2021 IEEE International Conference on Robotics and Automation (ICRA) | 2021

Saliency Features for 3D CAD-Data in the Context of Sampling-Based Motion Planning

 
 
 

Abstract


In this paper, we consider disassembly scenarios for real-world 3D CAD-data, where each component is defined by a triangle mesh. For a fast construction of collision-free disassembly paths, common approaches use sampling-based rigid body motion planning which is well studied in the literature. One fact that has so far received little attention is that in industrial disassembly scenarios components are often attached to each other with flexible fastening elements like clips. In the planning process, the fastening elements show the following characteristics: 1) They can cause complex non-linear disassembly paths. 2) They are often deformable. 3) They are usually modeled in a relaxed state and as an unknown part of the rigid mesh. That leads to the problem that unavoidable collisions occur during the planning process. Hence, the localization of the fastening elements and the integration of this information into the motion planning process is crucial for an automatic disassembly.We present a new geometric solution to extract salient features of 3D meshes which is specialized to find the fastening elements within the otherwise rigid mesh. Our approach measures a vertex-based surface feature using a local Gauss map in combination with a local thickness computation of the mesh. We compare our surface feature to state-of-the-art mesh saliency methods on various examples. Further, we integrate this measure of per-vertex saliency into a motion planning process and demonstrate the effectiveness of our result on real-world planning scenarios from the automotive industry.

Volume None
Pages 7858-7864
DOI 10.1109/ICRA48506.2021.9560979
Language English
Journal 2021 IEEE International Conference on Robotics and Automation (ICRA)

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