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DOI:10.1109/ROBOT.1994.351059Corpus ID: 10714019
Efficient distance computation between non-convex objects
S. Quinlan
Published 1994
Mathematics, Computer Science
Proceedings of the 1994 IEEE International Conference on Robotics and Automation
This paper describes an efficient algorithm for computing the distance between nonconvex objects. Objects are modeled as the union of a set of convex components. From this model we construct a hierarchical bounding representation based on spheres. The distance between objects is determined by computing the distance between pairs of convex components using preexisting techniques. The key to efficiency is a simple search routine that uses the bounding representation to ignore most of the possible… CONTINUE READING
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References
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A fast algorithm for incremental distance calculation
M. Lin, J. Canny
Mathematics, Computer Science
Proceedings. 1991 IEEE International Conference on Robotics and Automation
1991
552PDF
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A fast procedure for computing the distance between complex objects in three-dimensional space
E. Gilbert, D. W. Johnson, S. Keerthi
Computer Science
IEEE J. Robotics Autom.
1988
1,222PDF
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A Direct Minimization Approach for Obtaining the Distance between Convex Polyhedra
James E. Bobrow
Mathematics, Computer Science
Int. J. Robotics Res.
1989
117
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Efficient collision detection for animation and robotics
M. Lin, J. Canny
Mathematics
1993
311
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Determining the Separation of Preprocessed Polyhedra – A Unified Approach
D. Dobkin, D. Kirkpatrick
Computer Science
ICALP
1990
243
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OBBTree: a hierarchical structure for rapid interference detection
Stefan Gottschalk, M. Lin, D. Manocha
Computer Science
SIGGRAPH
1996
1,827PDF
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Approximating polyhedra with spheres for time-critical collision detection
Philip M. Hubbard
Computer Science
TOGS
1996
543PDF
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I-COLLIDE: an interactive and exact collision detection system for large-scale environments
J. Cohen, M. Lin, D. Manocha, Madhav K. Ponamgi
Computer Science
I3D ’95
1995
778PDF
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Hierarchical object models for efficient anti-collision algorithms
B. Faverjon
Computer Science
Proceedings, 1989 International Conference on Robotics and Automation
1989
42
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A new representation for collision avoidance and detection
A. P. Pobil, Miguel A. Serna, Juan Llovet
Mathematics, Computer Science
Proceedings 1992 IEEE International Conference on Robotics and Automation
1992
56
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