Abstract
We present a novel algorithm for collision-free navigation of a large number of independent agents in complex and dynamic environments. We introduce adaptive roadmaps to perform global path planning for each agent simultaneously. Our algorithm takes into account dynamic obstacles and interagents interaction forces to continuously update the roadmap based on a physically-based dynamics simulator. In order to efficiently update the links, we perform adaptive particle-based sampling along the links. We also introduce the notion of "link bands" to resolve collisions among multiple agents. In practice, our algorithm can perform real-time navigation of hundreds and thousands of human agents in indoor and outdoor scenes.
| Original language | English (US) |
|---|---|
| Article number | 4544511 |
| Pages (from-to) | 34-48 |
| Number of pages | 15 |
| Journal | IEEE Transactions on Visualization and Computer Graphics |
| Volume | 15 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2009 |
Bibliographical note
Funding Information:This work was supported in part by the Department of Energy High Performance Computer Science Fellowship administered by the Krell Institute, US Army Research Office, US National Science Foundation, RDECOM, and Intel. The authors would like to acknowledge members of the UNC GAMMA Group for useful discussions and feedback. The authors are also grateful to the anonymous reviewers for their comments.
Keywords
- Crowd simulation
- Multiagent path planning
- Pedestrian dynamics