Abstract: An interaction method and apparatus and an electronic device. The method comprises: displaying a first application interface, wherein the first application interface comprises an interface of a first application; and creating a second application account in the first application interface, wherein the second application account is used for logging in a second application. Therefore, a new interaction mode is provided.

Abstract: A method and system for positioning an indoor autonomous mobile robot is disclosed in this application, which includes: indoor layout of moving paths and indoor relative position information of the moving path are obtained by a vision sensor; visual positioning is performed by a visual locator on indoor image data collected by the visual sensor to obtain the first position information; and second position information of a UWB location tag is obtained and solved by an UWB locator; the first position information and the second position information are fused by an adaptive Kalman filter, to obtain final positioning information of the autonomous mobile robot. After fusion, the UWB locator can correct the accumulated error caused by visual positioning, and at the same time, visual positioning can smooth measured data of the UWB locator to make up for deficiencies.

Abstract: A method for human action recognition in a human-machine interactive assembly scene is disclosed in this application, joint coordinate streams of skeleton joints are obtained under a human action from motion sensing devices; a starting position and an ending position of the action are positioned according to data change based on a threshold value to obtain information of joints; resampling of angle change is made on the information of joints to obtain coordinates of joints; the coordinates of joints are normalized, to obtain a sequence of skeletons forming an action; obtaining a vector direction of the upper limb, and the scene is classified to be a left-hand scene or a right-hand scene; training is made for human action recognition in the left-hand scene and the right-hand scene respectively; human action outputs of the left-hand scene and the right-hand scene are fused to realize action recognition in a human-machine interaction scene.