The techniques and implementation of fast collision detection for three-dimension pipeline

Zhongliang Fu; Shiwei Shao

doi:10.1117/12.838607

15 October 2009 The techniques and implementation of fast collision detection for three-dimension pipeline

Zhongliang Fu, Shiwei Shao

Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74923F (2009) https://doi.org/10.1117/12.838607
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China

Abstract

In the design of engineering pipeline, spatial collision detection is always a necessary process. If the artificial method is used, a heavy work load is always needed and omissions occasionally happens; if the method of collision detection algorithm for three dimension object in graphics is used, the computation will increasing sharply with the increase of pipeline number. Because the data size of three dimension pipeline is extremely big, the key to solve collision problem is efficiency. In this paper, a new collision detection method for three dimension pipeline is presented. The new method is composed of two parts: the coarse detection based on Axis-Aligned Bounding Box and precise detection based on geometry model. The method abstracts the pipeline to spatial line-segments with semantic information using geometry method. Firstly, an improved Axis-Aligned Bounding Box algorithm is used to classify the pipelines. Finally, the result of coarse detection is used as initial value, the geometry location relation is used to classify the pipelines, and then the shortest connecting lines between pipelines are calculated. The experiment results show that, this method can detect collision three-dimension pipeline efficiently.

Citation Download Citation

Zhongliang Fu and Shiwei Shao "The techniques and implementation of fast collision detection for three-dimension pipeline", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74923F (15 October 2009); https://doi.org/10.1117/12.838607

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