Abstract: An inventory location, such as a shelf, may be used to stow different types of items in different areas of the shelf. Interactions may take place, such as the pick or place of items from the shelf. Weight data acquired from weight sensors at the shelf may be used to generate a set of hypotheses to describe types and quantities of items added to or removed from the shelf during an interaction. One or more of these hypotheses may be eliminated from consideration or selected as a solution based on activity data related to the shelf. The activity data is based on non-weight data from a non-weight sensor associated with the shelf. As an example, image data from a camera directed to the shelf can help identify presence of a user or a change in appearance at an area of the shelf to help evaluate hypotheses.

Abstract: An inventory location such as a shelf may be used to stow different types of items. Interactions may take place, such as the pick or place of one or more items from the inventory location. Weight data may be acquired from weight sensors coupled to the shelf. A measured change in weight is used to determine a first group of hypotheses. Each of the hypotheses may be descriptive of a different permutation of products being added to or removed from the shelf that could account for the measured change in weight. The weight data is also processed to determine a weight distribution of the items on the shelf. Information about the weight distribution may be used to select a subset of the first group of hypotheses. The subset may be used to determine what items were interacted with, quantity involved, and so forth.

Abstract: This disclosure describes techniques for synchronizing independent data streams. In some instances, a computing device couples to multiple independent sensors, such as cameras, and applies accurate timestamp information to the individual frames of sensor data from the independent sensors. After aligning these data streams by applying these accurate timestamps, the computing device may, in some instances, encode and transmit these timestamped data streams to one or more entities for further processing. In one example, a first camera (e.g., a depth camera configured to generate a depth map) may capture images of an environment, as may a second camera (e.g., an Red-Green-Blue (RGB) camera configured to generate color images). The resulting images may be temporally aligned with one another via the timestamping, and the resulting aligned images from both the depth sensor and the RGB camera may be used to create a three-dimensional (3D) model of the environment.