RI: Small: Collaborative Research: Bio-inspired Collaborative Sensing with Novel Gliding Robotic Fish

RI：小型：协作研究：新型滑翔机器鱼的仿生协作传感

• 批准号: 1319602
• 负责人: Xiaobo Tan
• 金额: $ 25.73万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1319602&HistoricalAwards=false
• 关键词: RI; Small; Collaborative; Research; Bio

Monitoring and understanding aquatic environments is critical to water sustainability. The goal of this award is to establish a theoretical framework and provide an enabling technology for robust underwater collaborative sensing with small, inexpensive robots. Inspired by the source-seeking behavior of live fish, computationally efficient algorithms are developed for cooperative tracing of the gradients of environmental fields, and their robustness is analyzed in the presence of localization error and changing communication topology. The algorithms are experimentally validated in thermal source seeking and tracing with a group of energy-efficient and highly maneuverable gliding robotic fish, which are enhanced in this project with optical communication and localization capabilities. Advanced controllers are developed for these robots to realize three-dimensional maneuvering and to track reference paths planned through collaborative sensing algorithms. This award offers fundamental understanding of limits and robustness properties of collaborative sensing by resource-limited robots, and contributes to the knowledge base in underwater communication and ranging for small robots. It enables technological advances for persistent sampling of versatile aquatic environments including coastal waters, lakes, and rivers, with a myriad of applications such as oil spill response, ecological monitoring, and port and drinking water security. The findings from this project are disseminated through publications, software sharing, and technology commercialization. The project provides interdisciplinary training opportunities for students, including those from underrepresented groups. Outreach activities, including museum/aquarium exhibits and teacher training, are developed to pique the interest of K-12 students, teachers, and the public in science and engineering.

监测和理解水生环境对于水的可持续性至关重要。 该奖项的目的是建立一个理论框架，并为与小型，廉价的机器人进行强大的水下协作感知提供有利的技术。 受到活鱼的源寻求行为的启发，开发了计算高效的算法，以合作地跟踪环境领域的梯度，并在存在本地化错误和不断变化的通信拓扑的情况下分析了它们的稳健性。这些算法在热源寻求和追踪中通过一组节能和高度可操作的滑行机器人鱼进行实验验证，在该项目中具有光学通信和定位能力，可以增强。为这些机器人开发了高级控制器，以实现三维操纵并跟踪通过协作传感算法计划的参考路径。 该奖项提供了对资源有限的机器人协作感知的限制和鲁棒性属性的基本理解，并为水下通信的知识库做出了贡献，并为小型机器人提供了范围。 它可以持续对包括沿海水域，湖泊和河流在内的多功能水生环境进行持续采样，并具有无数的应用，例如溢油响应，生态监测以及港口和饮用水安全。该项目的发现是通过出版物，软件共享和技术商业化传播的。该项目为学生提供了跨学科的培训机会，包括来自代表性不足的小组的培训机会。包括博物馆/水族馆展览和教师培训在内的外展活动的发展是为了引起K-12学生，教师和公众在科学和工程学方面的兴趣。

项目成果

Extended Kalman Filter-Based Active Alignment Control for LED Optical Communication

• DOI: 10.1109/tmech.2018.2841643
• 发表时间: 2018-05
• 期刊: IEEE/ASME Transactions on Mechatronics
• 作者: P. Solanki;Mohammed Al-Rubaiai;Xiaobo Tan

Adaptive single action control policies for linearly parameterized systems

线性参数化系统的自适应单动作控制策略

• 发表时间: 2019
• 期刊: Proceedings of 2019 ASME Dynamic Systems and Control Conference
• 作者: Osama Ennasr, Giorgos Mamakoukas

Distributed localization of a moving target: Structural observability-based convergence analysis

移动目标的分布式定位：基于结构可观测性的收敛分析

• 发表时间: 2018
• 期刊: Proceedings of 2018 American Control Conference
• 作者: Ennasr, O.;Tan, X.
• 通讯作者: Tan, X.

Ergodic exploration for adaptive sampling of water columns using gliding robotic fish

使用滑翔机器鱼进行水柱自适应采样的历经探索

• DOI: 10.1115/dscc2018-9179
• 发表时间: 2018
• 期刊: Proceedings of ASME 2018 Dynamic Systems and Control Conference
• 作者: Ennasr, Osama;Mamakoukas, Giorgos;Murphey, Todd;Tan, Xiaobo
• 通讯作者: Tan, Xiaobo