RI: Small: Robust Model-Based Identification, Navigation, and Control of Underactuated Underwater Vehicles

RI：小型：基于鲁棒模型的欠驱动水下航行器识别、导航和控制

• 批准号: 1909182
• 负责人: Louis Whitcomb
• 金额: $ 49.97万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1909182&HistoricalAwards=false
• 关键词: RI; Small; Robust; Model; Based

Over 70 percent of the Earth's surface is hidden by its oceans, which are believed to be the cradle of life on Earth. Yet, less is known about the sea floor and oceans than about the surface of the Moon. Scientific exploration of the oceans is critical to the understanding of the Earth's climate and life forms. However, most of the oceans are inhospitable to humans due to the immense depth, low temperatures, and the absence of light. Since the 1960's, oceanographers and engineers have worked towards the development of remotely-controlled underwater robots, with the goal of exploring the depths of the oceans. The fact that GPS does not work underwater makes underwater navigation especially challenging for autonomous robots. This project seeks to advance underwater exploration by developing new navigation and control methods to enable earth-science, commercial, and national-security missions that are beyond present capabilities.This project seeks to develop improved navigation and control methods for autonomous underactuated underwater vehicles (UUVs) through the development of novel approaches to model identification, model-based vehicle state estimation, and model-based adaptive control. The goal is to improve the accuracy of present-day underwater vehicle navigation by one to two orders of magnitude, down to sub-meter accuracy. Our approach is to develop novel robust RANSAC Nullspace-based Least-Square (NBLS) algorithms for the experimental identification of dual-model (surfaced and submerged) plant and actuator parameters of 6-DOF plant dynamic models for underactuated UUVs in the presence of sensor noise and outliers, to use these plant models in 6-DOF state estimators for underactuated UUVs to improve vehicle navigation precision, and to investigate switched nonlinear model-based adaptive controllers for underactuated UUVs to improve vehicle control precision. The stability of the proposed algorithms will be evaluated analytically and their performance will be evaluated both in simulation and in experiments with robotic hardwareThis 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.

超过 70% 的地球表面被海洋隐藏，海洋被认为是地球上生命的摇篮。 然而，人们对海底和海洋的了解还不如对月球表面的了解。对海洋的科学探索对于了解地球气候和生命形式至关重要。然而，由于深海、低温和缺乏光线，大多数海洋不适合人类居住。自 20 世纪 60 年代以来，海洋学家和工程师一直致力于开发遥控水下机器人，目标是探索海洋深处。 GPS 在水下不起作用这一事实使得水下导航对于自主机器人来说尤其具有挑战性。该项目旨在通过开发新的导航和控制方法来推进水下探索，以实现超出现有能力的地球科学、商业和国家安全任务。该项目旨在为自主欠驱动水下航行器（UUV）开发改进的导航和控制方法）通过开发模型识别、基于模型的车辆状态估计和基于模型的自适应控制的新方法。目标是将当今水下航行器导航的精度提高一到两个数量级，达到亚米级精度。我们的方法是开发新型稳健的基于 RANSAC 零空间的最小二乘 (NBLS) 算法，用于在存在传感器的情况下对欠驱动 UUV 的双模型（水面和水下）植物和 6 自由度植物动态模型的执行器参数进行实验识别噪声和异常值，在欠驱动 UUV 的 6 自由度状态估计器中使用这些工厂模型，以提高车辆导航精度，并研究基于切换非线性模型的自适应控制器欠驱动 UUV 可提高车辆控制精度。所提出算法的稳定性将进行分析评估，其性能将在模拟和机器人硬件实验中进行评估。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力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

Stable adaptive identification of fully‐coupled second‐order 6 degree‐of‐freedom nonlinear plant models for underwater vehicles: Theory and experimental evaluation

水下航行器全耦合二阶6自由度非线性对象模型的稳定自适应辨识：理论与实验评估

• DOI: 10.1002/acs.3235
• 发表时间: 2021-05
• 期刊: International Journal of Adaptive Control and Signal Processing
• 影响因子: 3.1
• 作者: McFarland, Christopher J.;Whitcomb, Louis L.
• 通讯作者: Whitcomb, Louis L.

Online Three-Axis Magnetometer Hard-Iron and Soft-Iron Bias and Angular Velocity Sensor Bias Estimation Using Angular Velocity Sensors for Improved Dynamic Heading Accuracy

在线三轴磁力计硬铁和软铁偏置以及角速度传感器偏置估计，使用角速度传感器提高动态航向精度

• DOI: 10.55417/fr.2022033
• 发表时间: 2022-03
• 期刊: Field Robotics
• 作者: Spielvogel, Andrew;Shah, Abhimanyu;Whitcomb, Louis
• 通讯作者: Whitcomb, Louis

Uniform Complete Observability of Mass and Rotational Inertial Parameters in Adaptive Identification of Rigid-Body Plant Dynamics

刚体对象动力学自适应识别中质量和旋转惯性参数的一致完整可观测性

• DOI: 10.1109/icra48506.2021.9561892
• 发表时间: 2021-05
• 期刊: 2021 IEEE International Conference on Robotics and Automation (ICRA
• 作者: Paine, Tyler M.;Whitcomb, Louis L.
• 通讯作者: Whitcomb, Louis L.

Performance Analysis of Ice-Relative Upward-Looking Doppler Navigation of Underwater Vehicles Beneath Moving Sea Ice

移动海冰下水下航行器冰相对上视多普勒导航性能分析

• DOI: 10.3390/jmse9020174
• 发表时间: 2021-02
• 期刊: Journal of Marine Science and Engineering
• 影响因子: 2.9
• 作者: Barker, Laughlin D.;Whitcomb, Louis L.
• 通讯作者: Whitcomb, Louis L.

Scientific Challenges and Present Capabilities in Underwater Robotic Vehicle Design and Navigation for Oceanographic Exploration Under-Ice

冰下海洋勘探水下机器人车辆设计和导航的科学挑战和现有能力

• DOI: 10.3390/rs12162588
• 发表时间: 2020-08
• 期刊: Remote Sensing
• 影响因子: 5
• 作者: Barker, Laughlin D.;Jakuba, Michael V.;Bowen, Andrew D.;German, Christopher R.;Maksym, Ted;Mayer, Larry;Boetius, Antje;Dutrieux, Pierre;Whitcomb, Louis L.
• 通讯作者: Whitcomb, Louis L.