A Hierarchical Collision Detection Algorithm for VA

This paper presents a Hierarchical Collision Detection Algorithm that is suitable for VA (Virtual Assembly). The proposed algorithm includes three level approaches which are preliminary detection, second detection and precision detection. The surround box approach was used for the preliminary detect...

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Bibliographic Details
Published in:2010 Chinese Control and Decision Conference pp. 4315 - 4319
Main Authors: Meiping Wu, Liyun Shi, Zhijun Ren
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2010
Subjects:
Algorithm design and analysis
Assembly Process Modeling
Assembly Sequence Planning
Assembly systems
Collision Detection Algorithm
Computational geometry
Detection algorithms
Mechanical engineering
Object detection
Process planning
Virtual environment
Virtual Environment (VE)
Virtual prototyping
Virtual reality
ISBN:1424451817, 9781424451814
ISSN:1948-9439
Online Access:Get full text
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Summary:This paper presents a Hierarchical Collision Detection Algorithm that is suitable for VA (Virtual Assembly). The proposed algorithm includes three level approaches which are preliminary detection, second detection and precision detection. The surround box approach was used for the preliminary detection, which can preclude a lot of detached part, and the detection quantity was reduced greatly. If two parts may collide or interfere, then, calculate the intersection region and storage the result in surround box S. The vector judgment approach was used to the second detection, which can reduce the half calculation working. The net-facet approach was utilized for the precision detection, which can quick calculate the opposite location of two parts. If they intersect we can get the intersection measure, otherwise, the nearest point or minimum distance between them can be got. By the algorithm, the calculation speed and detection accuracy are improved greatly and thereby can help in creation of the optimal assembly sequence quickly in virtual assembly environment.
ISBN:1424451817
9781424451814
ISSN:1948-9439
DOI:10.1109/CCDC.2010.5498377