  Argus exploits a Multi-Agent Reinforcement Learning (MARL) framework to
create a 3D mapping of the disaster scene using agents present around the
incident zone to facilitate the rescue operations. The agents can be both human
bystanders at the disaster scene as well as drones or robots that can assist
the humans. The agents are involved in capturing the images of the scene using
their smartphones (or on-board cameras in case of drones) as directed by the
MARL algorithm. These images are used to build real time a 3D map of the
disaster scene. Via both simulations and real experiments, an evaluation of the
framework in terms of effectiveness in tracking random dynamicity of the
environment is presented.
