Title
Fast collision detection through bounding volume hierarchies in workspace-time space for sampling-based motion planners
Abstract
This paper presents a fast collision-detection method for sampling-based motion planners based on bounding volume hierarchies in workspace-time space. By introducing time as an additional dimension to the robot's workspace, the method is able to quickly evaluate time-indexed candidate trajectories for collision with the known future motions of other agents. The approach makes no assumptions on the shape of the objects and is able to handle arbitrary motions. We highlight implementation details regarding the application of the collision detection technique within an online planning framework for automated driving. Furthermore, we give detailed profiling information to show the capability for real-time operation.
Year
DOI
Venue
2015
10.1109/ICRA.2015.7138981
2015 IEEE International Conference on Robotics and Automation (ICRA)
Keywords
Field
DocType
Collision detection,workspace-time space,bounding volume hierarchy,axis-aligned bounding box tree
Computer vision,Bounding volume,Collision detection,Profiling (computer programming),Computer science,Workspace,Collision,Artificial intelligence,Sampling (statistics),Robot,Trajectory
Conference
Volume
Issue
ISSN
2015
1
1050-4729
Citations 
PageRank 
References 
1
0.36
18
Authors
3
Name
Order
Citations
PageRank
Ulrich Schwesinger1333.16
Roland Siegwart27640551.49
Paul Timothy Furgale386942.35