EMT: Collaborative Research: Primate-inspired Heterogeneous Mobile and Static Sensor Networks

EMT：协作研究：受灵长类动物启发的异构移动和静态传感器网络尽管以前的生物启发模型主要集中在无脊椎动物（如蚂蚁）上，但具有更高认知功能的灵长类动物等哺乳动物对于建模日益复杂的工程问题很有价值。了解灵长类动物吗?社会和通信系统，并将从中学到的知识应用于工程领域，可能会激发许多问题的解决方案。本研究包括对铜tit猴、恒河猴和其他灵长类动物的群体行为和交流模式进行研究和建模，并将研究成果应用于异构移动和静态传感器网络的分布式控制。研究人员将对这些灵长类动物的社会和交流行为进行建模，这将为解决交流和网络问题提供生物学灵感。本研究的阶段包括：1)识别、解释和翻译灵长类动物行为模型；2)评估基于灵长类动物在异构移动和静态传感器网络中的分组模型的小群体和大群体形成的有效性；3)开发基于生物启发的基于消息的通信；4)开发基于生物启发的基于行为的通信。本研究旨在通过对灵长类动物的研究，更深入地了解仿生通信和网络的有效性，并在生物建模、传感器网络和机器人控制领域建立跨学科的研究和教育。

EMT: Collaborative Research: Primate-inspired Heterogeneous Mobile and Static Sensor Networks Although previous bio-inspired models have concentrated on invertebrates (such as ants), mammals such as primates with higher cognitive function are valuable for modeling the increasingly complex problems in engineering. Understanding primates? social and communication systems, and applying what is learned from them to engineering domains is likely to inspire solutions to a number of problems.This research involves studying and modeling modes of group behavior and communication of coppery titi monkeys, rhesus macaques, and other primate models, and applying what the investigators learn to the distributed control of heterogeneous mobile and static sensor networks. The investigators will model the social and communication behavior of these primates, which will provide biological inspiration for solving problems in communication and networking. The phases of this research include: 1) identification, interpretation, and translation of primate behavioral models, 2) assessment of the effectiveness of small and large group formations based on primate grouping models in heterogeneous mobile and static sensor networks, 3) development of bio-inspired message-based communications, and 4) development of bio-inspired behavior-based communications. This research aims to achieve a deeper understanding of effectiveness of bio-inspired communications and networking by studying primates, and to establish interdisciplinary research and education in the fields of biological modeling, sensor networking, and robots control.