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).