主动 发表于 2025-3-23 12:23:12
Italian Academies and Their Facebooks,tables. After successful localization, a collision avoidance mechanism is introduced reducing the problem’s complexity by interpreting the point clouds as depth maps and using 2D image analysis. The chapter is concluded by the presentation of experiments demonstrating the potential of the approach.MOTIF 发表于 2025-3-23 16:58:07
http://reply.papertrans.cn/19/1863/186266/186266_12.pngEfflorescent 发表于 2025-3-23 18:40:45
https://doi.org/10.1007/978-3-319-74757-6shots. By analyzing normal histograms (Extended Gaussian Images) the orientation is computed, to then get the position. The position estimation is described in 2 different ways, one two step and one single step approach which is capable of delivering accurate positions using a monocular camera. Expeingenue 发表于 2025-3-24 02:02:20
http://reply.papertrans.cn/19/1863/186266/186266_14.png纺织品 发表于 2025-3-24 06:19:36
http://reply.papertrans.cn/19/1863/186266/186266_15.png精致 发表于 2025-3-24 10:33:29
,Introduction—Automation and the Need for Pose Estimation,In this chapter, the topic of the book is introduced. It is explained, how object pose estimation is the basis of many automation tasks. The bin-picking problem as one of the famous examples of robotic automation is shortly introduced.勾引 发表于 2025-3-24 11:55:16
http://reply.papertrans.cn/19/1863/186266/186266_17.pngFOR 发表于 2025-3-24 17:48:40
http://reply.papertrans.cn/19/1863/186266/186266_18.pnglabyrinth 发表于 2025-3-24 22:04:26
3D Point Cloud Based Pose Estimation,tables. After successful localization, a collision avoidance mechanism is introduced reducing the problem’s complexity by interpreting the point clouds as depth maps and using 2D image analysis. The chapter is concluded by the presentation of experiments demonstrating the potential of the approach.全等 发表于 2025-3-25 00:09:05
Depth Map Based Pose Estimation,r very efficient scene analysis. An approach is described how grasp poses on unknown objects can be computed in real-time allowing for near time optimal grasping. It is further described how the approach can be extended for bin-picking tasks of known objects by combining the visual scene analysis wi