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CAREER: Controlling Ecologically Destructive Processes with a Network of Intelligent Robotic Agents

CAREER: Controlling Ecologically Destructive Processes with a Network of Intelligent Robotic Agents
职业:通过智能机器人代理网络控制生态破坏过程
批准号:
1646921
负责人:
Mac Schwager
金额:
$31.73万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-06-01 至 2019-08-31

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中文摘要
翻译
该项目旨在通过一组机器人的智能、协调干预来控制破坏性环境过程,如森林火灾、石油泄漏和农业害虫侵扰。这需要开发全新的控制理论和算法工具来驱动机器人采取控制行动来调节环境过程。机器人的控制动作闭合了一个围绕机器人和环境的大尺度反馈回路,产生了复杂的动力学现象。该项目提出了三种不同时间尺度下的机器人-环境耦合系统的控制策略:(i)与机器人动力学相比,环境变化缓慢;(ii)环境和机器人动力学在同一时间尺度上,寻求即时控制效果;(iii)环境和机器人动力学在同一时间尺度上,寻求长期控制效果。提出了三种不同的基于优化的技术来生成每个状态的分散控制策略。研究了这些策略下机器人-环境系统的稳定性、收敛性和最优性。此外,在实验室和室外对四旋翼空中机器人网络进行了实验,证明了控制策略的实用性。该项目还结合了一个全面的教育和推广计划,使用四旋翼机器人作为教学工具,覆盖来自不同背景的所有年级的学生。最终,该项目旨在通过为一种新的机器人技术奠定基础,减轻石油和其他化学品泄漏、森林火灾、害虫侵扰和其他生态破坏性现象造成的经济、社会和生态破坏。
英文摘要
This project aims to control destructive environmental processes such as forest fires, oil spills, and agricultural pest infestations through the intelligent, coordinated intervention of a group of robots. This requires the development of fundamentally new control theoretic and algorithmic tools to drive the robots to take control actions to regulate the environmental process. The robots' control actions close a large-scale feedback loop around the robots and the environment, giving rise to complex dynamical phenomena. The project proposes control strategies for this coupled robot-environment system in three different timescale regimes: (i) the environment changes slowly compared to the robots' dynamics, (ii) the environment and robot dynamics are on the same timescale and immediate control effect is sought, and (iii) the environment and robot dynamics are on the same timescale and long-term control effect is sought. Three different optimization based techniques are proposed to generate decentralized control strategies for each regime. Stability, convergence, and optimality properties of the robot-environment system under these strategies are studied. Furthermore, experiments with a network of quadrotor aerial robots, both in the lab and outdoors, demonstrate the practicality of the control strategies. The project also incorporates a comprehensive education and outreach program using quadrotor robots as teaching tools to reach students from diverse backgrounds at all grade levels. Ultimately, the project seeks to alleviate the economic, social, and ecological damage caused by oil and other chemical spills, forest fires, pest infestations, and other ecologically destructive phenomena by laying the foundations of a new robotic technology.
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NRI: FND: COLLAB: Distributed Semantically-Aware Tracking and Planning for Fleets of Robots
  • 批准号:
    1830402
  • 项目类别:
    Standard Grant
  • 资助金额:
    $46.8万
  • 财政年份:
    2018
  • 负责人:
    Mac Schwager
  • 依托单位:
Collaborative Research: Compressive Robotic Sensing Systems: Gaining Efficiency through Sparsity in Dynamic Sensing Environments
  • 批准号:
    1562335
  • 项目类别:
    Standard Grant
  • 资助金额:
    $37.5万
  • 财政年份:
    2016
  • 负责人:
    Mac Schwager
  • 依托单位:
CAREER: Controlling Ecologically Destructive Processes with a Network of Intelligent Robotic Agents
  • 批准号:
    1350904
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $49.34万
  • 财政年份:
    2014
  • 负责人:
    Mac Schwager
  • 依托单位:
CPS: Breakthrough: Collaborative Research: Cyber-Physical Manipulation (CPM): Locating, Manipulating, and Retrieving Large Objects with Large Populations of Robots
  • 批准号:
    1330036
  • 项目类别:
    Standard Grant
  • 资助金额:
    $23.69万
  • 财政年份:
    2013
  • 负责人:
    Mac Schwager
  • 依托单位:
海外基金