Bounding sphere CAD model simplification for efficient collision detection in offline programming
Alex Visser, Zengxi Stephen Pan, Stephen van Duin
Abstract
Alex Visser, Zengxi Stephen Pan, Stephen van Duin
Abstract
Collision detection performance is one of the major bottlenecks of Automated Offline Programming (AOLP). Simplifying CAD models allows collision detection algorithms to run more quickly, as a result more complex procedures are able to be calculated in a reasonable amount of time using AOLP. This paper presents a randomised bounding volume method for calculating a sphere based representation of a CAD model while conservatively removing small features. The output has fewer spheres when compared with other sphere packing techniques due to the first stage of the algorithm which removes small features from the model. Using the representation generated by the bounding sphere simplification algorithm for collision detection can dramatically improve performance in simulations and motion planning processes commonly used in AOLP.
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Collision detection performance is one of the major bottlenecks of Automated Offline Programming (AOLP). Simplifying CAD models allows collision detection algorithms to run more quickly, as a result more complex procedures are able to be calculated in a reasonable amount of time using AOLP. This paper presents a randomised bounding volume method for calculating a sphere based representation of a CAD model while conservatively removing small features. The output has fewer spheres when compared with other sphere packing techniques due to the first stage of the algorithm which removes small features from the model. Using the representation generated by the bounding sphere simplification algorithm for collision detection can dramatically improve performance in simulations and motion planning processes commonly used in AOLP.
Key concepts: Collision detection, Bounding volume, Bounding overwatch, CAD, Representation (politics), Computer science, Collision, Minimum bounding box