POWER RAMPING OF BEACON SIGNALS TO ENHANCE LOCATION ACCURACY

    公开(公告)号:US20230188940A1

    公开(公告)日:2023-06-15

    申请号:US17726647

    申请日:2022-04-22

    CPC classification number: H04W4/029 G01S5/0284 H04W52/367 H04B17/318

    Abstract: The technology enables locating asset tracking tags based on a ramped sequence of signals from one or more beacon tracking tags. The sequence includes at least one minimum power signal and at least one maximum power signal. Each signal in the sequence has a tag identifier and an initial signal strength value. Each beacon signal in the ramped sequence is associated with the time at which that beacon signal was received by a reader. Each beacon signal is also associated with a received signal strength at reception. A location of the beacon tracking tag is estimated according to the signals in the sequence based on the difference between the initial and received signal strengths. A position of the reader device is identified based on the beacon tag's location. An asset tracking tag location is identified based on the reader's location and packets received by the reader from the asset tag.

    UNDERWATER CAMERA BIOMASS PREDICTION AGGREGATION

    公开(公告)号:US20230177668A1

    公开(公告)日:2023-06-08

    申请号:US17457338

    申请日:2021-12-02

    CPC classification number: G06T7/0004 G06N3/08 A01K61/95

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for underwater camera biomass prediction aggregation. In some implementations, an exemplary method includes obtaining images of fish captured by an underwater camera; providing data of the images to a trained model; obtaining output of the trained model indicating the likelihoods that the biomass of fish are within multiple ranges; combining likelihoods of the output based on one or more ranges common to likelihoods of two or more fish to generate a biomass distribution; and determining an action based on the biomass distribution.

    TRAINING MACHINE LEARNING MODELS TO PREDICT CHARACTERISTICS OF ADVERSE EVENTS USING INTERMITTENT DATA

    公开(公告)号:US20230177407A1

    公开(公告)日:2023-06-08

    申请号:US18075521

    申请日:2022-12-06

    CPC classification number: G06N20/20

    Abstract: Methods, systems, and apparatus for providing a ML model for inference, the ML model having been trained using a first set of training data to provide predictions associated with an adverse event, after training of the ML model, receiving data from one or more data sources, the data representative of characteristics relevant to predictions associated with the adverse event, providing a second set of training data, determining, by a trigger module, a trigger decision based on a set of signals at least partially determined from the second set of training data, the trigger decision indicating whether the ML model is to be one of updated and retrained based on the second set of training data, and selectively executing one of updating and retraining of the ML model using at least a portion of the second set of training data in response to the trigger decision.

    MOLECULAR STRUCTURE TRANSFORMERS FOR PROPERTY PREDICTION

    公开(公告)号:US20230170059A1

    公开(公告)日:2023-06-01

    申请号:US17967685

    申请日:2022-10-17

    CPC classification number: G16C20/70 G16C20/20 G16C20/80

    Abstract: Computer-implemented methods may include accessing a multi-dimensional embedding space that supports relating embeddings of molecules to predicted values of a given property of the molecules. The method may also include identifying one or more points of interest within the embedding space based on the predicted values. Each of the one or more points of interest may include a set of coordinate values within the multi-dimensional embedding space and may be associated with a corresponding predicted value of the given property. The method may further include generating, for each of the one or more points of interest, a structural representation of a molecule by transforming the set of coordinate values included in the point of interest using a decoder network. The method may include outputting a result that identifies, for each of the one or more points of interest, the structural representation of the molecule corresponding to the point of interest.

    Systems and methods for inter-process communication within a robot

    公开(公告)号:US11656923B2

    公开(公告)日:2023-05-23

    申请号:US17880207

    申请日:2022-08-03

    CPC classification number: G06F9/544 G06F9/546

    Abstract: A method includes creating a publisher configured to send messages over a channel having a shared memory. The method includes creating at least one subscriber configured to receive the messages over the channel by sequentially referencing memory slots of the plurality of memory slots. The method includes determining that the next sequential memory slot is currently referenced by a subscriber. The method includes delaying sending the message by the publisher based on determining that the next sequential memory slot is currently referenced by the subscriber. The method includes receiving an event trigger indicative of message reading by the subscriber. The method includes, responsive to receiving the event trigger, determining that the next sequential memory slot is not currently referenced. The method includes sending the message to the next sequential memory slot based on determining that the next sequential memory slot is not currently referenced.

    Surface Wiping Tool for a Robot
    70.
    发明公开

    公开(公告)号:US20230145869A1

    公开(公告)日:2023-05-11

    申请号:US18054317

    申请日:2022-11-10

    Inventor: Courtney Kobata

    CPC classification number: B08B1/006 B25J11/0085 B08B3/04 B08B1/008 B08B13/00

    Abstract: A robotic device includes one or more robotic fingers and an attachable wiping tool. The attachable wiping tool includes a wiping component, a container configured to dispense a fluid, and an attachment component coupled to the robotic device. The attachment component is configured to align the one or more robotic fingers with the container such that the one or more robotic fingers, when actuated, engage the container to cause the container to dispense the fluid to the wiping component.

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