This paper investigates the planning and control problems for multi-robot systems under linear temporal logic (LTL) specifications. In contrast to most of existing literature, which presumes a static and known environment, our study focuses on dynamic environments that can have unknown moving obstacles like humans walking through. Depending on whether local communication is allowed between robots, we consider two different online re-planning approaches. When local communication is allowed, we propose a local trajectory generation algorithm for each robot to resolve conflicts that are detected on-line. In the other case, i.e., no communication is allowed, we develop a model predictive controller to reactively avoid potential collisions. In both cases, task satisfaction is guaranteed whenever it is feasible. In addition, we consider the human-in-the-loop scenario where humans may additionally take control of one or multiple robots. We design a mixed initiative controller for each robot to prevent unsafe human behaviors while guarantee the LTL satisfaction. Using our previous developed ROS software package, several experiments are conducted to demonstrate the effectiveness and the applicability of the proposed strategies.

翻译：本文研究了线性时序逻辑（LTL）规范下多机器人系统的规划与控制问题。与大多数现有文献假设静态已知环境不同，本研究聚焦于存在未知移动障碍物（如行人穿行）的动态环境。根据机器人间是否允许局部通信，我们考虑了两种不同的在线重规划方法。当允许局部通信时，我们为每个机器人提出了一种局部轨迹生成算法，用于解决在线检测到的冲突；在另一种不允许通信的情况下，我们开发了模型预测控制器以反应式地避免潜在碰撞。两种方法均在可行时保证任务满足性。此外，我们考虑了人机协同场景，其中人类可能额外控制一台或多台机器人。我们为每台机器人设计了混合主动控制器，在保证LTL满足性的同时阻止不安全的人类行为。利用我们先前开发的ROS软件包，通过多项实验验证了所提策略的有效性与适用性。