Skip to main content
Log in

Efficient Collision Detection among Moving Spheres with Unknown Trajectories

  • Published:
Algorithmica Aims and scope Submit manuscript

Abstract

Collision detection is critical for applications that demand a great deal of spatial interaction among objects. In such applications the trajectory of an object is often not known in advance either since a user is allowed to move an object at his/her will, or since an object moves under the rules that are hard to describe by exact mathematical formulas. In this paper we present a new algorithm that efficiently detects the collisions among moving spheres with unknown trajectories. We assume that the current position and velocity of every sphere can be probed at any time although its trajectory is unknown. We also assume that the magnitude of the acceleration of each sphere is bounded. Under these assumptions, we represent the bounding volume of the sphere as a moving sphere of variable radius, called a time-varying bound. Whenever the time-varying bounds of two spheres collide with each other, they are checked for actual collision. Exploiting these bounds, the previous event-driven approach for detecting the collisions among multiple moving spheres with ballistic trajectories is generalized for those with unknown trajectories. The proposed algorithm shows an interactive performance for thousands of moving spheres with unknown trajectories without any hardware help.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Ho Kyung Kim, Leonidas J. Guibas or Sung Yong Shin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kim, H., Guibas, L. & Shin, S. Efficient Collision Detection among Moving Spheres with Unknown Trajectories. Algorithmica 43, 195–210 (2005). https://doi.org/10.1007/s00453-005-1153-2

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00453-005-1153-2

Navigation