual relative pose based on the image and the key frame. The visual relative pose is computed based on two-dimensional coordinates of matching feature points between the image and the key frame that have been successfully matched. The method further includes updating an absolute pose and a map of a mobile device based on the relevant information of the visual relative pose and relevant information of a dead reckoning based relative pose, if the relevant information of the visual relative pose is obtained.

Abstract: A VSLAM method includes receiving an image obtained by a visual sensor. The method also includes retrieving a key frame from a pre-established key frame database, and after the key frame is retrieved, matching the image with the retrieved key frame. The method also includes computing relevant information of a visual relative pose based on the image and the key frame. The visual relative pose is computed based on two-dimensional coordinates of matching feature points between the image and the key frame that have been successfully matched. The method further includes updating an absolute pose and a map of a mobile device based on the relevant information of the visual relative pose and relevant information of a dead reckoning based relative pose, if the relevant information of the visual relative pose is obtained.