Safe, Resilient and Efficient Operation of Autonomous Aerial and Ground Vehicles

自主空中和地面车辆的安全、弹性和高效运行

基本信息

  • 批准号:
    1662542
  • 负责人:
  • 金额:
    $ 39.65万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-07-01 至 2021-12-31
  • 项目状态:
    已结题

项目摘要

Autonomous vehicles working alone or in coordination with other autonomous vehicles have become indispensable in recent years for many military and law enforcement missions (e.g., in surveillance, long-range communication, target acquisition and tracking, and even weapon delivery). Most recently, the aerial versions of these autonomous vehicles ('flying robots' or 'drones') have entered the civilian sector and have been used successfully in many applications such as fire detection, crop dusting, aerial surveying, entertainment industry, traffic monitoring, infrastructure inspection, weather/hurricane monitoring, and commercial product delivery, to name a few. The unmanned air vehicle (UAV) market is exploding and most often than not these autonomous vehicles will have to operate in an environment that is highly uncertain, and even adversarial. For instance, for the case of unmanned aerial or marine/underwater vehicles winds or sea currents have a great impact on system performance. Similarly, self-driving vehicles must operate and interact with the surrounding traffic flow. The theory and methodologies developed in this research will make it possible to enable better coordination of such autonomous vehicles and systems, thus increasing their efficiency, reliability, and overall performance. The results of this research will help in extending the usability and endurance of aerial and marine autonomous vehicles and contribute to the safe operation of self-driving vehicles in traffic. The educational aspects of the project also includes efforts for involving minority and other under-represented students in the research. The research tackles a fundamental problem in the area of differential games and optimal trajectory generation for autonomous vehicles operating in the presence of exogenous or endogenous disturbances. Recent advances in the analysis of coordinated control of multi-agent systems in the presence of external flow fields using Voronoi-like decompositions, along with numerical techniques based on level sets will be utilized to solve multi-agent pursuit-evasion and target assignment problems in a numerically efficient manner. A novel reachability set inclusion property allows for the solution of a large class of such pursuit-evasion problems with multiple agents, even under the influence of external disturbances such as the drift field. The results of this research will allow coordination strategies and distributed pursuit-evasion protocols that go beyond the usual Euclidean metrics to establish proximity relationships between the agents, including time, energy and fuel. Extensions to stochastic environments will also be addressed, by leveraging new decomposition methods to solve stochastic partial differential equations arising from a stochastic formulation of level set propagation.
近年来,单独工作或与其他自主车辆协调工作的自主车辆对于许多军事和执法任务(例如,在监视、远程通信、目标获取和跟踪,甚至武器投放方面)。最近,这些自动驾驶车辆的空中版本(“飞行机器人”或“无人机”)已进入民用领域,并已成功用于许多应用,例如火灾探测,作物除尘,航空测量,娱乐业,交通监测,基础设施检查,天气/飓风监测和商业产品交付,仅举几例。无人机(UAV)市场正在爆炸式增长,这些自动驾驶汽车通常不得不在高度不确定甚至是敌对的环境中运行。例如,对于无人驾驶航空器或海洋/水下航行器,风或海流对系统性能有很大影响。同样,自动驾驶车辆必须与周围的交通流进行操作和互动。在这项研究中开发的理论和方法将使人们能够更好地协调这些自动驾驶汽车和系统,从而提高其效率,可靠性和整体性能。这项研究的结果将有助于扩展空中和海上自动驾驶车辆的可用性和耐久性,并有助于自动驾驶车辆在交通中的安全运行。该项目的教育方面还包括努力让少数民族和其他代表性不足的学生参与研究。该研究解决了在存在外源性或内源性干扰的情况下运行的自动驾驶车辆的微分博弈和最优轨迹生成领域中的一个基本问题。在外部流场的存在下,使用Voronoi分解,沿着基于水平集的数值技术的多智能体系统的协调控制分析的最新进展将被用来解决多智能体的追求,逃避和目标分配问题,在数值上有效的方式。 一种新的可达集包含属性允许的解决方案的一大类这样的追求-逃避问题与多个代理,即使在外部干扰,如漂移场的影响下。这项研究的结果将允许协调策略和分布式追求逃避协议,超越通常的欧几里得度量,以建立代理之间的邻近关系,包括时间,能量和燃料。 扩展到随机环境也将得到解决,利用新的分解方法来解决随机偏微分方程所产生的随机制定的水平集传播。

项目成果

期刊论文数量(13)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Stochastic Differential Games: A Sampling Approach via FBSDEs
  • DOI:
    10.1007/s13235-018-0268-4
  • 发表时间:
    2018-06
  • 期刊:
  • 影响因子:
    1.5
  • 作者:
    Ioannis Exarchos;Evangelos A. Theodorou;P. Tsiotras
  • 通讯作者:
    Ioannis Exarchos;Evangelos A. Theodorou;P. Tsiotras
Safe Optimal Control Under Parametric Uncertainties
参数不确定性下的安全最优控制
  • DOI:
    10.1109/lra.2020.3010491
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    5.2
  • 作者:
    Makkapati, Venkata Ramana;Sarabu, Hemanth;Comandur, Vinodhini;Tsiotras, Panagiotis;Hutchinson, Seth
  • 通讯作者:
    Hutchinson, Seth
Reachability-Based Covariance Control for Pursuit-Evasion in Stochastic Flow Fields
随机流场中基于可达性的协方差控制的追踪规避
  • DOI:
    10.2514/6.2022-1382
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Makkapati, Venkata Ramana;Ridderhof, Jack;Tsiotras, Panagiotis
  • 通讯作者:
    Tsiotras, Panagiotis
Covariance Steering for Discrete-Time Linear-Quadratic Stochastic Dynamic Games
离散时间线性二次随机动态博弈的协方差引导
  • DOI:
    10.1109/cdc42340.2020.9303947
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Makkapati, Venkata Ramana;Rajpurohit, Tanmay;Okamoto, Kazuhide;Tsiotras, Panagiotis
  • 通讯作者:
    Tsiotras, Panagiotis
Trajectory Desensitization in Optimal Control Problems
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Panagiotis Tsiotras其他文献

Communication-Aware Map Compression for Online Path-Planning
用于在线路径规划的通信感知地图压缩
  • DOI:
    10.48550/arxiv.2309.13451
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Evangelos Psomiadis;Dipankar Maity;Panagiotis Tsiotras
  • 通讯作者:
    Panagiotis Tsiotras
Multi-Parameter Dependent Lyapunov Functions for the Stability Analysis of Parameter-Dependent LTI Systems
用于参数相关 LTI 系统稳定性分析的多参数相关 Lyapunov 函数
Time-Optimal Control of Axisymmetric Rigid Spacecraft Using Two Controls
轴对称刚性航天器的两种控制的时间最优控制
  • DOI:
  • 发表时间:
    1999
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Haijun Shen;Panagiotis Tsiotras
  • 通讯作者:
    Panagiotis Tsiotras
Zero-Sum Games Between Large-Population Heterogeneous Teams: A Reachability-based Analysis under Mean-Field Sharing
大规模异构团队之间的零和博弈:平均场共享下基于可达性的分析
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yue Guan;Mohammad Afshari;Panagiotis Tsiotras
  • 通讯作者:
    Panagiotis Tsiotras
Stabilization and Tracking of Underactuated Axisymmetric Spacecraft with Bounded Control
  • DOI:
    10.1016/s1474-6670(17)40326-0
  • 发表时间:
    1998-07-01
  • 期刊:
  • 影响因子:
  • 作者:
    Panagiotis Tsiotras;Jihao Luo
  • 通讯作者:
    Jihao Luo

Panagiotis Tsiotras的其他文献

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{{ truncateString('Panagiotis Tsiotras', 18)}}的其他基金

CPS: Medium: Learning-Enabled Assistive Driving: Formal Assurances during Operation and Training
CPS:中:支持学习的辅助驾驶:操作和培训期间的正式保证
  • 批准号:
    2219755
  • 财政年份:
    2022
  • 资助金额:
    $ 39.65万
  • 项目类别:
    Standard Grant
AstroSLAM - A Robust and Reliable Visual Localization and Pose Estimation Architecture for Space Robots in Orbit
AstroSLAM - 用于轨道空间机器人的稳健可靠的视觉定位和姿态估计架构
  • 批准号:
    2101250
  • 财政年份:
    2021
  • 资助金额:
    $ 39.65万
  • 项目类别:
    Standard Grant
RI: Small: Robust Autonomy for Uncertain Systems using Randomized Trees
RI:小型:使用随机树实现不确定系统的鲁棒自治
  • 批准号:
    2008686
  • 财政年份:
    2020
  • 资助金额:
    $ 39.65万
  • 项目类别:
    Continuing Grant
S&AS: FND: Decision-Making for Autonomous Systems with Limited Resources
S
  • 批准号:
    1849130
  • 财政年份:
    2019
  • 资助金额:
    $ 39.65万
  • 项目类别:
    Standard Grant
RI: Small: Incremental Sampling-Based Algorithms and Stochastic Optimal Control on Random Graphs
RI:小:基于增量采样的算法和随机图上的随机最优控制
  • 批准号:
    1617630
  • 财政年份:
    2016
  • 资助金额:
    $ 39.65万
  • 项目类别:
    Continuing Grant
CPS: Synergy: Collaborative Research: Adaptive Intelligence for Cyber-Physical Automotive Active Safety - System Design and Evaluation
CPS:协同:协作研究:网络物理汽车主动安全的自适应智能 - 系统设计和评估
  • 批准号:
    1544814
  • 财政年份:
    2015
  • 资助金额:
    $ 39.65万
  • 项目类别:
    Standard Grant
NRI: Information-Theoretic Trajectory Optimization for Motion Planning and Control with Applications to Space Proximity Operations
NRI:运动规划和控制的信息理论轨迹优化及其在空间邻近操作中的应用
  • 批准号:
    1426945
  • 财政年份:
    2014
  • 资助金额:
    $ 39.65万
  • 项目类别:
    Standard Grant
Environment-Agent Interaction in Autonomous Networked Teams with Applications to Minimum-Time Coordinated Control of Multi-Agent Systems
自治网络团队中的环境-智能体交互及其在多智能体系统最短时间协调控制中的应用
  • 批准号:
    1160780
  • 财政年份:
    2012
  • 资助金额:
    $ 39.65万
  • 项目类别:
    Standard Grant
GOALI/Collaborative Research: Advanced Driver Assistance and Active Safety Systems through Driver's Controllability Augmentation and Adaptation
GOALI/合作研究:通过驾驶员可控性增强和适应实现高级驾驶员辅助和主动安全系统
  • 批准号:
    1234286
  • 财政年份:
    2012
  • 资助金额:
    $ 39.65万
  • 项目类别:
    Standard Grant
Multiscale, Beamlet-Based Data Processing for the Solution of Shortest-Path Problems with Applications to Embedded Vehicle Autonomy
用于解决嵌入式车辆自主应用中最短路径问题的多尺度、基于子束的数据处理
  • 批准号:
    0856565
  • 财政年份:
    2009
  • 资助金额:
    $ 39.65万
  • 项目类别:
    Standard Grant

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