| 期刊全称 | Bin-Picking | | 期刊简称 | New Approaches for a | | 影响因子2023 | Dirk Buchholz | | 视频video | | | 发行地址 | Presents three full approaches to solve the bin-picking problem: based on normal maps, using depth maps, and based on point clouds in combination with depth maps.Explains the three approaches in detai | | 学科分类 | Studies in Systems, Decision and Control | | 图书封面 |  | | 影响因子 | .This bookis devoted to one of the most famous examples of automation handling tasks –the “bin-picking” problem. To pick up objects, scrambled in a box is aneasy task for humans, but its automation is very complex. In this book threedifferent approaches to solve the bin-picking problem are described, showinghow modern sensors can be used for efficient bin-picking as well as how classicsensor concepts can be applied for novel bin-picking techniques. 3D pointclouds are firstly used as basis, employing the known Random Sample Matchingalgorithm paired with a very efficient depth map based collision avoidancemechanism resulting in a very robust bin-picking approach. Reducing thecomplexity of the sensor data, all computations are then done on depth maps.This allows the use of 2D image analysis techniques to fulfill the tasks andresults in real time data analysis. Combined with force/torque and accelerationsensors, a near time optimal bin-picking system emerges. Lastly, surfacenormalmaps are employed as a basis for pose estimation. In contrast to knownapproaches, the normal maps are not used for 3D data computation but directlyfor the object localization problem, enabling the application | | Pindex | Book 2016 |
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发表于 2025-3-21 18:06:26
