  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.
