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Argus: Smartphone-enabled human cooperation for disaster situational awareness via MARL

Vidyasagar Sadhu, Gabriel Salles-Loustau, Dario Pompili, Saman Zonouz, Vincent Sritapan

Year
2017
Citations
14

Abstract

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. In this paper, we present a demo of our approach.

Keywords

DroneArgusSituation awarenessComputer scienceExploitReinforcement learningHuman–computer interactionRobotArtificial intelligenceSearch and rescue

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