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Collision detection during planning for sheet metal bending by bounding volume hierarchy approaches

ABSTRACT Collision detection is a computationally intensive task within process planning for sheet metal bending. An efficient collision detection algorithm can greatly improve the speed of the process planning. In this work, relevant features are extracted first from STL format of the part and tool models. Next, the collision detection strategies for the sheet metal bending problem are investigated considering bounding volume hierarchies involving oriented-bounding box (OBB) and axis-aligned bounding box (AABB) methods. The approaches are explained using two example parts. By analysing the data for 10 different sheet metal parts, it is demonstrated that although OBB hierarchy is more efficient in terms of minimising the number of collision tests between part and tool models, AABB hierarchy is superior in terms of computation time. The collision detection method based on AABB can be integrated with the sheet metal bend planning to realise CAD–CAM integration.