Robotic teamwork and collaboration

机器人团队合作

• 批准号: RGPIN-2014-04674
• 负责人: Dudek, Gregory
• 金额: $ 3.93万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=566668
• 关键词: Robotic; teamwork; collaboration

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：可以自动选择和收集有关周围世界的信息的系统，我将特别关注这个问题的各个方面。希望其活动被记录的目标代理正在被一名或多名寻求合作的纪录片制作者跟踪（或之前），但没有明确的沟通或明确的共享状态。观察或记录世界上的事件对于我们来说至关重要。了解我们的环境和我们对环境的管理它是发电厂中的一系列事件、正在评估的生态系统中生物学家的相互作用、工作中的自动化系统的活动或重大事件期间警察的活动。这项拨款将解决这个问题。在理论方面，通过构建计算模型来解释在什么情况下我们可以计算可以规划的动作，以允许机器人遵循与另一个移动主体相关的一系列事件，甚至允许使用多个观察者和多个目标。将与采用该理论进行操作的机器人系统的生产相结合使用视频输入数据实时记录其他机器人、人和/或其环境随着机器人技术和机器传感的开始成熟，对机器人之间以及机器人与其环境之间的交互的研究已成为实际应用的关键。研究计划专门针对信息寻求任务中的多主体协作交互，这些可以被非正式地设想为支持智能观察者发展的原则，或者更通俗地说是一类“机器人视频纪录片”。开发能够记录世界上不断变化的事件的自动化系统，为了完全完成此类任务，机器人必须制定一个计划，通过预测动态变化的对象的运动，使其在正确的时间处于正确的有利位置。在过去的六年里，我的实验室在控制机器人系统的理论约束以及行走、游泳和飞行的机器人系统及其操作变体的实验开发和评估方面都取得了进展。室内或室外，甚至与人互动这项工作在过去 6 年中发表了大约 50 篇参考出版物，该基础使我能够在理论、模拟和实践中获得解决多机器人交互问题的经验。在开发机器人纪录片制作人的过程中，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观察这些视觉事件，以及恢复的计算计划如果代理已经分离，那么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，在受控环境下可以评估它们的实践表现，并与理论预测和界限进行比较。