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In this paper, an approach for matching of primitive shapes detected from point clouds, to boundary representations of primitive shapes contained in CAD models of objects/workpieces is presented. The primary target application is object detection and pose estimation from noisy RGBD sensor data. This approach can also be used to determine incomplete object poses, including those of symmetrical objects...
In this paper, we propose a framework for intuitive task-based programming of robots using geometric inter-relational constraints. The intended applications of this framework are robot programming interfaces that use semantically rich task descriptions, allow intuitive (re-)programming, and are suitable for non-expert users typically found in SMEs. A key concept in this work is the use of CAD semantics...
In this paper, we introduce an approach for leveraging CAD description to a semantic level, in order to link additional knowledge to CAD models and to exploit resulting synergy effects.
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