OPTIMIZATION OF PACKAGE WEIGHT DISTRIBUTION
    36.
    发明公开

    公开(公告)号:US20230245036A1

    公开(公告)日:2023-08-03

    申请号:US18100940

    申请日:2023-01-24

    CPC classification number: G06Q10/083

    Abstract: The present application discloses a method, system, and computer system for arranging a set of objects for loading to a transport container. The method includes (i) receiving an indication of the set of objects to be loaded into the transport container for transport from a source location to a destination location, (ii) determining, based at least in part on object information corresponding to the set of objects and resources available to load the set of objects, an arrangement of the set of objects loaded into the transport container that satisfies a weight distribution criteria, and (iii) providing the arrangement as an output to be used in connection with loading the set of objects to the transport container.

    Robotic multi-item type palletizing and depalletizing

    公开(公告)号:US11591169B2

    公开(公告)日:2023-02-28

    申请号:US17211679

    申请日:2021-03-24

    Abstract: Techniques are disclosed to use a robotic arm to palletize or depalletize diverse items. In various embodiments, data associated with a plurality of items to be stacked on or in a destination location is received. A plan to stack the items on or in the destination location is generated based at least in part on the received data. The plan is implemented at least in part by controlling a robotic arm of the robot to pick up the items and stack them on or in the receptacle according to the plan, including by for each item: using one or more first order sensors to move the item to a first approximation of a destination position for that item at the destination location; and using one or more second order sensors to snug the item into a final position.

    AUTONOMOUS UNKNOWN OBJECT PICK AND PLACE
    40.
    发明申请

    公开(公告)号:US20200316782A1

    公开(公告)日:2020-10-08

    申请号:US16834115

    申请日:2020-03-30

    Abstract: A set of one or more potentially graspable features for one or more objects present in a workspace area are determined based on visual data received from a plurality of cameras. For each of at least a subset of the one or more potentially graspable features one or more corresponding grasp strategies are determined to grasp the feature with a robotic arm and end effector. A score associated with a probability of a successful grasp of a corresponding feature is determined with respect to each of a least a subset of said grasp strategies. A first feature of the one or more potentially graspable features is selected to be grasped using a selected grasp strategy based at least in part on a corresponding score associated with the selected grasp strategy with respect to the first feature. The robotic arm and the end effector are controlled to attempt to grasp the first feature using the selected grasp strategy.

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