Argus:智能手机支持的人类合作，通过MARL进行灾难态势感知

2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) Pub Date : 2017-03-13 DOI:10.1109/PERCOMW.2017.7917529

Vidyasagar Sadhu, Gabriel Salles-Loustau, D. Pompili, S. Zonouz, Vincent Sritapan

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引用次数: 14

摘要

Argus利用多智能体强化学习(MARL)框架，利用事故区域周围的智能体创建灾难现场的3D地图，以促进救援行动。代理人既可以是灾难现场的人类旁观者，也可以是可以帮助人类的无人机或机器人。在MARL算法的指导下，代理使用智能手机(或无人机上的机载摄像头)捕捉场景图像。这些图像用于构建灾难现场的实时3D地图。在本文中，我们展示了我们的方法的一个演示。

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

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.

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2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)

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