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Barrier Function Based Collaborative Control of Multiple Robots Under Signal Temporal Logic Tasks

机译:基于障碍功能的信号时间逻辑任务下多个机器人的协作控制

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摘要

Motivated by the recent interest in cyber-physical and autonomous robotic systems, we study the problem of dynamically coupled multiagent systems under a set of signal temporal logic tasks. In particular, the satisfaction of each of these signal temporal logic tasks depends on the behavior of a distinct set of agents. Instead of abstracting the agent dynamics and the temporal logic tasks into a discrete domain and solving the problem therein or using optimization-based methods, we derive collaborative feedback control laws.These control laws are based on a decentralized control barrier function condition that results in discontinuous control laws, as opposed to a centralized condition resembling the single-agent case. The benefits of our approach are inherent robustness properties typically present in feedback control as well as satisfaction guarantees for continuous-time multiagent systems. More specifically, time-varying control barrier functions are used that account for the semantics of the signal temporal logic tasks at hand. For a certain fragment of signal temporal logic tasks, we further propose a systematic way to construct such control barrier functions. Finally, we show the efficacy and robustness of our framework in an experiment, including a group of three omnidirectional robots.
机译:近期对网络物理和自治机器人系统的兴趣激励,我们研究了一组信号时间逻辑任务下动态耦合的多层系统的问题。特别地,这些信号时间逻辑任务中的每一个的满足取决于不同组件的行为。而不是将代理动态和时间逻辑任务抽象到离散域中并解决其中的问题或使用基于优化的方法,我们推出协作反馈控制规律。这些控制法根据分散的控制障碍功能条件,导致不连续控制法律,而不是类似于单智能案件的集中条件。我们的方法的好处是通常存在于反馈控制中的固有的鲁棒性属性以及连续时间多层系统的满意保证。更具体地,使用时变控制屏障功能,该函数用于手头的信号时间逻辑任务的语义。对于信号时间逻辑任务的某个片段,我们进一步提出了一种系统的系统来构造这种控制屏障功能。最后,我们展示了我们在实验中的框架的功效和稳健性,包括一组三个全向机器人。

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