Control ad libitum: a new framework for the design and development of control systems for heterogeneous robot teams

移动的机器人团队可以在行星探索、应急响应、安全、军事以及家庭和办公室环境中有效地执行许多有用的任务。这样一个团队可以用许多不同的方式构建，机器人的类型、控制系统、通信策略和学习算法都有许多可能性。本研究的目标是建立一个替代的通用框架，异构移动的机器人团队的控制系统的设计和开发，以克服现实世界中的应用程序的一些基本挑战。新的框架引入了三个关键功能的控制系统架构，即a）通过代理持久性和传播的动态分布式处理，B）可扩展的分层控制，不需要团队成员的先验知识，和c）社会学习应用于通信和知识共享在一个异构的团队。最终的结果将是一个高度模块化和容错的机器人团队，在分组和任务协调方面具有灵活性，并且能够随着时间的推移提高其集体性能。在这项研究中，以下一系列的任务将由这样一个团队执行：i）基本导航，ii）团队定位，iii）探索和映射，iv）对象发现，和v）对象收集。这些任务将在每个试验开始时团队未知的混乱环境中进行。

Teams of mobile robots can efficiently carry out many useful tasks in planetary exploration, emergency response, security, military, and home and office environments. Such a team can be constructed in numerous different ways, and there are many possibilities for the type of robots, control system, communication strategies, and learning algorithms. The goal of this research is to establish an alternative generic framework for the design and development of control systems for heterogeneous mobile robot teams to overcome some fundamental challenges of real-world applications. The new framework introduces three key features to the control system architecture, namely a) dynamically distributed processing through agent persistence and propagation, b) scalable hierarchical control requiring no prior knowledge of team membership, and c) social learning applied to communication and knowledge sharing in a heterogeneous team. The end result will be a team of robots that is highly modular and fault tolerant, flexible in terms of grouping and task coordination, and capable of improving its collective performance over time. In this research, the following series of tasks will be performed by such a team: i) basic navigation, ii) team localization, iii) exploration and mapping, iv) object discovery, and v) object collection. These tasks will be carried out in a cluttered environment that is unknown to the team at the outset of each trial.