Grasping of an object by a robot based on grasp strategy determined using machine learning model(s)

    公开(公告)号:US11097418B2

    公开(公告)日:2021-08-24

    申请号:US15862514

    申请日:2018-01-04

    Abstract: Grasping of an object, by an end effector of a robot, based on a grasp strategy that is selected using one or more machine learning models. The grasp strategy utilized for a given grasp is one of a plurality of candidate grasp strategies. Each candidate grasp strategy defines a different group of one or more values that influence performance of a grasp attempt in a manner that is unique relative to the other grasp strategies. For example, value(s) of a grasp strategy can define a grasp direction for grasping the object (e.g., “top”, “side”), a grasp type for grasping the object (e.g., “pinch”, “power”), grasp force applied in grasping the object, pre-grasp manipulations to be performed on the object, and/or post-grasp manipulations to be performed on the object.

    Sensorized Robotic Gripping Device

    公开(公告)号:US20220339803A1

    公开(公告)日:2022-10-27

    申请号:US17857443

    申请日:2022-07-05

    Abstract: A robotic gripping device is provided. The robotic gripping device includes a palm and a plurality of digits coupled to the palm. The robotic gripping device also includes a time-of-flight sensor arranged on the palm such that the time-of-flight sensor is configured to generate time-of-flight distance data in a direction between the plurality of digits. The robotic gripping device additionally includes an infrared camera, including an infrared illumination source, where the infrared camera is arranged on the palm such that the infrared camera is configured to generate grayscale image data in the direction between the plurality of digits.

    GRASPING OF AN OBJECT BY A ROBOT BASED ON GRASP STRATEGY DETERMINED USING MACHINE LEARNING MODEL(S)

    公开(公告)号:US20210347040A1

    公开(公告)日:2021-11-11

    申请号:US17379091

    申请日:2021-07-19

    Abstract: Grasping of an object, by an end effector of a robot, based on a grasp strategy that is selected using one or more machine learning models. The grasp strategy utilized for a given grasp is one of a plurality of candidate grasp strategies. Each candidate grasp strategy defines a different group of one or more values that influence performance of a grasp attempt in a manner that is unique relative to the other grasp strategies. For example, value(s) of a grasp strategy can define a grasp direction for grasping the object (e.g., “top”, “side”), a grasp type for grasping the object (e.g., “pinch”, “power”), grasp force applied in grasping the object, pre-grasp manipulations to be performed on the object, and/or post-grasp manipulations to be performed on the object.

    Positioning a Robot Sensor for Object Classification

    公开(公告)号:US20210187735A1

    公开(公告)日:2021-06-24

    申请号:US17193809

    申请日:2021-03-05

    Abstract: In one embodiment, a method includes receiving, from a first sensor on a robot, first sensor data indicative of an environment of the robot. The method also includes identifying, based on the first sensor data, an object of an object type in the environment of the robot, where the object type is associated with a classifier that takes sensor data from a predetermined pose relative to the object as input. The method further includes causing the robot to position a second sensor on the robot at the predetermined pose relative to the object. The method additionally includes receiving, from the second sensor, second sensor data indicative of the object while the second sensor is positioned at the predetermined pose relative to the object. The method further includes determining, by inputting the second sensor data into the classifier, a property of the object.

    Positioning a robot sensor for object classification

    公开(公告)号:US10967507B2

    公开(公告)日:2021-04-06

    申请号:US15968922

    申请日:2018-05-02

    Abstract: In one embodiment, a method includes receiving, from a first sensor on a robot, first sensor data indicative of an environment of the robot. The method also includes identifying, based on the first sensor data, an object of an object type in the environment of the robot, where the object type is associated with a classifier that takes sensor data from a predetermined pose relative to the object as input. The method further includes causing the robot to position a second sensor on the robot at the predetermined pose relative to the object. The method additionally includes receiving, from the second sensor, second sensor data indicative of the object while the second sensor is positioned at the predetermined pose relative to the object. The method further includes determining, by inputting the second sensor data into the classifier, a property of the object.

    Robot grip detection using non-contact sensors

    公开(公告)号:US10792809B2

    公开(公告)日:2020-10-06

    申请号:US15839109

    申请日:2017-12-12

    Abstract: A method is provided that includes controlling a robotic gripping device to cause a plurality of digits of the robotic gripping device to move towards each other in an attempt to grasp an object. The method also includes receiving, from at least one non-contact sensor on the robotic gripping device, first sensor data indicative of a region between the plurality of digits of the robotic gripping device. The method further includes receiving, from the at least one non-contact sensor on the robotic gripping device, second sensor data indicative of the region between the plurality of digits of the robotic gripping device, where the second sensor data is based on a different sensing modality than the first sensor data. The method additionally includes determining, using an object-in-hand classifier that takes as input the first sensor data and the second sensor data, a result of the attempt to grasp the object.

    Positioning a Robot Sensor for Object Classification

    公开(公告)号:US20190337152A1

    公开(公告)日:2019-11-07

    申请号:US15968922

    申请日:2018-05-02

    Abstract: In one embodiment, a method includes receiving, from a first sensor on a robot, first sensor data indicative of an environment of the robot. The method also includes identifying, based on the first sensor data, an object of an object type in the environment of the robot, where the object type is associated with a classifier that takes sensor data from a predetermined pose relative to the object as input. The method further includes causing the robot to position a second sensor on the robot at the predetermined pose relative to the object. The method additionally includes receiving, from the second sensor, second sensor data indicative of the object while the second sensor is positioned at the predetermined pose relative to the object. The method further includes determining, by inputting the second sensor data into the classifier, a property of the object.

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