Robotic control using value distributions

    公开(公告)号:US11571809B1

    公开(公告)日:2023-02-07

    申请号:US17017920

    申请日:2020-09-11

    Abstract: Techniques are described herein for robotic control using value distributions. In various implementations, as part of performing a robotic task, state data associated with the robot in an environment may be generated based at least in part on vision data captured by a vision component of the robot. A plurality of candidate actions may be sampled, e.g., from continuous action space. A trained critic neural network model that represents a learned value function may be used to process a plurality of state-action pairs to generate a corresponding plurality of value distributions. Each state-action pair may include the state data and one of the plurality of sampled candidate actions. The state-action pair corresponding to the value distribution that satisfies one or more criteria may be selected from the plurality of state-action pairs. The robot may then be controlled to implement the sampled candidate action of the selected state-action pair.

    AUTONOMOUS ORGANIC AQUATIC FILTRATION SYSTEMS

    公开(公告)号:US20230034365A1

    公开(公告)日:2023-02-02

    申请号:US17387312

    申请日:2021-07-28

    Abstract: Methods, systems, and computer-readable media that implement a mobile filtration system that provides sustainable, on-demand water filtration while supporting the growth and maintenance of organisms. The method includes determining an environmental parameter associated with a volume of water, determining, based on the determined environmental parameter, a control parameter for an autonomous submersible structure that includes a platform on which marine life grows, and generating, based on determining the control parameter, an instruction for the autonomous submersible structure.

    Automatic field of view detection
    94.
    发明授权

    公开(公告)号:US11562497B1

    公开(公告)日:2023-01-24

    申请号:US17482029

    申请日:2021-09-22

    Inventor: Yueqi Li

    Abstract: Implementations are described herein for analyzing a sequence of digital images captured by a mobile vision sensor (e.g., integral with a robot), in conjunction with information (e.g., ground truth) known about movement of the vision sensor, to determine spatial dimensions of object(s) and/or an area captured in a field of view of the mobile vision sensor. Techniques avoid the use of visual indicia of known dimensions and/or other conventional tools for determining spatial dimensions, such as checkerboards. Instead, techniques described herein allow spatial dimensions to be determined using less resources, and are more scalable than conventional techniques.

    Systems and Methods for Sampling Images

    公开(公告)号:US20230007157A1

    公开(公告)日:2023-01-05

    申请号:US17930928

    申请日:2022-09-09

    Abstract: An example method includes determining, by a controller of an image capture system, a plurality of sets of exposure parameter values for one or more exposure parameters. The plurality of sets of exposure parameter values are determined at an exposure determination rate. The method further includes capturing, by an image capture device of the image capture system, a plurality of images. Each image of the plurality of images is captured according to a set of exposure parameter values of the plurality of sets of exposure parameter values. The method also includes sending, by the controller of the image capture system to an image processing unit, a subset of the plurality of images. Each subset of images is sent at a sampling rate, and the sampling rate is less than the exposure determination rate.

    DATA AUGMENTATION USING BRAIN EMULATION NEURAL NETWORKS

    公开(公告)号:US20220414453A1

    公开(公告)日:2022-12-29

    申请号:US17360680

    申请日:2021-06-28

    Abstract: In one aspect, there is provided a method performed by one or more data processing apparatus, the method including receiving a training dataset having multiple training examples, where each training example includes: (i) an image, and (ii) a segmentation defining a target region of the image that has been classified as including pixels in a target category. The method further includes determining a respective refined segmentation for each training example, including, for each training example, processing the target region of the image defined by the segmentation for the training example using a de-noising neural network to generate a network output that defines the refined segmentation for the training example. The method further includes training a segmentation machine learning model on the training examples of the training dataset, including, for each training example training the segmentation machine learning model to process the image included in the training example to generate a model output that matches the refined segmentation for the training example.

    IMPLEMENTING NEURAL NETWORKS THAT INCLUDE CONNECTIVITY NEURAL NETWORK LAYERS USING SYNAPTIC CONNECTIVITY

    公开(公告)号:US20220414434A1

    公开(公告)日:2022-12-29

    申请号:US17362747

    申请日:2021-06-29

    Inventor: Lam Thanh Nguyen

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing connectivity neural network layers. One of the methods includes processing a network input using a neural network to generate a network output, comprising: generating a layer input to a connectivity layer of the neural network based on the network input, wherein the layer input to the connectivity layer comprises a plurality of input values arranged in a plurality of input channels; processing the layer input using the connectivity layer to generate a layer output comprising a plurality of output values arranged in a plurality of output channels; processing the plurality of output channels of the connectivity layer using a brain emulation subnetwork of the neural network to generate a brain emulation subnetwork output; and generating the network output based on the brain emulation subnetwork output.

    STATE ESTIMATION FOR A ROBOT EXECUTION SYSTEM

    公开(公告)号:US20220402123A1

    公开(公告)日:2022-12-22

    申请号:US17353609

    申请日:2021-06-21

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for state estimation in a robotics system. One of the systems includes an execution subsystem configured to drive one or more robots in an operating environment including continually evaluating a plurality of execution predicates, wherein each execution predicate comprises a rule having a predicate value, and wherein, whenever a state value that satisfies the predicate value of the predicate is detected by the execution subsystem, the execution subsystem is configured to trigger a corresponding action to be performed in the operating environment by the one or more robots. A state estimator is configured to continually execute a state estimation function using one or more sensor values or status messages obtained from the operating environment and to automatically update a discrete state value for a first execution predicate of the plurality of execution predicates evaluated by the execution subsystem.

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