Method and system for object grasping
AssigneeIntrinsic Innovation LLC
InventorsLi Yang Ku, Michael Stark, Ahmad Humayun, Nan Rong, Bhaskara Mannar Marthi
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Abstract
A method for object grasping, including: determining features of a scene; determining candidate grasp locations; determining a set of candidate grasp proposals for the candidate grasp locations; optionally modifying a candidate grasp proposal of the set; determining grasp scores associated with the candidate grasp proposals; selecting a set of final grasp proposals based on the grasp scores; and executing a grasp proposal from the set of final grasp proposals.
Claims20
A method, comprising:
- determining a set of data for an object in a scene, each of the set of data comprising a respective keypoint and a corresponding object component identifier;
- determining a set of candidate grasp locations for the object, using the set of data, wherein each candidate grasp location of the set of candidate grasp locations is associated with a respective occlusion score determined by a machine learning model trained on images labeled with predetermined occlusion scores for locations in the images;
- determining one or more candidate grasp proposals based on the set of candidate grasp locations for grasping the object;
- selecting a candidate grasp proposal from the one or more candidate grasp proposals as a final grasp proposal based on one or more criteria;
- and
- storing the final grasp proposal in memory to be retrieved for controlling a robot to grasp the object.
A system comprising:
- one or more computers and one or more non-transitory storage devices on which are stored instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
- determining a set of data for an object in a scene, each of the set of data comprising a respective keypoint and a corresponding object component identifier;
- determining a set of candidate grasp locations for the object, using the set of data, wherein each candidate grasp location of the set of candidate grasp locations is associated with a respective occlusion score determined by a machine learning model trained on images labeled with predetermined occlusion scores for locations in the images;
- determining one or more candidate grasp proposals based on the set of candidate grasp locations for grasping the object;
- selecting a candidate grasp proposal from the one or more candidate grasp proposals as a final grasp proposal based on one or more criteria;
- and
- storing the final grasp proposal in memory to be retrieved for controlling a robot to grasp the object.
One or more non-transitory computer storage media encoded with computer program instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:
- determining a set of data for an object in a scene, each of the set of data comprising a respective keypoint and a corresponding object component identifier;
- determining a set of candidate grasp locations for the object, using the set of data, wherein each candidate grasp location of the set of candidate grasp locations is associated with a respective occlusion score determined by a machine learning model trained on images labeled with predetermined occlusion scores for locations in the images;
- determining one or more candidate grasp proposals based on the set of candidate grasp locations for grasping the object;
- selecting a candidate grasp proposal from the one or more candidate grasp proposals as a final grasp proposal based on one or more criteria;
- and
- storing the final grasp proposal in memory to be retrieved for controlling a robot to grasp the object.
Dependencies are inferred from the claim text.