机器人灾难响应的人工智能和物联网

Min-Fan Ricky Lee, Tzu-Wei Chien
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引用次数: 9

摘要

在福岛核灾难和汶川地震之后,相关政府机构认识到灾难应变机器人的紧迫性。台湾有许多天灾人祸,通常不可能立即派出相关人员进行搜寻或探索。项目提出利用智能物联网(AIoT)(人工智能+物联网)架构与地面、水面、空中、水下机器人协同,应用于灾害响应,地面、水面、空中、水下群机器人从灾难现场采集环境大数据,然后通过物联网。从现场工作站到云端进行“训练”深度学习模型和“模型验证”,经过训练的深度学习模型通过物联网传输到现场工作站,再传输到地面、水面、空中和水下的群体机器人进行现场连续物体分类。不断验证与环境的“识别”,并为响应做出最佳决策。相关任务包括监视、搜索和营救目标。
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Artificial Intelligence and Internet of Things for Robotic Disaster Response
After the Fukushima nuclear disaster and the Wenchuan earthquake, the relevant government agencies recognized the urgency of disaster-straining robots. There are many natural or man-made disasters in Taiwan, and it is usually impossible to dispatch relevant personnel to search or explore immediately. The project proposes to use the architecture of Intelligent Internet of Things (AIoT) (Artificial Intelligence + Internet of Things) to coordinate with ground, surface and aerial and underwater robots, and apply them to disaster response, ground, surface and aerial and underwater swarm robots to collect environmental big data from the disaster site, and then through the Internet of Things. From the field workstation to the cloud for “training” deep learning model and “model verification”, the trained deep learning model is transmitted to the field workstation via the Internet of Things, and then transmitted to the ground, surface and aerial and underwater swarm robots for on-site continuing objects classification. Continuously verify the “identification” with the environment and make the best decisions for the response. The related tasks include monitoring, search and rescue of the target.
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