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公开(公告)号:EP4332900A1
公开(公告)日:2024-03-06
申请号:EP22192858.3
申请日:2022-08-30
发明人: MOURA CIRILO ROCHA, Eduardo , ERDOGAN, Husnu Melih , SOLOWJOW, Eugen , UGALDE DIAZ, Ines , SHAHAPURKAR, Yash , TIAN, Nan , BATSII, Pavlo , SCHÜTTE, Christopher
IPC分类号: G06T7/73
摘要: It is recognized herein that current approaches to robotic picking lack efficiency and capabilities. In particular, current approaches often do not properly or efficiently estimate the pose of bins, due to various technical challenges in doing so, which can impact grasp computations and overall performance of a given robot. The pose of the bin can be determined or estimated based on depth images. Such bin pose estimation can be performed during runtime of a given robot, such that grasping can be enhanced due to the bin pose estimations.
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公开(公告)号:EP4249178A1
公开(公告)日:2023-09-27
申请号:EP22164356.2
申请日:2022-03-25
发明人: UGALDE DIAZ, Ines , SOLOWJOW, Eugen , SHAHAPURKAR, Yash , ERDOGAN, Husnu Melih , MOURA CIRILO ROCHA, Eduardo
摘要: It is recognized herein that robots or autonomous systems can lose time when computing grasp scores for empty bins. Further, when grasps are attempted on empty bins, for instance due to the related grasp score computations, the robot can lose additional time through being used unnecessarily to attempt the grasp. Such usage can wear on the robot, or damage the robot, in some cases. An autonomous system can classify or determine whether a bin contains an object or is empty, for example, such that a grasp computation is not performed when the bin is empty. In some examples, a system classifies a given bin at runtime before each grasp computation is performed. Thus, systems described herein can avoid performing unnecessary grasp computations, thereby conserving processing time and overheard, among addressing other technical problems.
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公开(公告)号:EP4249177A1
公开(公告)日:2023-09-27
申请号:EP22163566.7
申请日:2022-03-22
发明人: UGALDE DIAZ, Ines , SOLOWJOW, Eugen , SHAHAPURKAR, Yash , ERDOGAN, Husnu Melih , MOURA CIRILO ROCHA, Eduardo
IPC分类号: B25J9/16
摘要: It is recognized herein that current approaches to robotic bin picking based on depth images can introduce technical issues, for example issues related to identifying grasp points of particular objects in bins. Based on color images of a given bin having a group of objects, grasp point identification can be performed on objects that are packed in such a manner that a depth image might not detect accurate boundaries associated with particular objects in the group.
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