Time Advancement and Bounds Intersection Checking for Faster Broad-Phase Collision Detection of Paired Object Trajectories

For self-driving mechanisms, the motion planning requires a reasonably fast algorithm for collision detection along the trajectories. We present three algorithms for the detection of collision among objects with predefined trajectories. The first algorithm uses the intersection of the path’s bounding box. The second algorithm sequentially checks for intersection between each pair of corresponding axis-aligned bounding boxes (AABB) from the trajectories of the two paths. Lastly, the latter algorithm is modified using iterative time advancement to an estimated earliest possible collision time. Simulation experiments on a variety of pair trajectories demonstrate a significant speedup of the proposed algorithms over the existing baseline algorithm. They are, therefore, preferable alternatives for faster broad-phase collision detection in applications such as motion planning

International Journal of Shape Modeling c ○ World Scientific Publishing Company TEMPORAL COHERENCE IN BOUNDING VOLUME HIERARCHIES FOR COLLISION DETECTION

Collision detection is a fundamental problem in computer graphics. In this paper, temporal coherence is studied and an algorithm exploiting it for bounding volume hierarchies, is presented. We show that maintaining some of the intersection tests computed in the previous frame, along with certain information, is able to speedup the intersection tests considerably. The algorithm is able to accelerate the collision detection for small motions and works as fast as the regular algorithm for large motions, where temporal coherence does not exist. The algorithm framework can be implemented for any type of bounding volume hierarchy. To demonstrate this, it was implemented for the OBB and the AABB data structures and tested on several benchmark scenarios