We investigate a multi-agent planning problem, where each agent aims to achieve an individual task while avoiding collisions with other agents. Each agent’s task is expressed as a Time-Window Temporal Logic (TWTL) specification defined over a discretized environment. We propose a distributed receding horizon algorithm for online planning of agent trajectories. We show that under mild assumptions on the environment, the resulting trajectories are always safe (collision-free) and lead to the satisfaction of the TWTL specifications or a finite temporal relaxation. Accordingly, each agent is guaranteed to safely achieve its task, possibly with some minimal finite delay. Performance of the proposed algorithm is demonstrated via numerical simulations and experiments with quadrotors.

我们研究了一个多代理计划问题，其中每个代理旨在完成一项单独的任务，同时避免与其他代理发生冲突。每个代理的任务都表示为在离散环境中定义的时间窗口时间逻辑（TWTL）规范。我们提出了一种用于智能体轨迹在线规划的分布式后退视野算法。我们表明，在对环境的温和假设下，所得轨迹始终是安全的（无碰撞），并导致TWTL规范的满足或有限的时间松弛。因此，可以保证每个代理可以安全地完成其任务，可能会有一些最小的有限延迟。通过数值仿真和四旋翼实验证明了该算法的性能。