Robotic teamwork and collaboration

机器人团队合作

基本信息

  • 批准号:
    RGPIN-2014-04674
  • 负责人:
  • 金额:
    $ 3.93万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2017
  • 资助国家:
    加拿大
  • 起止时间:
    2017-01-01 至 2018-12-31
  • 项目状态:
    已结题

项目摘要

In the short term, I seek to develop algorithms to address problem of developing autonomous active observers: systems that can automatically select and collect information regarding the world around them. I will do this big focussing, in particular, on aspects of this problem where a target agent that wants its activities to be documented is being followed (or preceded) by one or more documentarians with which it seeks to cooperate, but without explicit communication or explicitly shared state. The observation or recording of events in the world is critical to our understanding of our environment and our management of it, be it a sequence of events in a power plant, the interactions of a biologist in an ecosystem that in being evaluated, the activities of an automated system at work, or the activities of the police for during a major event.This grant will address this problem on the theoretical front by building computational models that explain under what circumstances we can compute actions can be planned to allow a robot to follow a sequence of events associated with another moving agent, even allowing the use of multiple observers and multiple targets. This theoretical development will be coupled with the production of robotic systems that employ this theory to operate in real time using video input data to document other robots, people and/or their environment. As robotics and machine sensing have started to mature, the study of interactions between robots, and between robots and their environment has become the lynchpin of practical applications. My research program addresses multi- agent cooperative interaction specifically in the context of information-seeking tasks. These can be informally envisioned as the creation of principles supporting the development of intelligent observers, or more colloquially a class of “robotic video documentarians.” That is, the development of automated systems that can document evolving events in the world. To fully accomplish this kind of task, a robot must develop a plan that gets it in the right vantage points at the right times by predicting the movement of the dynamically changing subject(s), obstacles and occlusions. In the last 6 years my lab has made progress on both the theoretical constraints that govern robotic systems, as well as the experimental development and evaluation of robotic systems that walk, swim, and fly, with variants that operate indoors or outdoors, and even interact with one another across these disparate domains. This work has resulted in the last 6 years in roughly 50 refereed publications, and that base has allowed me to acquire experience solving multi-robot interaction problems in both theory, i simulation and in practice.To address the problem of developing robotic documentarians, I will begin by developing algorithms to address three inter-related aspects of the larger problem: determination of what visual events to observe and when, computation of optimal motion plans to allow intermittent observation of these visual events without explicit communication, and computing plans for the recovery of visual contact if the agents have become separated. Each of these algorithmic stages will then find embodiment in functioning laboratory systems where their performance in practice can be evaluated in controlled circumstances and compared with theoretical predictions and bounds.
在短期内,我寻求开发算法来解决开发自主主动观察者的问题:系统可以自动选择和收集有关它们周围世界的信息。我将特别关注这个问题的各个方面,其中一个希望记录其活动的目标代理正在被一个或多个记录者跟踪(或先于),它寻求与之合作,但没有明确的通信或明确的共享状态。观察或记录世界上的事件对于我们理解环境和管理环境至关重要,无论是发电厂的一系列事件,生物学家在被评估的生态系统中的相互作用,工作中的自动化系统的活动,还是警察在重大事件中的活动。这笔拨款将通过建立计算模型来解决这个问题,该模型将解释在什么情况下我们可以计算出可以计划的动作,从而允许机器人遵循与另一个移动代理相关的一系列事件,甚至允许使用多个观察者和多个目标。这一理论的发展将与机器人系统的生产相结合,机器人系统采用这一理论,使用视频输入数据实时操作,以记录其他机器人、人和/或他们的环境。随着机器人技术和机器传感技术的成熟,研究机器人之间以及机器人与环境之间的相互作用已成为实际应用的关键。我的研究项目是在信息搜寻任务的背景下,研究多智能体的合作互动。这些可以被非正式地设想为支持智能观察者发展的原则的创造,或者更通俗地说,一类“机器人视频纪录片”。也就是说,开发能够记录世界上不断变化的事件的自动化系统。为了完全完成这类任务,机器人必须制定一个计划,通过预测动态变化的物体、障碍物和遮挡的运动,在正确的时间到达正确的有利位置。在过去的6年里,我的实验室在控制机器人系统的理论约束方面取得了进展,也在机器人系统的实验开发和评估方面取得了进展,这些机器人系统可以行走、游泳和飞行,在室内或室外操作,甚至在这些不同的领域相互作用。这项工作在过去的6年里发表了大约50篇论文,这个基础让我在理论、模拟和实践中获得了解决多机器人交互问题的经验。为了解决开发机器人纪录片制作人的问题,我将首先开发算法来解决更大问题的三个相互关联的方面:确定要观察什么视觉事件以及何时观察,计算最佳运动计划以允许在没有明确通信的情况下间歇性地观察这些视觉事件,以及计算在代理分离时恢复视觉接触的计划。然后,这些算法阶段中的每一个都将在功能实验室系统中找到体现,在这些系统中,它们在实践中的表现可以在受控环境中进行评估,并与理论预测和界限进行比较。

项目成果

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Dudek, Gregory其他文献

Image stitching with dynamic elements
  • DOI:
    10.1016/j.imavis.2009.03.004
  • 发表时间:
    2009-09-02
  • 期刊:
  • 影响因子:
    4.7
  • 作者:
    Mills, Alec;Dudek, Gregory
  • 通讯作者:
    Dudek, Gregory
A Simple Tactile Probe for Surface Identification by Mobile Robots
  • DOI:
    10.1109/tro.2011.2119910
  • 发表时间:
    2011-06-01
  • 期刊:
  • 影响因子:
    7.8
  • 作者:
    Giguere, Philippe;Dudek, Gregory
  • 通讯作者:
    Dudek, Gregory
Simultaneous planning, localization, and mapping in a camera sensor network
  • DOI:
    10.1016/j.robot.2006.05.009
  • 发表时间:
    2006-11-30
  • 期刊:
  • 影响因子:
    4.3
  • 作者:
    Rekleitis, Ioannis;Meger, David;Dudek, Gregory
  • 通讯作者:
    Dudek, Gregory
Fidora: Robust WiFi-Based Indoor Localization via Unsupervised Domain Adaptation
  • DOI:
    10.1109/jiot.2022.3163391
  • 发表时间:
    2022-06-15
  • 期刊:
  • 影响因子:
    10.6
  • 作者:
    Chen, Xi;Li, Hang;Dudek, Gregory
  • 通讯作者:
    Dudek, Gregory
Collaborative Sampling Using Heterogeneous Marine Robots Driven by Visual Cues
使用视觉提示驱动的异构海洋机器人进行协作采样
  • DOI:
    10.1109/crv.2017.49
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Manjanna, Sandeep;Hansen, Johanna;Li, Alberto Quattrini;Rekleitis, Ioannis;Dudek, Gregory
  • 通讯作者:
    Dudek, Gregory

Dudek, Gregory的其他文献

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{{ truncateString('Dudek, Gregory', 18)}}的其他基金

Robotic Data Capture
机器人数据采集
  • 批准号:
    RGPIN-2019-05887
  • 财政年份:
    2022
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
Robotic Data Capture
机器人数据采集
  • 批准号:
    RGPIN-2019-05887
  • 财政年份:
    2021
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
NSERC Canadian Robotics Network
NSERC 加拿大机器人网络
  • 批准号:
    508451-2017
  • 财政年份:
    2021
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Strategic Network Grants Program
NSERC Canadian Robotics Network
NSERC 加拿大机器人网络
  • 批准号:
    508451-2017
  • 财政年份:
    2020
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Strategic Network Grants Program
Robotic Data Capture
机器人数据采集
  • 批准号:
    RGPIN-2019-05887
  • 财政年份:
    2020
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
Robotic Data Capture
机器人数据采集
  • 批准号:
    RGPIN-2019-05887
  • 财政年份:
    2019
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
NSERC Canadian Robotics Network
NSERC 加拿大机器人网络
  • 批准号:
    508451-2017
  • 财政年份:
    2019
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Strategic Network Grants Program
Robotic teamwork and collaboration
机器人团队合作
  • 批准号:
    RGPIN-2014-04674
  • 财政年份:
    2018
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
Robotic teamwork and collaboration
机器人团队合作
  • 批准号:
    RGPIN-2014-04674
  • 财政年份:
    2016
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Discovery Grants Program - Individual
Computational Tools for Active Sampling in Aquatic and Uncontrolled Environments
用于水生和不受控制环境中主动采样的计算工具
  • 批准号:
    RTI-2017-00888
  • 财政年份:
    2016
  • 资助金额:
    $ 3.93万
  • 项目类别:
    Research Tools and Instruments

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Robotic teamwork and collaboration
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  • 批准号:
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  • 财政年份:
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  • 资助金额:
    $ 3.93万
  • 项目类别:
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