Abstract: A load sensor compares generated values of load signals to predicted values of the load signals. Where an error between a generated value and a predicted value is less than a threshold, a value of zero is transmitted by the load sensor to an external systems, in an encoded stream of bits, and the error are used to calculate a predicated value of a next load signal, such that insubstantial changes in loading resulting in small errors are not transmitted to the external system. Where an error between the generated value and the predicted value exceeds the threshold, however, a value representative of the error is transmitted to the external system, in an encoded stream of bits. The external system processes the stream of bits to calculate the error, to determine that an item has been placed on a storage system or removed therefrom, or to identify the item.

Abstract: Modular storage systems include load sensors disposed beneath or in association with platforms. The load sensors are pulse-sampled for signals corresponding to loads at time intervals, rather than continuously, in order to conserve electrical power. An item associated with a transaction is identified based on a change in the loads, as determined from the pulse-sampled signals. The platforms are aligned at horizontal or non-horizontal angles, and photovoltaic power sources with banks of photovoltaic cells are mounted to front edges of the platforms. When a user reaches over one of the photovoltaic cells to access an item on a platform, a level of power or voltage generated by the photovoltaic cell is diminished. The item closest to the photovoltaic cell having the diminished power or voltage, or a customer that accessed the item, may be identified accordingly.

Abstract: Systems and techniques for detecting events involving a user that occurred during a session in a facility, and performing a holistic, session-based analysis of the events to determine items taken by the user from the facility. An inventory management system may initially analyze the events to determine a hypothesis for a result of each respective event and a probability that the hypotheses are accurate. An initial listing of the items determined to be taken by the user may be generated along with probabilities that the items were taken. Upon determining that a probability an item was taken is lower than a threshold, the management system may select an algorithm to process an event in the session that is likely to resolve uncertainty in the initial listing. The management system may iteratively process events until a final listing represents the items taken by the user with an allowable probability.

Abstract: An apparatus includes a platform or other accessory that is supported by one or more transducer assemblies using piezoelectric transducers. In one implementation, a saddle structure provides mechanical support to a platform while transferring force from a load onto a portion to which a pair of piezoelectric transducers are affixed. As a load on the saddle changes, the resulting change in strain on the portion produces signals from the piezoelectric transducers. In another implementation a beam provides mechanical support to a platform or other accessory. A pair of piezoelectric transducers are affixed near a strain concentrator, such as a hole in the beam, produce signals indicative of a change in load on the beam.

Abstract: Load cells are used in a fixture of a facility to acquire weight data. However, some of the load cells used in the fixture may fail. One way to test a subset of load cells is to compare data from a first subset of load cells to a second subset of load cells using a linear regression. For example, the linear regression may help determine predicted values for the first subset of load cells. Actual values from the first subset of load cells are then compared to the predicted values. If the differences between the actual values and predicted values for the first subset of load cells are greater than a threshold, a determination is made that the first subset of load cells has failed. Weight data from the second subset of load cells may then be used to determine hypotheses for describing interactions at the fixture.

Abstract: One or more load cells measure the weight of items at a fixture. Weight changes occur as items are picked from or placed to the fixture and may be used to determine when the item was picked or placed, quantity and so forth. Individual weights for a type of item may vary. A set of data comprising weight changes associated with interactions involving a single one of a particular type of item is gathered. These may be weight changes due to picks, places, or both. A model, such as a probability distribution, may be created that relates a particular weight of that type of item to a probability. The model may then be used to process other weight changes and attempt to determine what type of item was involved in an interaction.

Abstract: One or more load cells measure the weight of items on a shelf or other fixture. Weight changes occur as items are picked from or placed to the fixture. Output from the load cells is processed to produce denoised data. The denoised data is processed to determine event data representative of a pick or a place of an item. Hypotheses are generated using information about where particular types of items are stowed, the weights of those particular types of items, and the event data. A high scoring hypothesis is used to determine interaction data indicative of the type and quantity of an item that was added to or removed from the fixture. If ambiguity exists between hypotheses, additional techniques such as data about locations of weight changes and fine grained analysis may be used to determine the interaction data.

Abstract: A user undertakes an event, such as adding, removing, or otherwise interacting with an item stowed at a fixture. Using successive samples of weight data that occur during an event, a plurality of vectors are generated that are indicative of a weight change and a location associated with the fixture. The vectors are processed to determine where within the fixture the event took place. Hypotheses are generated that describe predicted interactions involving predicted locations that correspond to those indicated by the vectors. The hypotheses are ranked and then one is selected as a solution. The predicted values associated with the selected hypothesis are then used to generate interaction data that indicates one or more types of item and quantities of the items that were added, removed, or otherwise handled by the user.

Abstract: An impulse strip including a plurality of clips, hooks or other features for attaching items to the impulse strip also includes a plurality of switches associated with each of the clips, hooks or other features. The switches are in communication with illuminators or other indicators that are arranged in an array. When an item is loaded onto the strip, or removed from the strip, a switch may be opened or closed, causing one of the illuminators in the array to be activated or deactivated accordingly. An image captured of the illuminators is processed to determine which of the illuminators is activated and which is deactivated, and an inventory level of the strip may be determined based on the statuses of the respective illuminators corresponding to the clips, the hooks or the other features of the impulse strip.

Abstract: A platform is supported at four corners by four half-bridge load cells. Adjacent load cells are oppositely polarized. During operation, analog output from a pair of oppositely polarized half-bridge load cells is provided to an instrument amplifier. Analog output from the instrument amplifier is provided to an analog to digital converter to provide digital data. The digital data is then used to determine weight data indicative of a weight as measured by the pair of half-bridge load cells at that time. A set of switching elements, such as a quad bilateral switch controlled by a microcontroller, rapidly switch between pairs of oppositely polarized load cells. The weight data may be used to determine an overall weight change on the platform, such as a pick or a place of an item. Weight data from the four pairs of load cells may be used to determine a change in center of gravity.

Abstract: An apparatus includes a platform or other accessory that is supported by one or more piezoelectric transducers. As items are placed on or removed from the accessory, the piezoelectric transducer generates an electric charge that is representative of a change in weight. An amplifier receives the charge and provides output voltage that can be sampled to determine a weight value. In one implementation the platform may be supported by a transducer assembly comprising a frame and a pair of piezoelectric transducers on opposite sides of the frame. Signals from the pair may be used to compensate for environmental effects on the assembly, such as changes in temperature. The piezoelectric transducers and associated circuitry are extremely energy efficient, consuming little electrical power during operation.

Abstract: Sensor data from load cells at a shelf is processed using a first time window to produce first event data describing coarse and sub-events. Location data is determined that indicates where on the shelf weight changes occurred at particular times. Hypotheses are generated using information about where items are stowed, weights of those of items, type of event, and the location data. If confidence values of these hypotheses are below a threshold value, second event data is determined by merging adjacent sub-events. This second event data is then used to determine second hypotheses which are then assessed. A hypothesis with a high confidence value is used to generate interaction data indicative of picks or places of particular quantities of particular types of items from the shelf.

Abstract: Load cells measure the weight of items on a shelf. Weight changes occur as items are picked from or placed to the fixture. Information about these weight changes is used to determine an estimated location on the shelf of a weight change. Hypotheses are generated using information about where particular types of items are stowed, the weights of those particular types of items, information about the weight changes, and the estimated locations of the weight changes. A model is used to produce confidence values in the hypotheses based on a change in weight measured at a first side and a change in weight measured at a second side of the shelf. A hypothesis with a confidence value that exceeds the threshold may be selected and used to determine interaction data indicative of a quantity picked or placed, type of item, and location on the shelf.

Abstract: This disclosure describes techniques for removing noise from a signal to generate a modified signal, with the modified signal preserving any transitions of interest (e.g., sharp-edge discontinuities) present within the initial signal. In one example, the signal comprises a time-series signal with the time series representing a sequence of weight measurements from a scale device. In some examples, the scale device includes a platform that supports one or more physical items that may be selectively removed or added to. Here, the signal may include a sequence of step functions corresponding to changes in weight on the scale device (based on the removal or addition of items on the platform), plus corrupting noise from vibration. The techniques described herein may remove the corrupting noise, while preserving the sharp edges representing sudden changes in weight.

Abstract: A user may pick an item from a first inventory location, such as in a lane on a shelf, and may return it another location that is assigned to another type of item. Described are techniques to generate tidiness data that is indicative of whether an item has been returned to an inventory location assigned to that type of item. As items are taken, information about the type of item taken and its weight are stored. When an increase in weight at a lane indicates a return of an item to the lane, the weight of the return is compared to the stored weight of the items previously taken by a user. If the weights correspond to within a threshold value, the type of item associated with the stored weight is deemed to be returned and tidiness data indicative of a tidy return of the item to its appointed lane may be generated.

Abstract: A device comprises a crossmember. The crossmember is supported by one or more weight sensors, such that a total weight of the crossmember and any supported load may be measured. One or more strain gauges are affixed to the crossmember. An accessory may comprise a portion to support an inventory item, such as a hook, shelf, bin, basket, and so forth. The accessory also includes an engagement feature to mechanically engage a portion of the crossmember. Several accessories may be engaged to the crossmember. As the load on the accessory changes, such as due to a pick or place of items, a total weight change may be determined by summing the output from the weight sensors. Data from the strain gauges may be used to allocate the total weight change to a particular accessory, allowing for the determination of the weight change for that particular accessory.

Abstract: A parallel planar weight sensing device includes an accessory mounting bracket with an upper portion and a lower portion. Part of the accessory mounting bracket extends around a crossmember that also has an upper portion and a lower portion. Affixed to the upper portion of the crossmember is a first load cell while a second load cell is affixed to the lower portion of the crossmember. The upper portion of the accessory mounting bracket is affixed to the first load cell while the lower portion is affixed to the second load cell. An accessory, such as a shelf or hook, may be attached to the accessory mounting bracket and used to stow items. As the load on the accessory changes, such as due to a pick or place of items, a total weight change may be determined by summing the output from the load cells.

Abstract: A shifted-lens imaging device mounted in association with a storage unit captures images of interactions by personnel with items on the storage unit. The images are processed to identify the items and/or the personnel, and to store an association of the personnel with the items in one or more data stores. The shifted-lens imaging device is mounted to the storage unit directly, such as by one or more extensions, and aligned to include a planar area of interest associated with the storage unit, such as a frontal area of the storage unit, within a field of view. A lens of the shifted-lens imaging device is shifted in parallel with the imaging sensor by an offset or distance that may be selected based on a focal length of the imaging device and a distance between the imaging device and dimensions of the planar area of interest.

Abstract: Shelves or other fixtures may be used to support items at a facility. Load cells at the fixtures may be used to acquire weight data indicative of changes to the fixture as items are added or removed from the fixture. The load cells may occasionally fail to provide accurate information. Described are techniques for comparing the data from a first sensor with data from other sensors to determine if the first sensor has failed. A linear regression may be performed using the data from the other sensors, and the results compared with the output from the first sensor. If the difference exceeds a threshold amount, an error in the first sensor may be determined. Once determined, other actions may be taken, such as generating a repair ticket to fix the first sensor, disregarding weight from that sensor, and so forth.