CAREER: Algorithms for Minimalist Robot Teams

这个项目的目标是设计算法，使简单的移动机器人团队能够可靠地完成广泛的任务。关键的洞察力是，即使感知和运动都存在显著的不确定性，这样的团队也有可能进行有效的规划。这种方法建立在单个机器人极简主义现有工作的基础上，但也必须克服由于机器人之间的协调和沟通而产生的大量复杂问题。这项工作的一个显著特点是，问题在多个尺度上是复杂的和不平凡的：多机器人团队的规划不能与单个机器人的规划和控制问题完全脱钩。该项目结合了三个相关的研究工作。首先，它研究了表示每个机器人关于其自身状态以及关于其他机器人的状态和知识的不确定性的技术。其次，它为机器人之间的通信开发了节能和健壮的策略。第三，它将这些技术应用到专门的规划算法中，以允许机器人团队以分散的方式完成他们的任务。这项研究将产生一系列新的算法，这些算法将允许简单的机器人团队管理不确定性、沟通和规划，以便完成广泛的任务类别。这些算法将使更简单、更自主的机器人团队能够以更少的成本部署。这样的机器人将对我们社会的许多领域产生重大的积极影响，包括交通、太空探索和农业。更广泛的影响将包括为中学生开发和分发“隐蔽教育”游戏软件，以及培训本科生和研究生研究人员。

The objective of this project is to design algorithms that allow teams of simple mobile robots to complete a wide range of tasks reliably. The key insight is that effective planning is possible for such teams, even in spite of significant uncertainty stemming from both sensing and motion. This approach builds upon existing work on minimalism for single robots, but must also overcome substantial complications that arise from coordination and communication between the robots. A distinguishing feature of this work is that the problems are complex and nontrivial at multiple scales: Planning for the multi-robot teams cannot be fully decoupled from the planning and control issues for individual robots.The project combines three related research endeavors. First, it investigates techniques for representing each robot's uncertainty about its own state, and about the state and knowledge of the other robots. Second, it develops energy-efficient and robust strategies for communication between robots. Third, it applies these techniques in specialized planning algorithms to allow robot teams to complete their tasks in a decentralized manner.This research will result in a collection of new algorithms that will allow teams of simple robots to manage uncertainty, communication, and planning in order to complete broad classes of tasks. These algorithms will enable simpler, more autonomous teams of robots to be deployed with less expense. Such robots will have significant positive impact on many sectors of our society, including transportation, space exploration, and agriculture. Broader impact will include development and distribution of "covertly educational" game software for middle school students, and training of undergraduate and graduate student researchers.