Motivated by the recent interest in cyber-physical and autonomous robotic systems, we study the problem of dynamically coupled multi-agent 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 multi-agent 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.

中文翻译：

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信号时态逻辑任务下基于屏障功能的多机器人协同控制

受最近对网络物理和自治机器人系统的兴趣所激发，我们研究了在一组信号时间逻辑任务下动态耦合的多主体系统的问题。特别地，这些信号时间逻辑任务中的每一个的满意度取决于一组不同的代理的行为。我们没有推导协作反馈控制律，而不是将代理动态和时间逻辑任务抽象到一个离散域中并在其中解决问题或使用基于优化的方法。这些控制律是基于分散的控制屏障功能条件，该条件导致不连续的控制律，这与类似于单主体案例的集中式条件相反。我们方法的好处是反馈控制中通常具有固有的鲁棒性，以及连续时间多智能体系统的满意度保证。更具体地，使用时变控制屏障功能，其考虑了手头信号时间逻辑任务的语义。对于信号时间逻辑任务的某些片段，我们进一步提出了一种构造这种控制屏障功能的系统方法。最后，我们在一个实验中展示了我们框架的有效性和鲁棒性，该实验包括一组三个全向机器人。我们进一步提出了构建这种控制屏障功能的系统方法。最后，我们在一个实验中展示了我们框架的有效性和鲁棒性，该实验包括一组三个全向机器人。我们进一步提出了构建这种控制屏障功能的系统方法。最后，我们在一个实验中展示了我们框架的有效性和鲁棒性，该实验包括一组三个全向机器人。