Simulation level of detail for multiagent control

Many classes of applications require multiagent navigation control algorithms to specify the movements and actions of heterogeneous groups containing thousands of characters. The scale and complexity of these interacting character groups require navigation control algorithms that are both generalizable and specifically tuned to particular character platforms. We propose a technique called simulation level of detail (LOD) that provides a simulation-based interface between navigation control algorithms and the specific mobile characters on which they operate. A simulation LOD efficiently models a character's ability to move given its dynamic state and provides this simplified version of the character to navigation controllers for use in run-time search algorithms that compute locomotion actions. We develop our simulation LOD algorithms on groups of physically simulated human and alien bicyclists and demonstrate reusable controllers that provide improvements in path following and herding tasks.