Semantic zone separation for map generation

    公开(公告)号:US11194994B2

    公开(公告)日:2021-12-07

    申请号:US15848561

    申请日:2017-12-20

    Abstract: Methods, systems, and apparatus for receiving a mapping of a property that includes a three-dimensional representation of the property, receiving observations of the property that each depict a portion of the property, providing the mapping and the observations to an object mapping engine, receiving an object mapping of the property, wherein the object mapping includes a plurality of object labels that each identify an object that was recognized from the observations and a location of the object within the three-dimensional representation that corresponds to a physical location of the object in the property, and obtaining a semantic mapping of the property that identifies semantic zones of the property with respect to the three-dimensional representation, wherein the semantic mapping is generated based on an output that results from a semantic mapping model processing the object mapping.

    Semantic Mapping of Environments for Autonomous Devices

    公开(公告)号:US20210041881A1

    公开(公告)日:2021-02-11

    申请号:US17001259

    申请日:2020-08-24

    Abstract: Methods, systems, and apparatus for receiving a reference to an object located in an environment of a robot, accessing mapping data that indicates, for each of a plurality of object instances, respective probabilities of the object instance being located at one or more locations in the environment, wherein the respective probabilities are based at least on an amount of time that has passed since a prior observation of the object instance was made, identifying one or more particular object instances that correspond to the referenced object, determining, based at least on the mapping data, the respective probabilities of the one or more particular object instances being located at the one or more locations in the environment, selecting, based at least on the respective probabilities, a particular location in the environment where the referenced object is most likely located, and directing the robot to navigate to the particular location.

    Mitigating reality gap through optimization of simulated hardware parameter(s) of simulated robot

    公开(公告)号:US11707840B1

    公开(公告)日:2023-07-25

    申请号:US17535373

    申请日:2021-11-24

    CPC classification number: B25J9/163 B25J9/1653 G05B13/0265 G05B13/042

    Abstract: Mitigating the reality gap through optimization of one or more simulated hardware parameters for simulated hardware components of a simulated robot. Implementations generate and store real navigation data instances that are each based on a corresponding episode of locomotion of a real robot. A real navigation data instance can include a sequence of velocity control instances generated to control a real robot during a real episode of locomotion of the real robot, and one or more ground truth values, where each of the ground truth values is a measured value of a corresponding property of the real robot (e.g., pose). The velocity control instances can be applied to a simulated robot, and one or more losses can be generated based on comparing the ground truth value(s) to corresponding simulated value(s) generated from applying the velocity control instances to the simulated robot. The simulated hardware parameters and environmental parameters can be optimized based on the loss(es).

    Semantic mapping of environments for autonomous devices

    公开(公告)号:US10754343B2

    公开(公告)日:2020-08-25

    申请号:US15897568

    申请日:2018-02-15

    Abstract: Methods, systems, and apparatus for receiving a reference to an object located in an environment of a robot, accessing mapping data that indicates, for each of a plurality of object instances, respective probabilities of the object instance being located at one or more locations in the environment, wherein the respective probabilities are based at least on an amount of time that has passed since a prior observation of the object instance was made, identifying one or more particular object instances that correspond to the referenced object, determining, based at least on the mapping data, the respective probabilities of the one or more particular object instances being located at the one or more locations in the environment, selecting, based at least on the respective probabilities, a particular location in the environment where the referenced object is most likely located, and directing the robot to navigate to the particular location.

    Semantic Place Recognition and Localization
    16.
    发明申请

    公开(公告)号:US20200265232A1

    公开(公告)日:2020-08-20

    申请号:US16751361

    申请日:2020-01-24

    Abstract: Methods, systems, and apparatus for receiving data that represents a portion of a property that was obtained by a robot, identifying, based at least on the data, objects that the data indicates as being located within the portion of the property, determining, based on the objects, a semantic zone type corresponding to the portion of the property, accessing a mapping hierarchy for the property, wherein the mapping hierarchy for the property specifies semantic zones of the property that have corresponding semantic zone types and are associated with locations at the property, and specifies characteristics of the semantic zones, and selecting, from among the semantic zones and based at least on the semantic zone type and the data, a particular semantic zone, and setting, as a current location of the robot at the property, a particular location at the property associated with the particular semantic zone.

    SEMANTIC ZONE SEPARATION FOR MAP GENERATION
    17.
    发明申请

    公开(公告)号:US20190188477A1

    公开(公告)日:2019-06-20

    申请号:US15848561

    申请日:2017-12-20

    Abstract: Methods, systems, and apparatus for receiving a mapping of a property that includes a three-dimensional representation of the property, receiving observations of the property that each depict a portion of the property, providing the mapping and the observations to an object mapping engine, receiving an object mapping of the property, wherein the object mapping includes a plurality of object labels that each identify an object that was recognized from the observations and a location of the object within the three-dimensional representation that corresponds to a physical location of the object in the property, and obtaining a semantic mapping of the property that identifies semantic zones of the property with respect to the three-dimensional representation, wherein the semantic mapping is generated based on an output that results from a semantic mapping model processing the object mapping.

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