A target object posture estimation method, comprising: obtaining a three-dimensional point cloud according to a scene depth map of a target object; extracting a target object point set from the three-dimensional point cloud; calculating a visibility loss value of the target object according to the three-dimensional point cloud and the target object point set; calculating a key point loss value of the target object by means of performing Hough voting on the target object point set; performing semantic segmentation on pixel points of the scene depth map, so as to obtain a semantic loss value of the target object; and calculating a posture of the target object according to the visibility loss value, the key point loss value, the semantic loss value and a multi-task joint model. Further provided are a target object posture estimation apparatus, a device and a storage medium. The method further relates to blockchain technology, and a scene depth map can be stored in a blockchain node. By means of the method, the posture of a target object to be grabbed can be accurately analyzed, thereby improving the grabbing precision of a mechanical arm.
OBJECT POSTURE ESTIMATION METHOD AND APPARATUS, AND ELECTRONIC DEVICE AND COMPUTER STORAGE MEDIUM