DART: Diversity-enhanced Autonomy in Robot Teams
DART: Diversity-enhanced Autonomy in Robot Teams
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DOI：
10.1177/0278364919839137
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发表时间：
2019-03
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影响因子：
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通讯作者：
Nora Ayanian
中科院分区：
文献类型：
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作者：
Nora Ayanian
本文定义了机器人团队（DART）多样性增强自治的研究领域，这是一种用于创建和设计多机器人协调策略的新型范式。尽管当前进行多机器人协调的方法在结构化的，充分理解的环境中取得了成功，但它们在非结构化的，不确定的环境（例如灾难响应）中并未成功。尽管在过去十年中，机器人硬件已经显着提高，但我们解决多机器人问题的方式却没有。即使在多机器人系统领域取得了重大进展，也存在相同的解决问题范式：做出假设以简化问题，并且对这些假设进行了优化的解决方案，并将其部署给整个团队。如果原始假设无效，则会导致脆性解决方案证明无能为力。本文介绍了一个新的多机器人问题解决范式，该范式使用了各种控制策略，这些控制策略在同一机器人团队中协同工作。这种方法将使多机器人系统在非结构化和不确定的环境中（例如在灾难响应，环境监测和军事应用中）更加健壮，并允许多机器人系统超越当今成功的高度结构化和高度控制的环境。
This paper defines the research area of Diversity-enhanced Autonomy in Robot Teams (DART), a novel paradigm for the creation and design of policies for multi-robot coordination. Although current approaches to multi-robot coordination have been successful in structured, well-understood environments, they have not been successful in unstructured, uncertain environments, such as disaster response. Although robot hardware has advanced significantly in the past decade, the way we solve multi-robot problems has not. Even with significant advances in the field of multi-robot systems, the same problem-solving paradigm has remained: assumptions are made to simplify the problem, and a solution is optimized for those assumptions and deployed to the entire team. This results in brittle solutions that prove incapable if the original assumptions are invalidated. This paper introduces a new multi-robot problem-solving paradigm which uses a diverse set of control policies that work together synergistically within the same team of robots. Such an approach will make multi-robot systems more robust in unstructured and uncertain environments, such as in disaster response, environmental monitoring, and military applications, and allow multi-robot systems to extend beyond the highly structured and highly controlled environments where they are successful today.