結合改良式物件姿態估測之最佳機器人夾取策略

dc.contributor許陳鑑zh_TW
dc.contributorHsu, Chen-Chienen_US
dc.contributor.author游鈞凱zh_TW
dc.contributor.authorYou, Jiun-Kaien_US
dc.date.accessioned2022-06-08T02:37:02Z
dc.date.available9999-12-31
dc.date.available2022-06-08T02:37:02Z
dc.date.issued2021
dc.description.abstractnonezh_TW
dc.description.abstract['Thanks to the recent advancement in technology, robotic development has been gradually evolved from traditional industrial robots capable of performing repetitive and routine tasks to intelligent robots with autonomous vision-based grasping strategy to satisfy the needs for various applications in industries, for example, flexible production in low-volume automation for small and medium-sized businesses (SMBs). To accurately execute tasks for various robots, including industrial, service, andcooperative robots, robotic grasping of objects dominates the performance and reliability for a robotic system. Therefore, an optimal robotic grasping strategy incorporating a multiple-object pose estimation mechanism is presented in this thesis, where a RGB camera, rather than a RGB-D camera, is only used to estimate the 6DoF object pose in the images through a proposed object pose estimation system incorporating a projection loss function and refinement network. On the basis of the obtained 6-DoF object pose estimation, we can analyze the transformed 3D cloud of the object via the estimated object pose to derive an optimal grasp pose for the robot arm. As a result, the robotic system can efficiently grasp objects with arbitrary poses in the environment.']en_US
dc.description.sponsorship電機工程學系zh_TW
dc.identifier60875004H-38884
dc.identifier.urihttps://etds.lib.ntnu.edu.tw/thesis/detail/8c6bbe784368478f32f1668892fe1d1d/
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/116955
dc.language英文
dc.subjectnonezh_TW
dc.subjectobject pose estimationen_US
dc.subjectLINEMODen_US
dc.subjectOcclusion LINEMODen_US
dc.subjectgrasp strategyen_US
dc.title結合改良式物件姿態估測之最佳機器人夾取策略zh_TW
dc.titleOptimal Robotic Grasping Strategy Incorporating Improved Object Pose Estimationen_US
dc.type學術論文

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