Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics and AI, with numerous applications in real-world scenarios. One such scenario is filming scenes with multiple actors, where the goal is to capture the scene from multiple angles simultaneously. Here, we present a formation-based filming directive of task assignment followed by a Conflict-Based MAPF algorithm for efficient path planning of multiple agents to achieve filming objectives while avoiding collisions. We propose an extension to the standard MAPF formulation to accommodate actor-specific requirements and constraints. Our approach incorporates Conflict-Based Search, a widely used heuristic search technique for solving MAPF problems. We demonstrate the effectiveness of our approach through experiments on various MAPF scenarios in a simulated environment. The proposed algorithm enables the efficient online task assignment of formation-based filming to capture dynamic scenes, making it suitable for various filming and coverage applications.

翻译：多智能体路径规划（MAPF）是机器人学和人工智能中的一个基本问题，在现实场景中具有广泛应用。其中一个典型应用是多演员场景拍摄，目标是从多个角度同时捕捉场景。本文提出一种基于编队的拍摄任务分配策略，结合基于冲突的MAPF算法，实现多智能体高效路径规划，在完成拍摄目标的同时避免碰撞。我们扩展了标准MAPF框架以适应演员特定的需求与约束。该方法采用冲突导向搜索——一种广泛用于求解MAPF问题的启发式搜索技术。通过在模拟环境中对不同MAPF场景进行实验，验证了所提方法的有效性。该算法能够通过在线高效分配基于编队的拍摄任务，捕捉动态场景，适用于各类拍摄及覆盖应用。