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DRONA: A Framework for Safe Distributed Mobile Robotics

机译:DRONA:安全分布式移动机器人的框架

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Distributed mobile robotics (DMR) involves teams of networked robots navigating in a physical space to achieve tasks in a coordinated fashion. A major challenge in DMR is to program the ensemble of robots with formal guarantees and high assurance of correct operation. To this end, we introduce DRONA, a framework for building reliable DMR applications. This paper makes three central contributions: (1) We present a novel and provably correct decentralized asynchronous motion planner that can perform on-the-fly collision-free planning for dynamically generated tasks. Moreover, the motion planner is the first to take into account the fact that distributed robots may have clocks that are only synchronized up to a tolerance, i.e., they are almost synchronous; (2) We formalize the DMR system as a mixed-synchronous system, and present a sound abstraction-based verification approach for DMR systems, and (3) DRONA provides a state-machine based language for safe event-driven programming of a DMR system and the code generated by the compiler can be executed on platforms such as the robot operating system (ROS). To demonstrate the efficacy of DRONA, we build and verify a priority mail delivery system. Using our abstraction-based verification approach we were able to find, within a few minutes, bugs which could not be found by performing random simulation for several hours. Our verified decentralized motion-planner scales efficiently for large number of robots (upto 128 robots) and workspace sizes (upto a 256x256 grid).
机译:分布式移动机器人(DMR)涉及到在物理空间中导航以协作方式完成任务的联网机器人团队。 DMR的主要挑战是对机器人整体进行编程,要有正式的保证和对正确操作的高度保证。为此,我们介绍了DRONA,这是一个用于构建可靠的DMR应用程序的框架。本文做出了三个主要贡献:(1)我们提出了一种新颖且可证明正确的分散式异步运动计划器,该计划器可以对动态生成的任务执行动态无碰撞计划。此外,运动计划器是第一个考虑到以下事实的人:分布式机器人的时钟可能仅同步到一定的容差,即它们几乎是同步的。 (2)我们将DMR系统形式化为混合同步系统,并提出了一种基于声音抽象的DMR系统验证方法,并且(3)DRONA提供了一种基于状态机的语言,用于DMR系统的安全事件驱动编程编译器生成的代码可以在诸如机器人操作系统(ROS)的平台上执行。为了证明DRONA的功效,我们构建并验证了优先邮件传递系统。使用我们的基于抽象的验证方法,我们能够在几分钟内发现通过执行数小时的随机模拟而无法找到的错误。我们经过验证的分散式运动计划器可有效地缩放以用于大量机器人(最多128个机器人)和工作区大小(最大256x256网格)。

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