NNA: Dynamic Vehicle-Terrain Modeling and Control of Lightweight Ground Robots in Snow and Sand

NNA:雪地和沙地中轻型地面机器人的动态车辆地形建模和控制

基本信息

  • 批准号:
    1824687
  • 负责人:
  • 金额:
    $ 41.53万
  • 依托单位:
  • 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:
    2019-01-01 至 2023-09-30
  • 项目状态:
    已结题

项目摘要

This research project seeks fundamental understanding of the dynamics of wheeled vehicles moving through soft terrain such as snow and sand. The project will derive models of movement that incorporate improved descriptions of interactions between the wheels and the ground. These innovative models will allow the treatment of, for example, lightweight vehicles and easily crumbled terrain. These models will allow the robot to predict when it is in danger of getting irrevocably stuck. New model-based control techniques will then allow the robot to avoid this danger, for example, by repeated compaction of the terrain, appropriate modulation of cable forces from a towed load, or simply revising the planned route. The results will be deployed in mobile ground robot systems capable of traversing Arctic regions untended, carrying or towing sensor packages to provide "ground truth" data for comparison to satellite or aircraft measurements. No lightweight autonomous mobile platform currently exists that can roam Arctic terrain autonomously for long periods of time, without becoming immobilized by pockets of low cohesion snow. This project builds upon the Investigator's success with similar robots used in the more uniform and predictable terrain of the Antarctic. This project advances the national health, prosperity, and welfare by enabling long-range, long-duration scientific surveys of the Arctic region, that will provide improved understanding of the response of Arctic systems to natural and human activity. This project also supports the NSF Big Idea on Navigating the New Arctic. Finally, the project will support new content in the interdisciplinary engineering design experience for Dartmouth undergraduates, and will provide new material to a hands-on Arctic science outreach program for high school students from the US, Denmark, and Greenland.Existing vehicle-terrain models have been derived and validated for heavy vehicles, and it has been shown that the behavior of lightweight vehicles differs from what these models predict. As a result, it is difficult to anticipate lightweight robot behavior in low mobility conditions using current models. The goal of this project is to develop vehicle-terrain models for lightweight ground robots that includes all the important dynamics, and integrates those models with vehicle design and control to maximize mobility. The project will develop estimation methods to detect incipient immobilization and control methods to avoid immobilization by reshaping the terrain?s shear stress capacity and modulating towed load. A modular robotic platform will be developed to acquire data for deriving and validating vehicle-terrain models and control approaches for lightweight robot models. The platform will allow rapid modification of wheel/grouser geometry, ground pressure, and drawbar load to obtain parametric data in situ. Higher fidelity vehicle-terrain models enable control schemes comprised of model-based prediction of incipient immobilization that trigger control modes to avoid immobilization and enable a robot to make forward progress through soft terrain.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.
该研究项目旨在基本理解轮式车辆穿过柔软地形(例如雪和沙)的动态。该项目将得出运动模型,该模型结合了轮子与地面之间相互作用的改进描述。这些创新的模型将允许例如轻质车辆和易于崩溃的地形进行处理。这些模型将允许机器人预测何时有不可撤销的危险。然后,新的基于模型的控制技术将允许机器人避免这种危险,例如,通过重复对地形的压实,从拖曳负载中对电缆力进行适当的调节,或简单地修改计划的路线。结果将部署在能够遍历北极区域的移动地面机器人系统中,携带或牵引传感器包装,以提供“地面真相”数据,以与卫星或飞机测量值进行比较。目前没有轻巧的自主移动平台可以长时间自动漫游北极地形,而不会被低粘性雪的口袋固定而固定。该项目建立在研究者的成功基础上,该机器人在南极的更统一和可预测的地形中使用的类似机器人。该项目通过对北极地区进行远距离的长期科学调查来促进民族健康,繁荣和福利,这将提高人们对北极系统对自然和人类活动的反应的了解。该项目还支持NSF关于浏览新北极的大想法。 Finally, the project will support new content in the interdisciplinary engineering design experience for Dartmouth undergraduates, and will provide new material to a hands-on Arctic science outreach program for high school students from the US, Denmark, and Greenland.Existing vehicle-terrain models have been derived and validated for heavy vehicles, and it has been shown that the behavior of lightweight vehicles differs from what these models predict.结果,很难使用当前模型在低移动性条件下预测轻型机器人行为。该项目的目的是为包括所有重要动态的轻量级地面机器人开发车辆透水模型,并将这些型号与车辆设计和控制结合起来,以最大程度地提高移动性。 该项目将开发估计方法来检测初期的固定和控制方法,以避免通过重塑地形剪切应力能力和调节拖曳负载来避免固定。将开发一个模块化的机器人平台,以获取用于衍生和验证轻型机器人模型的车辆透水模型和控制方法的数据。该平台将允许快速修改车轮/格子几何形状,地面压力和拉杆负载,以便在原位获得参数数据。更高的忠诚度车辆模型可以使控制方案由基于模型的初期固定化预测组成,这些预测触发控制模式以避免固定模式,并使机器人能够通过柔和的地形通过柔软的地形进行进步。该奖项反映了NSF的法定任务,并认为通过基金会的知识优点和宽广的crietia crietia criperia criperia criperia criperia criperia criperia criperia criperia criperia criperia criperia criperia criperia recteria receptia criperia criperia recectia criperia criperia均值得一提。

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
MOBILITY MODES AND CONTROL OF A PASSIVELY-ARTICULATED MULTI-SEGMENT WHEELED VEHICLE
被动铰接多节轮式车辆的移动模式与控制
PROPRIOCEPTIVE SENSING OF TERRAIN FORCES BY COMPLIANT, FOUR-WHEELED ROVING MODULES
通过兼容的四轮漫游模块对地形力进行本体感知
Incipient Immobilization Detection for Lightweight Rovers Operating in Deformable Terrain
在可变形地形中运行的轻型漫游车的初始固定检测
RIGID WHEEL DESIGN AND EVALUATION FOR LIGHTWEIGHT SNOW ROVER
轻型雪地车的刚性轮设计与评估
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Laura Ray其他文献

Elemental Cognitive Acts, and Their Architecture
基本认知行为及其架构
  • DOI:
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    R. Granger;E. Bowen;Antonio Rodriguez;Laura Ray;Chris Kymn;Khari Jarrett
  • 通讯作者:
    Khari Jarrett
The new morbidity: use of school and community health care resources for behavioral, educational, and social-family problems.
新的发病率:使用学校和社区医疗保健资源来解决行为、教育和社会家庭问题。
  • DOI:
  • 发表时间:
    1981
  • 期刊:
  • 影响因子:
    8
  • 作者:
    Philip R. Nader;Laura Ray;Susan G. Brink
  • 通讯作者:
    Susan G. Brink
Velocity field in the McMurdo shear zone from annual ground penetrating radar imaging and crevasse matching
  • DOI:
    10.1016/j.coldregions.2020.103023
  • 发表时间:
    2020-05-01
  • 期刊:
  • 影响因子:
  • 作者:
    Laura Ray;Madeleine Jordan;Steven A. Arcone;Lynn M. Kaluzienski;Benjamin Walker;Peter Ortquist Koons;James Lever;Gordon Hamilton
  • 通讯作者:
    Gordon Hamilton
Feedforward and Feedback Processing of Spatiotemporal Tubes for Efficient Object Localization
用于高效目标定位的时空管前馈和反馈处理
Pregnancy outcomes following exposure to abatacept during pregnancy.
怀孕期间接触阿巴西普后的妊娠结局。

Laura Ray的其他文献

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{{ truncateString('Laura Ray', 18)}}的其他基金

Engaged student learning - Exploration and Design: Small group learning in engineering systems and control education
学生参与学习 - 探索与设计:工程系统和控制教育中的小组学习
  • 批准号:
    1611672
  • 财政年份:
    2016
  • 资助金额:
    $ 41.53万
  • 项目类别:
    Standard Grant
I-Corps: Real Time Acoustic Beamforming for Directed Listening
I-Corps:用于定向聆听的实时声学波束形成
  • 批准号:
    1312440
  • 财政年份:
    2013
  • 资助金额:
    $ 41.53万
  • 项目类别:
    Standard Grant
Collaborative Research: Flow and Fracture Dynamics in an Ice Shelf Lateral Margin: Observations and Modeling of the McMurdo Shear Zone
合作研究:冰架侧缘的流动和断裂动力学:麦克默多剪切带的观测和建模
  • 批准号:
    1245915
  • 财政年份:
    2013
  • 资助金额:
    $ 41.53万
  • 项目类别:
    Continuing Grant
PFI: Cognitive Signal Processing
PFI:认知信号处理
  • 批准号:
    1112753
  • 财政年份:
    2011
  • 资助金额:
    $ 41.53万
  • 项目类别:
    Standard Grant
Collaborative Research: Cool Robot to support Greenland science campaigns
协作研究:酷机器人支持格陵兰科学活动
  • 批准号:
    0806157
  • 财政年份:
    2010
  • 资助金额:
    $ 41.53万
  • 项目类别:
    Continuing Grant
GOALI: SMART ELECTROMAGNETIC SENSORS FOR STRUCTURAL AND MATERIAL DAMAGE IDENTIFICATION
目标:用于结构和材料损坏识别的智能电磁传感器
  • 批准号:
    0408844
  • 财政年份:
    2004
  • 资助金额:
    $ 41.53万
  • 项目类别:
    Standard Grant
SGER: Cool Robots: Scalable Mobile Robots for Instrument Network Deployment in Polar Climates
SGER:酷机器人:用于极地气候下仪器网络部署的可扩展移动机器人
  • 批准号:
    0343328
  • 财政年份:
    2003
  • 资助金额:
    $ 41.53万
  • 项目类别:
    Standard Grant
Enhancing Sensitivity of Vibration-based Damage Metrics using Feedback Control: Towards Dual Use Smart Structures
使用反馈控制增强基于振动的损伤度量的灵敏度:迈向双重用途智能结构
  • 批准号:
    9988414
  • 财政年份:
    2000
  • 资助金额:
    $ 41.53万
  • 项目类别:
    Standard Grant
Minimizing Nonlinear Process Model Uncertainty for Motion Control and Friction-Based Diagnostics
最小化运动控制和基于摩擦的诊断的非线性过程模型不确定性
  • 批准号:
    9721468
  • 财政年份:
    1998
  • 资助金额:
    $ 41.53万
  • 项目类别:
    Continuing Grant
Integrated Laboratory for Manufacturing Education
制造教育综合实验室
  • 批准号:
    9551466
  • 财政年份:
    1995
  • 资助金额:
    $ 41.53万
  • 项目类别:
    Standard Grant

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基于深度强化学习的大规模动态车辆路径规划研究
  • 批准号:
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