This paper proposes a decentralized trajectory planning framework for the collision avoidance problem of multiple micro aerial vehicles (MAVs) in environments with static and dynamic obstacles. The framework utilizes spatiotemporal occupancy grid maps (SOGM), which forecast the occupancy status of neighboring space in the near future, as the environment representation. Based on this representation, we extend the kinodynamic A* and the corridor-constrained trajectory optimization algorithms to efficiently tackle static and dynamic obstacles with arbitrary shapes. Collision avoidance between communicating robots is integrated by sharing planned trajectories and projecting them onto the SOGM. The simulation results show that our method achieves competitive performance against state-of-the-art methods in dynamic environments with different numbers and shapes of obstacles. Finally, the proposed method is validated in real experiments.

翻译：本文提出了一种去中心化轨迹规划框架，用于解决存在静态与动态障碍物的环境中多微型飞行器（MAVs）的碰撞规避问题。该框架采用时空占据网格图（SOGM）作为环境表征，该图可预测邻近空间在近未来的占据状态。基于该表征，我们扩展了动力约束A*算法与走廊约束轨迹优化算法，以高效处理任意形状的静态与动态障碍物。通过共享规划轨迹并将其投影至SOGM，实现了通信机器人之间的碰撞规避。仿真结果表明，在具有不同障碍物数量与形状的动态环境中，该方法相较于现有最优方法展现出竞争性性能。最后，通过实际实验验证了所提方法的有效性。