Title
Plane-Based Local Behaviors for Multi-Agent 3D Simulations with Position-Based Dynamics
Abstract
Position-Based Dynamics (PBD) has been shown to provide a flexible framework for modeling per-agent collision avoidance behavior for crowd and multi-agent simulations in planar scenarios. In this work, we propose to extend the approach such that collision avoidance reactions can utilize in a controlled way the volumetric 3D space around each agent when deciding how to avoid collisions with other agents. We propose to use separation planes for collision avoidance, using either preferred or automatically determined planes. Our results demonstrate the ability to control the spatial 3D behavior of simulated agents by constraining the produced movements according to the separation planes. Our method is generic and can be integrated with different crowd simulation techniques. We also compare our results with a 3D collision avoidance method based on Reciprocal Velocity Obstacles (RVOs).
Year
DOI
Venue
2020
10.1109/AIVR50618.2020.00044
2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)
Keywords
DocType
ISBN
crowd simulation,3D multi-agent simulation,3D collision avoidance
Conference
978-1-7281-7464-8
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Ritesh Sharma1103.25
Tomer Weiss201.69
Marcelo Kallmann363959.35