CDS&E: A Computational Framework for Parsimonious Sonar Sensing

CDS

• 批准号: 1762577
• 负责人: Hongxiao Zhu
• 金额: $ 66.85万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1762577&HistoricalAwards=false
• 关键词: CDS& Computational; Framework; Parsimonious; Sonar

Autonomous sensing systems play an increasingly important role in health care, manufacturing, transportation, disaster response, national security and other activities. Sensing systems in platforms such as autonomous vehicles often require clear lines-of-sight and are inefficient. They generate large amounts of data that cannot be processed by small platforms with limited onboard computation. This project lays the foundation for a new transformative data-centered efficient sensing platform based on bats' bio-sonar. The researchers will develop a computational framework that facilitates estimation of environmental parameters for sensing and navigation--enabling enhanced performance in complex environments and with reduced hardware requirements. This enables the use of autonomous devices for a broad scope of applications ranging from cooperative robots to medical devices and micro-air vehicles. The project will also offer multidisciplinary training to university students and will engage K-12 students in outreach activities.This project will develop a computational approach to advance the discovery and understanding of parsimonious sonar sensing in complex environments. The researchers will perform large-scale simulations to generate densely vegetated environments and vegetation echoes; develop novel statistical models to extract echo signatures and learn their relation to environmental parameters and design dynamic algorithms for sensing and navigation. This computational approach provides enabling tools--validated using simulated and experimental data--to advance the community's ability to develop adaptive models for various sensing scenarios and enable novel sensing paradigms. Simulation algorithms and algorithms for sensing and navigation will be integrated into open source packages and made available on GitHub. The conceptual framework will be published in appropriate journals.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

自主传感系统在医疗保健、制造业、交通运输、灾害响应、国家安全和其他活动中发挥着越来越重要的作用。自动驾驶汽车等平台中的传感系统通常需要清晰的视线，效率低下。它们生成的大量数据无法由机载计算有限的小型平台处理。该项目为基于蝙蝠生物声纳的以数据为中心的新型高效传感平台奠定了基础。研究人员将开发一种计算框架，促进对传感和导航环境参数的估计，从而在复杂环境中提高性能并降低硬件要求。这使得自主设备能够用于从协作机器人到医疗设备和微型飞行器的广泛应用。该项目还将为大学生提供多学科培训，并将让K-12学生参与外联活动，该项目将开发一种计算方法，以促进在复杂环境中发现和理解吝啬声纳传感。 研究人员将进行大规模模拟，以生成密集的植被环境和植被回波;开发新的统计模型来提取回波特征，并了解它们与环境参数的关系，并设计用于传感和导航的动态算法。这种计算方法提供了使能工具-使用模拟和实验数据进行验证-以提高社区为各种传感场景开发自适应模型的能力，并实现新颖的传感模式。 传感和导航的仿真算法和算法将被集成到开源软件包中，并在GitHub上提供。 该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Crop Height and Plot Estimation for Phenotyping from Unmanned Aerial Vehicles using 3D LiDAR

使用 3D LiDAR 对无人机表型进行作物高度和地块估计

• DOI: 10.1109/iros45743.2020.9341343
• 发表时间: 2021
• 期刊: International Conference on Intelligent Robots and Systems (IROS
• 作者: Dhami, Harnaik;Yu, Kevin;Xu, Tianshu;Zhu, Qian;Dhakal, Kshitiz;Friel, James;Li, Song;Tokekar, Pratap
• 通讯作者: Tokekar, Pratap

Recreating Bat Behavior on Quad-rotor UAVs-A Simulation Approach

• 发表时间: 2020-02
• 作者: M. H. Tanveer;Antony Thomas;Xiaowei Wu;R. Müller;Pratap Tokekar;Hongxiao Zhu

Fast Simulation of Trees and Forests for Bat-inspired Sonar Sensing

快速模拟树木和森林以实现蝙蝠声纳传感

• DOI: 10.1109/icict55905.2022.00041
• 发表时间: 2022
• 期刊: 2022 5th International Conference on Information and Computer Technologies (ICICT
• 作者: Wahed, M.;Islam, M.;Wu, X.;Zhu, H.
• 通讯作者: Zhu, H.