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Brain Storm Robotics: An Automatic Design Framework for Multi-Robot Systems

机译:头脑风暴机器人技术:多机器人系统的自动设计框架

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Designing the collaborative mechanism is a fundamental problem for the multi-robot systems. It aims to determine the perception, communication, and motion strategies for a single robot to obtain the desired behavior at the system level. Generally, we can use manual design and automatic design, or the combination of the above two approaches for particular system behavior. With the increasing of task complexity and the uncertainty of surroundings, the adaptability and autonomy are hard to achieve with manual design approaches. By using the mechanism of learning or evolution, automatic design can generate sensor configurations, communication parameters, as well as control strategies automatically, which has been widely concerned in recent years. In this paper, the brainstorming method of collaborative problem-solving in human society is introduced into the design of multi-robot systems. This paper proposes an automatic design framework: Brain Storm Robotics(BSR), in which the system architecture, the representation of ideas, and the generation of new ideas are discussed. The effectiveness of the proposed BSR framework is verified by an example of designing an aggregation behavior for a swarm of robots. The results show that the control strategy designed by this framework is more efficient than that designed manually, which has outstanding development prospects. The future researches for the development of this potential framework are also discussed.
机译:设计协作机制是多机器人系统的基本问题。它旨在确定单个机器人的感知,通信和运动策略,以便在系统级别获得所需的行为。通常,对于特定的系统行为,我们可以使用手动设计和自动设计,或将以上两种方法结合使用。随着任务复杂性的增加和周围环境的不确定性,手动设计方法很难实现适应性和自治性。通过使用学习或进化机制,自动设计可以自动生成传感器配置,通信参数以及控制策略,这是近年来受到广泛关注的问题。本文将人类社会中协作问题解决的集思广益方法引入多机器人系统的设计中。本文提出了一个自动设计框架:Brain Storm Robotics(BSR),其中讨论了系统架构,思想表示和新思想的生成。通过为大量机器人设计聚集行为的示例,验证了所提出的BSR框架的有效性。结果表明,该框架设计的控制策略比人工设计的控制策略更有效,具有广阔的发展前景。还讨论了开发该潜在框架的未来研究。

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