Multicopter swarms with decentralized structure possess the nature of flexibility and robustness, while efficient spatial-temporal trajectory planning still remains a challenge. This report introduces decentralized spatial-temporal trajectory planning, which puts a well-formed trajectory representation named MINCO into multi-agent scenarios. Our method ensures high-quality local planning for each agent subject to any constraint from either the coordination of the swarm or safety requirements in cluttered environments. Then, the local trajectory generation is formulated as an unconstrained optimization problem that is efficiently solved in milliseconds. Moreover, a decentralized asynchronous mechanism is designed to trigger the local planning for each agent. A systematic solution is presented with detailed descriptions of careful engineering considerations. Extensive benchmarks and indoor/outdoor experiments validate its wide applicability and high quality. Our software will be released for the reference of the community.

翻译：具有分散式结构的多机组群体具有灵活性和稳健性的性质,而有效的空间时空轨迹规划仍是一项挑战,本报告介绍了分散式空间时空轨迹规划,将完善的MINOCO轨迹代表制纳入多试剂设想方案,我们的方法确保每个物剂的高质量地方规划,受到在杂乱环境中协调群集或安全要求的任何制约。然后,当地轨迹生成被设计成一个不受限制的优化问题,在毫秒内有效解决。此外,还设计了一个分散式的不同步机制,以启动每个物剂的本地规划。一个系统化解决方案,详细描述仔细的工程考虑。广泛的基准和室内/室外实验验证了其广泛适用性和高质量。我们的软件将被发布供社区参考。